#they benefit too much from this to be like. principled. even if people are essentially misgendering them in a way........

[snekdood]

i honestly feel like the reason a lot of people choose not to believe me about the SA my abuser did to me is bc they dont want to even begin for a second to have like. barely an inch of empathy for a man

[smusherina]

yard work - chapter 6 (regina george x reader)

fandom: Mean Girls (all media)

pairing: Regina George x OFC/Reader

summary: You'd been in the same class as Regina George since kindergarten. You'd lived on the same street even longer. Once upon a time, when life was sandbox disputes and who got the swing first arguments, you'd even been friends. Now, in junior year of high school, you doubted she even remembered you. The same couldn't be said about you. You definitely remembered her.

warnings(s): 2004 was not a good time for the gays. homophobia persists. insecurity about weight and insulting oneself about it.

chapter 1 / chapter 2 / chapter 3 / chapter 4 / chapter 5 / chapter 7

You dipped into your savings and got Regina a new, fancy moisturizer. You couldn't count on her using it instead of the lard, but well. Guide a horse to water, can't make it drink, and all that.

You didn't tell her about the Homecoming prank, though. She'd been pissed about that. Not for long, because then it turned into a sort of trend at Northshore and it only boosted her popularity.

You were perhaps more upset about it. Upset you'd let it happen, upset they'd done it in the first place, upset Regina stood there with Aaron. He didn't even look like he wanted to be there.

Regina managing to turn it around for her benefit didn't stop you from feeling bad. It was the principle of the thing. You'd taken some distance from her. Everybody, actually. People just didn't feel all that great to be around. You were betraying Regina by letting her be essentially bullied by Janis, you were tolerating Regina's abusive reign over the student body, Aaron was getting on your last nerve by simply existing, and your mom's death anniversary was coming up.

You went to the Georges' less. Regina came to yours when you didn't lie about having to catch up on homework or doing a project. You did do some yard work for them since you still needed the extra cash. Just basic things like raking leaves and doing small repairs here and there. You also covered the pool with Mrs George's help.

"Whew, I forget what a chore that is every year!" She wiped at her forehead. You laid on the grass, chest heaving. You'd carried maybe seventy per cent of that thing.

"You said it, Mrs George." You managed to get out.

"How many years have I been telling you to call me Jude. Or just mom." You looked up at her. She looked so much like Regina. Or Regina looked so much like her.

She'd known your mom. Cried harder at her funeral than your dad or even yourself. You hadn't really gotten it, at that point. She'd hugged you tight and told you what an amazing woman she was, that she hadn't deserved to go yet. She sent you food for weeks after, which you appreciated because dad was too busy sorting stuff out to cook for you.

She'd been more of a mom to you than your own had ever gotten to be. Still, it felt wrong to call her anything other than Mrs George. It was weird. Word association gone all wrong. Mom meant a casket being lowered into a hole on a bleak November day, an echoing house and an empty kitchen, sad and wistful things. Mrs George meant afternoons spent running around in the backyard, eating 'till your belly was full to bursting, happiness and summer.

"Many, many years." You groaned as you got up. "Is Reggie home?"

You figured it would be weird if you didn't go say hi, at least. You didn't want to cut her out entirely. It was just hard being around her when the weight of your own actions, and inactions, weighed on your shoulders.

She smiled in a way that told you she'd noticed your deflection. "In her room."

"Great. Oh, by the way, what did you do with the apples this year?"

"I convinced Rick to donate them to the women's shelter downtown. They'll be put to good use there."

"That's awesome," You put your hands to your hips and looked around. "Anything you want me to do?"

"I'll just hose down the rose bushes, you head on inside. Avoid the living room, Rick's on a conference call." She waved you off with a smile.

You trod through the house carefully, shoes in hand. You knew the Georges were a shoes-on household, but it just never felt right for you to walk on carpeted floors with your shoes on. What if you had stepped on dogshit? What then?

"Reg?" Her door was open a crack, so you peeked in. "You decent?"

"Yes, I'm decent." You could hear the eye roll in her voice. "What do you want?"

Yikes. She wasn't happy.

You walked in and closed the door behind you. She was on her bed, reading a book on her belly. She was snacking on some candy bar.

"I just came to say hi. I put the pool cover on with your mom." You walked up to her. "What're you reading?"

"I could hear you huffing and puffing all the way up here." She turned on her side to look at you. "The Catcher in the Rye. It's boring."

"I dunno, I liked it." You climbed in hesitantly. When she didn't protest, you settled down on your side facing her, head leaned against your palm.

"You've read it?" She tossed the book on the floor next to the bed, now giving you her full attention. "Can you write my paper?"

"Depends on how much you'll pay me." You grinned and rubbed your fingers together like you were handling cash.

"Boo, you whore." She pouted. "Aren't we supposed to be beyond that?"

"I don't do charity, my friend." You flopped onto your back and crossed your arms. Shit, she had a comfy bed. So soft but just firm enough, too. You let your eyes close. You were so tired from all that physical labour.

"Get off my bed, you traitor." You opened your eyes too late. She was already on you, pushing you, and you had no time to resist until you were toppling onto the floor. You clambered down in a mess of limbs and sheets, which you'd grabbed in your desperate attempt to stay aboard.

"Reg! Your bed is actually high up! Help me!" You felt like Mufasa clinging to the face of the cliff, fingers digging into the slippery bedding. One of your legs was still on the bed, but not securely enough that you would've been able to pull yourself to safety.

"Just put your leg on the floor, dumbass." She cackled, watching you panic over such a small drop.

"No, look, it's not that- close." You lowered your leg and your knee made contact with the floor. Regina fell back, gasping as she laughed. "Shut up, you teapot!"

"No! I'm not-" She tried to stifle the laughs escaping her, the real wheezing ones she didn't let out of their cage willingly, but one look at you set it off again. "Your hair!"

You lifted your hands to your head. "It's not my fault your sheets are fucking static."

By the time Mrs George came to inform you that she'd be starting on dinner, thus signifying you should probably go, Regina had stopped laughing, if just barely.

"Have you been using the moisturizer I gave you?" You tried to analyze her face. It didn't look any less flawless than usual.

"Yeah, it's really great. My old night lotion started smelling weird for some reason. Maybe it expired early or something." You just hummed in response.

"I should probably go home and make myself dinner too."

"I'll walk you down."

You walked down the stairs and to the backdoor, avoiding the living room despite the blaring of the TV. Mr George was definitely not on a call anymore.

"What're you making today?" Regina asked, standing somewhat awkwardly on the porch.

"Probably tacos. I found a great deal on some corn tortillas at the store. They're all going bad today, so. Gonna stuff myself."

"Save some for me, yeah?"

You weren't sure what she meant by that. "Sure."

You walked home and as you'd said, got started on dinner. Moving around the kitchen without Regina there in the way, chopping whatever vegetables into misshapen cubes, felt weird. She wasn't over that often, but you'd gotten used to it regardless.

It was perhaps your biggest flaw as a person, how intolerant you were to being alone. Ironic, considering how much time you had to spend alone.

If it was up to you, you would've made Birria tacos with a good cut of sirloin, but you didn't have the money for fresh cuts of beef. Besides, you hadn't even started on the stew, and that took a whole day. So, you settled on some basic ground beef filling. You had made Pico de Gallo earlier that day, so it was nice and flavourful by the time you were constructing your tacos.

Back when you'd still needed a babysitter, there had been this one Mexican lady who appeared on the roster most often. It was so long ago you couldn't remember her name. She'd made you call her Abuela. She was sweet and taught you the wonder of Latin American cuisine. From what you could understand, she'd been well-travelled and really loved food everywhere.

She stopped coming when all of your babysitters did. The last time you saw her, you hadn't known it would be the last time.

This time of year really made you a monster. A dull grey, depressing monster. You'd have to find some exciting hobby because even you were getting sick of this. Maybe cliff jumping?

A knock on your door was the last thing you expected when you were finally ready to chow down. Making such a huge amount of food took time.

"What?" You barked to whoever dared to disturb you. "Oh, shit."

"Is that how you greet all your dinner guests?" Regina asked, batting her eyelashes. She had on a deep red dress, shiny satin that licked at the curves and edges of her body just right. It reached all the way to her feet, where you could see black heels peeking out from under the hem. She stood taller than usual, but still so short you could see above her head. The dress was strapless as far as you could tell as her jacket was covering her shoulders. Sweetheart neckline and a clutch to match. She had a thin gold chain around her neck with a small R-charm on it. Gold hoop earrings, hair done up in curls.

A grin crept up onto her face as you continued to gape at her visage. "I know, right?" She posed, one hand holding the clutch at level with her thigh and one poised at her waist. "I'm so sexy."

"Yeah, uh, yes, you are." You stuttered, stunned and flustered. You wanted to touch her, feel the fabric of the dress with the tips of your fingers, grab a hold of her and press close to her. She looked so fucking good.

"Thanks, baby." She took a couple of steps forward to reach you and, nonchalant as could be, brushed her hand at your shoulder as if she were brushing off dust.

Your knees wobbled.

"I have dinner for us." You blurted out. "I, uh..." You needed to pull it together. "I'm gonna go change."

"You do that," Regina said with an indulgent smile. You shot up the stairs.

When you came back down, still tucking your shirt into your trousers and tie undone, Regina was sitting on the couch perusing a magazine. It was probably from last year or something, you didn't exactly update the stuff under the coffee table.

You coughed to get her attention. "Ready for dinner, Reggie?"

"Ugh, don't ruin the moment. Anything other than that."

"I'm Jorts and you're Reggie, that's how it's been." You reminded and gently plucked her clutch from her hands before gesturing for her to turn around. She did, looking a little confused. When you reached to take her jacket off, she recoiled.

"Um, I would like to keep it on." She said, the confidence from before diminishing.

"Oh, why?" You asked. "Are you cold?"

"No, it's just, um..." Regina George stammering. You didn't think you'd live to see the day. "I don't look like I used to before."

"What does that mean?" You checked her out, toes to forehead. Drop-dead gorgeous as always.

"I've gained a bunch of weight." She looked down as if she needed to be ashamed. "I barely fit into this gown. I had to suck in even with the Spanx. And I still look like a whale."

As much as you would've liked to be incredulous and loud about just how wrong she was, it didn't seem like the right course of action. She was being open and vulnerable with you.

"I don't think you look like a whale." You stepped close to her tentatively. You set the clutch on the coffee table. Then, just as tentatively, circled your arms around her. You slotted your fingers together at her lower back and pulled her to you so that your bellies touched.

"I couldn't hug a whale." You pointed out helpfully, leaning back slightly to still look her in the eyes. "I'd love to see the dress in its full glory."

Regina, hands fussing with unmade your tie, bit her lip in contemplation.

"Careful, don't mess up your lipstick." She rubbed her lips together at that, a smile threatening to break out.

"Fine. But you can't laugh or stare or anything."

"I swear." You put one hand on your heart and the other up. "Now turn around."

She did as you asked. "You're being awfully chivalrous."

"It's what you deserve, Reggie." You crooned jokingly, pulling the jacket from her shoulders. The dress was cut elegantly so that there were no straps, but bits of fabric hanging by her upper arms. Cold-shoulder. You hoped the jokes in your tone hid how nervous you were.

"What did I just say?" As if that little moment between you two hadn't even happened, she was right back to her normal self.

"Fine. But you'll always be my Reggie. I guess tonight we can pretend." You sighed. "Whatever you say, honey."

"Better." She turned and tugged at your tie. "Now, let's get you sorted."

"I had very little notice, okay?" You grumbled but bent down obediently so she'd have an easier time tying your tie. You'd used to play dress up mixed with house all the time. You'd nearly always been the dad and so, you had to wear a tie. Obviously. Mrs George had gotten tired of constantly being asked to do it, so she'd taught Regina.

Now, it felt a little different. For one, you were taller. Secondly, this wasn't a children's game. Maybe you were playing a little bit, pretending, but it didn't quite feel like that. There was something undeniably real about this.

"There." She said once she was finished, smoothing it out against your chest. "You couldn't find one matching the dress?"

"You're impossible to please." You chuckled. "I'll make sure to go tie shopping as soon as possible."

"Good." She liked to ignore your sardonic tone pretty often. "Now, what's on the menu?"

You tucked the rest of the shirt into your pants and, voila, you were done.

"Tacos, my lady." You offered up your arm half in jest. She hooked her wrist into the bend of your elbow with an incline of her head. Clearly, she was a girl that liked to be wined and dined.

You snuck a bottle from your dad's wine collection, hoping it wasn't some speciality. Looking at the label, it wasn't very old. Wine quality was assessed like that, right?

You ate your fills and then some, drinking wine all the while, then retreated to the couch to recover, and turned on the TV to watch while eating dessert. Sharing a pint of ice cream, curled up on the couch in fancy clothes, warm and away from the cold of late November, you wondered what had brought this on.

It wasn't an official date, that much you knew. Regina wasn't a lesbian like you. Maybe she was indulging you. That would mean she knew you had a crush on her. You hoped that wasn't true. Regina was an observant person, though. Fuck, that'd be humiliating.

It didn't feel like she was playing with you. It looked like she was having as much fun as you. Maybe she wanted to have a nice, romantic dinner without the pressure of having to impress or perform for her date.

It was nice she'd chosen you. Regardless of why she'd come here tonight, you were just glad she was with you. You'd had a lot of people leave, most of them never coming back. The exceptions to the rule were Regina and your dad. They were similar in that, but nothing else. When dad came back, he brought with him a never-pleased frown and a stifling presence. When Regina came back, she brought light.

She had her flaws. You had yours. Thanksgiving was right around the corner and Christmas would soon follow. You had no doubt that Janis had something nefarious planned for at least one of those events. Nothing was sure, things were undecided.

"I'm going for a smoke." You said when the episode ended.

"I'm coming with."

"You won't be getting one."

"I don't want it anyway. Cigarettes taste like shit."

You laughed and walked to the backdoor. Through it and onto the patio, you slumped onto the bench swing. Regina followed a lot more gracefully, heels chucked somewhere in the house, bundled up in the blanket she'd claimed as hers since the first time she slept over. She sat next to you and spread it over both your laps. You hummed in thanks and lit up.

Regina might've been a massive bitch. She had, and there was no denying it, done some awful things. And maybe it was fucked up for you to like one part of a person and not the whole of them, but did that count if you were sure that the undesirable part was all a facade?

"So..." You started. "Better than any of the dates Aaron took you to?" You couldn't help but ask. Veiled under a joke, you hoped your jealousy didn't show.

"Don't be cocky." She admonished, resembling her mom almost creepily. "He didn't really take me out."

"What? Why?" If you could openly date Regina there wouldn't be a limit to how much you'd be taking her out, showing her off to anybody who'd listen.

"How should I know?" She shrugged indignantly. "We broke up a little after Homecoming."

"What? I didn't hear about this."

"Really? I thought you would've since it was pretty big news for a while." You didn't want to admit you'd been purposefully avoiding rumours about the couple for the majority of their relationship. "He outlived his purpose."

"The Halloween Party and Homecoming." You clarified and she nodded.

You took a drag. Regina pulled what seemed like a candy bar out of her clutch. It was the same brand she'd been eating earlier today.

Considering she'd been insecure about her weight, you didn't comment on it. You took another drag. You couldn't shake off the feeling that there was something weird.

"Hey, can I look at the packaging of that?"

Wordlessly, Regina handed it over. You looked at the product info. Great, it was all in Swedish.

"Where'd you get these?"

"Cady got me a box of them. They're good for weight loss. Like, they just burn all your carbs." You furrowed your eyebrows and looked back at the product info. The numbers didn't seem like that of a weight loss product.

You didn't like she was eating something that would empty her stomach right after dinner. That couldn't have been healthy.

"You're trusting something Cady gave to you?"

She tilted her head, as if about to question you. Her mouth opened, then closed, and opened again.

"Shut up. Shut up."

You took a long drag.

Taglist: @autorasexy, @wedfan2, @unadulterated-moron, @modernsapphicism, @9unknown0, @sage-rose2000, @massive-honkas, @nattys-swiftie, @likefirenrain, @luz-enjoyer, @dandelions4us, @natashamaximoff-69, @alexkolax, @jareaul0ver, @here4theqts, @charleeeesworld, @natsbiggestfan1, @brocoliisscared

(i keep forgetting to add this note. comment on this post if you want on the taglist!)

[hypexion]

Dot and Bubble turned out to be much more than what the trailer offered, yet still I will post my list of words next to dots.

First up, in spite of it all, the episode is not escaping the "social media bad" allegations. More on that later

The core concept of the Doctor having to remotely guide someone out of a situation is excellent. Very Blink, but in real-time

The idea of being surrounded by a danger you're unaware of until someone reveals it is also pretty rad. And slightly terrifying

Like the scene where Lindy de-bubbles outside and loads of people are being eaten is messed up

Sadly I think it goes a little too far in having Lindy being unable to walk in a straight line without the bubble. I'm pretty sure that's not even how walking works

You could force the re-bubbling just by making it so she doesn't know the way out of the building. Then in the Plaza 55 scene just have her freak out and freeze because she's surrounded by scary monsters

The problem is that suddenly Lindy is capable of basic motor skills after a few minutes anyway so what was even the point

Also the Dots wanting to kill everyone felt kind of stupid to me for complex meta reasons. Social media might not have your best interests in mind, but the way it which it does so is not homicidal. It in fact needs you alive

The first big twist was pretty brutal. Surprise! The perky idiot was in fact evil!

This actually also clashes with Lindy previously being incapable of all thought since her plan requires fairly decent critical thinking skills to combine several pieces of information and to predict how revealing Ricky September's previous name might save her

This theoretically serves as the final hint of the other twist unless you already worked it out: The Finetimers are all racist. So much so that they walk off into the wilderness to die horribly

wow Ncuti Gatwa puts his all into that Doctor Speech

but there's a but

While it is good that the topic was not avoided, flattening all racist down into a vauge "wow look at those stupid racists" is not an amazing way to handle it?

There are smart bigots of all kinds and they are often the most dangerous ones

It also sort of glosses over how exactly Finetime is benefitting from whatever inequitable society they have

The audience reaction here is also not particularly inspiring here even on the things that aren't Fridge Horror

Some people are saying "woah the Finetimers didn't deserve to be saved" which is essentially not just missing the text of this episode but the entirety of Doctor Who. The Doctor's ethos is that everyone deserves to be saved. If the Daleks get mercy so does everyone else

Also what's going in this episode is genocide

And it gets worse. The episode shows us a very specific slice of the Finetimer's culture. They are directly stated to be the children of the rich upperclass.

The concept of a rich privileged elite only makes sense if the is an underclass from which the elite are distinct

Lindy is reflexively dismissive of the Doctor, and acts as if he should be obligated to help her, but she isn't surpised to see him. So whatever group Lindy thinks the Doctor is part of still existed when she moved to Finetime.

Therefore, I think it's incredibly likely that in addition to the rich racists, the Dots also murdered the entirety of Homeworld's underclass, for the "crime" of being that underclass.

So did the Dots turn against their creators for principled reasons, or did they simply absorb the values of the culture that created them, with the only difference being that they put themselves at the top of the hierarchy?

anyhow I think it would have been more messed up if Lindy realised "yeah we aren't going to make it" and abandoned the other Finetimers, while still being exactly as evil, bigoted and self-centered as she was before. Hell have her lie to the others that she's going to wait for more survivors then turn around and say "so what are we waiting for lets gooooo" in her airhead voice

[tyote]

since politics has been on my (and probably everyone's) brain a lot lately i took a shit-ton of political compass tests and averaged them all together, then fed them to a LLM (running locally) to specifically create a profile of people i probably wouldn't get along with politically, lmao.

and wouldn't ya know, me being true neutral once again means many people (at least on the internet) would probably not like me too much, ha

full report of my nemeses under the cut, 'cause it's thorough

"Tyler, with his unique blend of political philosophies, would likely find himself at odds with individuals who hold extreme or uncompromising views. Here's how he might view these perspectives:

Far-Left Extremists: Tyler respects the desire for equality and fairness that drives many on the far left. However, he believes that radical socialism or communism often overlooks the importance of personal property and small businesses, which he sees as vital for a healthy economy. In Tyler's view, these extreme ideologies can lead to the concentration of power in the hands of the state, stifling individual initiative and innovation. He worries that such systems can result in economic inefficiency, a lack of personal freedom, and even oppression, ultimately harming the very people they aim to help. Tyler sees these systems as potentially leading to authoritarianism under the guise of equality.

Far-Right Extremists: While Tyler understands the importance of national identity and community values, he strongly opposes the exclusionary and xenophobic policies promoted by far-right nationalists or supremacists. Despite his nativist tendencies, Tyler believes that a thriving society benefits from a variety of backgrounds and viewpoints. He sees extreme nationalism as a dangerous ideology that fosters division, hatred, and violence. Tyler's brand of nativism is about valuing community heritage and ensuring that immigration policies are compassionate, economically viable, and practical, balancing the nation's capacity to accept immigrants with the need for a straightforward, fair, and legal process.

Authoritarians: Tyler appreciates the need for strong leadership, but he firmly believes that power should be distributed and checked to prevent abuse. He opposes authoritarian figures like Joseph Stalin or Pol Pot because they centralize power and suppress individual freedoms, which contradicts his commitment to representative democracy and the rule of law. Tyler believes that a healthy democracy requires transparency, accountability, and the active participation of its citizens to prevent the rise of tyranny. He sees checks and balances as essential to safeguarding freedom and justice. Authoritarian regimes, in his view, are oppressive and detrimental to human rights.

Libertarian Extremists: Tyler recognizes the appeal of minimal government intervention and personal freedom championed by extreme libertarians. However, he believes that a completely laissez-faire approach can lead to economic inequality and social disparity. Tyler supports a balanced economic system that combines individual freedom with ethical principles and community responsibility. He thinks that some level of regulation is necessary to protect the vulnerable and ensure that everyone has a fair chance to succeed. In his view, a mix of personal liberty and social welfare creates a more equitable and just society.

Populists: Tyler understands the frustration that drives populist movements and the desire for change. However, he is wary of leaders who use divisive rhetoric and offer simplistic solutions to complex problems. Figures like Bernie Sanders and Hugo Chavez, who appeal to broad, sweeping changes, might clash with Tyler's centrist and pragmatic approach. Tyler believes that effective governance requires nuanced policies and thoughtful deliberation, rather than quick fixes and polarizing tactics. He values evidence-based decision-making over populist promises. Populist leaders, in his view, often exploit people's emotions and fears for political gain, leading to instability and poor governance.

In essence, Tyler values moderation, a variety of backgrounds and viewpoints, and ethical governance. He believes that extreme, uncompromising, or authoritarian views, regardless of their position on the political spectrum, often fail to address the complexities of society in a balanced and fair manner."

[acti-veg]

I feel like going vegan can be easy for some people but I also think a lot of people already have so much else to worry about, so they just don’t feel able to have the time or energy into researching veganism, learning new recipes, etc? It’s not that going vegan in itself is hard but if you have 100 other problems in your life sometimes small things can seem like too much?

also I feel like for some people, food may be the main source of pleasure in their life. So giving up their favourite foods can feel like a major sacrifice. I’m vegan myself, and I’m not saying this is a good enough reason not to be vegan, I don’t think it is, but I can see how it can be difficult for people - ofc I realise the animals’ suffering is far greater than the person giving up their favourite food, but to them, it might feel like a lot - and being completely honest, as a vegan, I don’t think many vegan alternatives to products taste as good as ‘the real thing’.

Idk I just think of my grandma when she was very old with dementia and not able to do much really - but she loved her food. I’d have found it really difficult to deny her non vegan food that she liked? what are your thoughts?

What you’re describing here is valid, but it’s also essentially just a description of the challenges of living an ethical life. There are always barriers to doing the right thing, and doing the wrong thing is usually quite a lot easier - that isn’t at all unique to veganism. Yes there are challenges and other things to worry about, but everyone should be doing their best to live well and to not cause harm when you can avoid it.

There are for sure people who experience real barriers to eating plant-based, some moreso than most, from health issues to food deserts, but there is really nothing unique about food when it comes to ethical decision making. We can advocate that people should do the right thing while acknowledging that doing so can be difficult.

I don’t think we need to be able to argue that vegan food tastes just as good (even though I think it does), or that it’s super easy for anyone to be vegan, we just need to be able to say that not exploiting animals and destroying our planet in the process is the right thing to do. It’s up to all of us as individuals to figure out our situation and how much we’re able to do the right thing in any context, but even if we’re not able to do it, it doesn’t change the fact that it is the right thing.

All veganism asks of us is to do our best, precisely because it is a moral principle and not a diet. Making ethical decisions will very often be more difficult - its easier to not think about companies you support, to not reflect on your own prejudices and to never challenge anyone else on theirs. You may have valid reasons for doing the wrong thing, hurting others to benefit yourself, for making other lives more difficult to make yours easier, but it being understandable and there being valid reasons behind it doesn’t make it any less wrong.

[nocturnal-desolation]

My standards are not high at all. I don't think of it that way. They should be the standard. Most people seem to have very low standards. That's the way I look at it.

They're just essential qualities and principles that I live by. Honesty, loyalty, accountability, critical thinking, a willingness to learn, a certain amount of intelligence, among many other things. But they're basic, they're very simple at their core, and I just expect from everybody else what I expect from myself, what I can deliver. No more, no less. It can't be too much. For example, I'd never just leave someone I like or do them wrong. Not even if it would benefit me a lot, financially, or if it would give me more status or whatever. I'd rather lose all the wrong people who don't value my loyalty towards another person than keep them around. Yes, indeed, you might end up alone. It has a lot to do with the fact that not everyone will appreciate what you stand for, what you do for them, especially if they don't know that you defended them in their absence. I don't try to convince these people of my worth, I don't try to make them stay, which doesn't mean I give up on them easily. It's just… if they're interested in my motives, in my true nature, in discussion and understanding, in clearing up misunderstandings, if they're actually interested in getting to know me on a personal level, they'll do all that on their own. Most people don't. I have to accept that, and sometimes it's better that way. They're usually interested in superficial things like looks, style, money and so on, but not in me as a person. That says a lot about them, not so much about me. And yes, it can hurt your feelings…

But no matter what you do, there's always a price to pay, and it's up to us to decide if it's worth it. I can say for sure that whenever I didn't do what felt right, I regretted it much more than when I did it, or when I stuck to my guns and paid the price.

My standards are so high I might end up alone.

[devoqdesign]

The Psychology Behind Effective User Onboarding

User onboarding is a critical first step in creating a positive user experience. When done right, it builds trust, reduces confusion, and encourages long-term engagement with your product. But to create an effective onboarding experience, it’s essential to understand the psychology behind what makes people stick with a new tool or service. Here’s a breakdown of key psychological principles that guide effective user onboarding.

1. First Impressions Matter: The Power of Primacy

The primacy effect in psychology tells us that people tend to remember the first piece of information they encounter more vividly. When it comes to user onboarding, this initial impression is crucial.

Create a Welcoming Introduction: Users should feel welcomed and valued from the very first screen. A friendly greeting, personal touch, or even a short message that explains the product’s core benefits can make users feel they’re in the right place.

Set Clear Expectations: Briefly guide users on what they’ll accomplish or experience during onboarding. This helps them feel prepared and gives them a sense of structure, which is comforting and motivating.

2. Simplicity and Clarity: The Cognitive Load Theory

Cognitive load theory states that our brains have limited processing capacity. Overloading users with too much information at once can lead to confusion and disengagement.

Break Down Tasks: Instead of overwhelming users with multiple features at once, break down the onboarding process into small, manageable steps. For example, introduce one feature at a time and allow users to interact with it before moving on.

Avoid Jargon: Use simple, user-friendly language to describe features and functions. Technical or complex language can confuse users, especially those who are new to the product.

3. Building Trust and Familiarity: The Mere Exposure Effect

The mere exposure effect is a psychological phenomenon where people develop a preference for things simply because they are familiar with them. The more users see and interact with your product, the more they are likely to trust and enjoy it.

Introduce Core Features First: Ensure that users become familiar with your product’s core features early in the onboarding process. This helps them understand the product’s main value and feel more confident in navigating it.

Use Repetition Wisely: If a feature is critical, reintroduce it naturally in different contexts or encourage users to use it multiple times. This reinforces its importance and makes the feature feel intuitive.

4. Progress and Motivation: The Zeigarnik Effect

The Zeigarnik Effect suggests that people are more likely to remember tasks they’ve started but haven’t completed. By giving users a sense of progress, you can encourage them to finish the onboarding process.

Use Progress Bars: A progress bar during onboarding shows users how far they’ve come and how close they are to completing the setup. This visual cue keeps users motivated to finish what they’ve started.

Celebrate Small Wins: Incorporate feedback elements, like checkmarks or small animations, to acknowledge when a user completes a step. This reinforces their progress and provides a sense of accomplishment.

5. Emotional Engagement: The Hook Model

The Hook Model is a psychological approach used in product design to create habitual engagement through triggers and rewards. An effective onboarding experience keeps users emotionally engaged with triggers, actions, and immediate rewards.

Provide Immediate Value: Show users the benefits of using your product as early as possible. For instance, allow them to complete a meaningful task, like setting up a profile or personalizing settings, to make them feel invested in the experience.

Encourage Micro-Interactions: Small interactions, like tapping a button or watching a short tutorial, keep users engaged. These micro-interactions make onboarding feel dynamic rather than a passive process.

6. Social Proof and Validation: Bandwagon Effect

The bandwagon effect is the psychological tendency to align behavior with what others are doing, which can be a powerful motivator in user onboarding.

Showcase Testimonials or Case Studies: If users see that others have had a positive experience, they’re more likely to trust and use the product themselves. Including short testimonials or success stories during onboarding can boost user confidence.

Display User Metrics: Mentioning the number of active users or the widespread adoption of your product can act as a subtle but powerful form of social proof, helping new users feel they’re making a wise choice.

7. Personalization and Control: Self-Determination Theory

Self-determination theory suggests that people are more motivated when they feel they have control over their actions. Personalized onboarding enhances user experience by catering to individual preferences and needs.

Offer Personalized Options: Allow users to customize aspects of the onboarding experience, such as themes, layouts, or feature preferences. This approach can make users feel more in control and satisfied with their experience.

Ask for Input: Ask users questions about their goals or preferences and tailor their onboarding experience accordingly. For instance, a fitness app might ask if the user’s goal is to lose weight or gain muscle, then personalize the experience based on their answer.

8. Creating a Flow State: Csikszentmihalyi’s Flow Theory

Psychologist Mihaly Csikszentmihalyi describes “flow” as a mental state of complete absorption in an activity. In an effective onboarding experience, users are guided into this state through engaging, well-paced steps that avoid unnecessary friction.

Design a Smooth Onboarding Flow: The onboarding process should have a clear, logical flow that gradually increases in complexity. For example, start with basic tasks and move to more advanced features as users become comfortable.

Provide Just-in-Time Information: Instead of explaining all features upfront, introduce each feature only when users need it. This minimizes cognitive load and allows users to stay focused on the task at hand.

9. Overcoming Uncertainty: Loss Aversion and Friction Reduction

Loss aversion is a psychological principle that suggests people prefer to avoid losses over acquiring equivalent gains. When users start with a new product, there’s often a feeling of uncertainty or “loss” of familiar territory.

Use Clear and Helpful Navigation: Ensure users know how to get help if they’re stuck during onboarding. Quick access to tooltips, FAQs, or chat support can reduce any anxiety they might feel.

Minimize Friction Points: Avoid unnecessary steps or tasks that could slow down or frustrate users. For example, if signing up requires personal information, consider allowing users to skip non-essential fields initially.

10. Reinforcement and Habit Formation: Operant Conditioning

Operant conditioning, a concept developed by psychologist B.F. Skinner, is the process of shaping behavior by rewarding desired actions. In onboarding, reinforcing positive actions can help create habits.

Reward Desired Actions: Celebrate key actions, like profile completion or completing tutorials, with small rewards like badges or confetti animations. These reinforcements encourage continued engagement.

Use Notifications as Reminders: Once users complete onboarding, gentle reminders or notifications can encourage them to revisit and use the product. These notifications should add value, such as tips or usage insights, rather than purely promoting engagement.

Conclusion

Understanding the psychology behind user onboarding can transform a basic introduction into an engaging and satisfying experience. By focusing on principles like cognitive load reduction, motivation, familiarity, and social proof, you can create an onboarding process that not only welcomes new users but actively encourages them to stay, explore, and become loyal advocates for your product. A thoughtful onboarding experience reflects the needs, behaviors, and motivations of users — ultimately shaping a strong foundation for their journey with your product.

View my profile for : UI/UX design, Mobile Design & Product Designer

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Machines

of

Loving Grace1

How AI Could Transform the World for the Better

October 2024

I think and talk a lot about the risks of powerful AI. The company I’m the CEO of, Anthropic, does a lot of research on how to reduce these risks. Because of this, people sometimes draw the conclusion that I’m a pessimist or “doomer” who thinks AI will be mostly bad or dangerous. I don’t think that at all. In fact, one of my main reasons for focusing on risks is that they’re the only thing standing between us and what I see as a fundamentally positive future. I think that most people are underestimating just how radical the upside of AI could be, just as I think most people are underestimating how bad the risks could be.

In this essay I try to sketch out what that upside might look like—what a world with powerful AI might look like if everything goes right. Of course no one can know the future with any certainty or precision, and the effects of powerful AI are likely to be even more unpredictable than past technological changes, so all of this is unavoidably going to consist of guesses. But I am aiming for at least educated and useful guesses, which capture the flavor of what will happen even if most details end up being wrong. I’m including lots of details mainly because I think a concrete vision does more to advance discussion than a highly hedged and abstract one.

First, however, I wanted to briefly explain why I and Anthropic haven’t talked that much about powerful AI’s upsides, and why we’ll probably continue, overall, to talk a lot about risks. In particular, I’ve made this choice out of a desire to:

Maximize leverage. The basic development of AI technology and many (not all) of its benefits seems inevitable (unless the risks derail everything) and is fundamentally driven by powerful market forces. On the other hand, the risks are not predetermined and our actions can greatly change their likelihood.

Avoid perception of propaganda. AI companies talking about all the amazing benefits of AI can come off like propagandists, or as if they’re attempting to distract from downsides. I also think that as a matter of principle it’s bad for your soul to spend too much of your time “talking your book”.

Avoid grandiosity. I am often turned off by the way many AI risk public figures (not to mention AI company leaders) talk about the post-AGI world, as if it’s their mission to single-handedly bring it about like a prophet leading their people to salvation. I think it’s dangerous to view companies as unilaterally shaping the world, and dangerous to view practical technological goals in essentially religious terms.

Avoid “sci-fi” baggage. Although I think most people underestimate the upside of powerful AI, the small community of people who do discuss radical AI futures often does so in an excessively “sci-fi” tone (featuring e.g. uploaded minds, space exploration, or general cyberpunk vibes). I think this causes people to take the claims less seriously, and to imbue them with a sort of unreality. To be clear, the issue isn’t whether the technologies described are possible or likely (the main essay discusses this in granular detail)—it’s more that the “vibe” connotatively smuggles in a bunch of cultural baggage and unstated assumptions about what kind of future is desirable, how various societal issues will play out, etc. The result often ends up reading like a fantasy for a narrow subculture, while being off-putting to most people.

Yet despite all of the concerns above, I really do think it’s important to discuss what a good world with powerful AI could look like, while doing our best to avoid the above pitfalls. In fact I think it is critical to have a genuinely inspiring vision of the future, and not just a plan to fight fires. Many of the implications of powerful AI are adversarial or dangerous, but at the end of it all, there has to be something we’re fighting for, some positive-sum outcome where everyone is better off, something to rally people to rise above their squabbles and confront the challenges ahead. Fear is one kind of motivator, but it’s not enough: we need hope as well.

The list of positive applications of powerful AI is extremely long (and includes robotics, manufacturing, energy, and much more), but I’m going to focus on a small number of areas that seem to me to have the greatest potential to directly improve the quality of human life. The five categories I am most excited about are:

Biology and physical health

Neuroscience and mental health

Economic development and poverty

Peace and governance

Work and meaning

My predictions are going to be radical as judged by most standards (other than sci-fi “singularity” visions2), but I mean them earnestly and sincerely. Everything I’m saying could very easily be wrong (to repeat my point from above), but I’ve at least attempted to ground my views in a semi-analytical assessment of how much progress in various fields might speed up and what that might mean in practice. I am fortunate to have professional experience in both biology and neuroscience, and I am an informed amateur in the field of economic development, but I am sure I will get plenty of things wrong. One thing writing this essay has made me realize is that it would be valuable to bring together a group of domain experts (in biology, economics, international relations, and other areas) to write a much better and more informed version of what I’ve produced here. It’s probably best to view my efforts here as a starting prompt for that group.

Basic assumptions and framework

To make this whole essay more precise and grounded, it’s helpful to specify clearly what we mean by powerful AI (i.e. the threshold at which the 5-10 year clock starts counting), as well as laying out a framework for thinking about the effects of such AI once it’s present.

What powerful AI (I dislike the term AGI)3 will look like, and when (or if) it will arrive, is a huge topic in itself. It’s one I’ve discussed publicly and could write a completely separate essay on (I probably will at some point). Obviously, many people are skeptical that powerful AI will be built soon and some are skeptical that it will ever be built at all. I think it could come as early as 2026, though there are also ways it could take much longer. But for the purposes of this essay, I’d like to put these issues aside, assume it will come reasonably soon, and focus on what happens in the 5-10 years after that. I also want to assume a definition of what such a system will look like, what its capabilities are and how it interacts, even though there is room for disagreement on this.

By powerful AI, I have in mind an AI model—likely similar to today’s LLM’s in form, though it might be based on a different architecture, might involve several interacting models, and might be trained differently—with the following properties:

In terms of pure intelligence4, it is smarter than a Nobel Prize winner across most relevant fields – biology, programming, math, engineering, writing, etc. This means it can prove unsolved mathematical theorems, write extremely good novels, write difficult codebases from scratch, etc.

In addition to just being a “smart thing you talk to”, it has all the “interfaces” available to a human working virtually, including text, audio, video, mouse and keyboard control, and internet access. It can engage in any actions, communications, or remote operations enabled by this interface, including taking actions on the internet, taking or giving directions to humans, ordering materials, directing experiments, watching videos, making videos, and so on. It does all of these tasks with, again, a skill exceeding that of the most capable humans in the world.

It does not just passively answer questions; instead, it can be given tasks that take hours, days, or weeks to complete, and then goes off and does those tasks autonomously, in the way a smart employee would, asking for clarification as necessary.

It does not have a physical embodiment (other than living on a computer screen), but it can control existing physical tools, robots, or laboratory equipment through a computer; in theory it could even design robots or equipment for itself to use.

The resources used to train the model can be repurposed to run millions of instances of it (this matches projected cluster sizes by ~2027), and the model can absorb information and generate actions at roughly 10x-100x human speed5. It may however be limited by the response time of the physical world or of software it interacts with.

Each of these million copies can act independently on unrelated tasks, or if needed can all work together in the same way humans would collaborate, perhaps with different subpopulations fine-tuned to be especially good at particular tasks.

We could summarize this as a “country of geniuses in a datacenter”.

Clearly such an entity would be capable of solving very difficult problems, very fast, but it is not trivial to figure out how fast. Two “extreme” positions both seem false to me. First, you might think that the world would be instantly transformed on the scale of seconds or days (“the Singularity”), as superior intelligence builds on itself and solves every possible scientific, engineering, and operational task almost immediately. The problem with this is that there are real physical and practical limits, for example around building hardware or conducting biological experiments. Even a new country of geniuses would hit up against these limits. Intelligence may be very powerful, but it isn’t magic fairy dust.

Second, and conversely, you might believe that technological progress is saturated or rate-limited by real world data or by social factors, and that better-than-human intelligence will add very little6. This seems equally implausible to me—I can think of hundreds of scientific or even social problems where a large group of really smart people would drastically speed up progress, especially if they aren’t limited to analysis and can make things happen in the real world (which our postulated country of geniuses can, including by directing or assisting teams of humans).

I think the truth is likely to be some messy admixture of these two extreme pictures, something that varies by task and field and is very subtle in its details. I believe we need new frameworks to think about these details in a productive way.

Economists often talk about “factors of production”: things like labor, land, and capital. The phrase “marginal returns to labor/land/capital” captures the idea that in a given situation, a given factor may or may not be the limiting one – for example, an air force needs both planes and pilots, and hiring more pilots doesn’t help much if you’re out of planes. I believe that in the AI age, we should be talking about the marginal returns to intelligence7, and trying to figure out what the other factors are that are complementary to intelligence and that become limiting factors when intelligence is very high. We are not used to thinking in this way—to asking “how much does being smarter help with this task, and on what timescale?”—but it seems like the right way to conceptualize a world with very powerful AI.

My guess at a list of factors that limit or are complementary to intelligence includes:

Speed of the outside world. Intelligent agents need to operate interactively in the world in order to accomplish things and also to learn8. But the world only moves so fast. Cells and animals run at a fixed speed so experiments on them take a certain amount of time which may be irreducible. The same is true of hardware, materials science, anything involving communicating with people, and even our existing software infrastructure. Furthermore, in science many experiments are often needed in sequence, each learning from or building on the last. All of this means that the speed at which a major project—for example developing a cancer cure—can be completed may have an irreducible minimum that cannot be decreased further even as intelligence continues to increase.

Need for data. Sometimes raw data is lacking and in its absence more intelligence does not help. Today’s particle physicists are very ingenious and have developed a wide range of theories, but lack the data to choose between them because particle accelerator data is so limited. It is not clear that they would do drastically better if they were superintelligent—other than perhaps by speeding up the construction of a bigger accelerator.

Intrinsic complexity. Some things are inherently unpredictable or chaotic and even the most powerful AI cannot predict or untangle them substantially better than a human or a computer today. For example, even incredibly powerful AI could predict only marginally further ahead in a chaotic system (such as the three-body problem) in the general case,9 as compared to today’s humans and computers.

Constraints from humans. Many things cannot be done without breaking laws, harming humans, or messing up society. An aligned AI would not want to do these things (and if we have an unaligned AI, we’re back to talking about risks). Many human societal structures are inefficient or even actively harmful, but are hard to change while respecting constraints like legal requirements on clinical trials, people’s willingness to change their habits, or the behavior of governments. Examples of advances that work well in a technical sense, but whose impact has been substantially reduced by regulations or misplaced fears, include nuclear power, supersonic flight, and even elevators.

Physical laws. This is a starker version of the first point. There are certain physical laws that appear to be unbreakable. It’s not possible to travel faster than light. Pudding does not unstir. Chips can only have so many transistors per square centimeter before they become unreliable. Computation requires a certain minimum energy per bit erased, limiting the density of computation in the world.

There is a further distinction based on timescales. Things that are hard constraints in the short run may become more malleable to intelligence in the long run. For example, intelligence might be used to develop a new experimental paradigm that allows us to learn in vitro what used to require live animal experiments, or to build the tools needed to collect new data (e.g. the bigger particle accelerator), or to (within ethical limits) find ways around human-based constraints (e.g. helping to improve the clinical trial system, helping to create new jurisdictions where clinical trials have less bureaucracy, or improving the science itself to make human clinical trials less necessary or cheaper).

Thus, we should imagine a picture where intelligence is initially heavily bottlenecked by the other factors of production, but over time intelligence itself increasingly routes around the other factors, even if they never fully dissolve (and some things like physical laws are absolute)10. The key question is how fast it all happens and in what order.

With the above framework in mind, I’ll try to answer that question for the five areas mentioned in the introduction.

1. Biology and health

Biology is probably the area where scientific progress has the greatest potential to directly and unambiguously improve the quality of human life. In the last century some of the most ancient human afflictions (such as smallpox) have finally been vanquished, but many more still remain, and defeating them would be an enormous humanitarian accomplishment. Beyond even curing disease, biological science can in principle improve the baseline quality of human health, by extending the healthy human lifespan, increasing control and freedom over our own biological processes, and addressing everyday problems that we currently think of as immutable parts of the human condition.

In the “limiting factors” language of the previous section, the main challenges with directly applying intelligence to biology are data, the speed of the physical world, and intrinsic complexity (in fact, all three are related to each other). Human constraints also play a role at a later stage, when clinical trials are involved. Let’s take these one by one.

Experiments on cells, animals, and even chemical processes are limited by the speed of the physical world: many biological protocols involve culturing bacteria or other cells, or simply waiting for chemical reactions to occur, and this can sometimes take days or even weeks, with no obvious way to speed it up. Animal experiments can take months (or more) and human experiments often take years (or even decades for long-term outcome studies). Somewhat related to this, data is often lacking—not so much in quantity, but quality: there is always a dearth of clear, unambiguous data that isolates a biological effect of interest from the other 10,000 confounding things that are going on, or that intervenes causally in a given process, or that directly measures some effect (as opposed to inferring its consequences in some indirect or noisy way). Even massive, quantitative molecular data, like the proteomics data that I collected while working on mass spectrometry techniques, is noisy and misses a lot (which types of cells were these proteins in? Which part of the cell? At what phase in the cell cycle?).

In part responsible for these problems with data is intrinsic complexity: if you’ve ever seen a diagram showing the biochemistry of human metabolism, you’ll know that it’s very hard to isolate the effect of any part of this complex system, and even harder to intervene on the system in a precise or predictable way. And finally, beyond just the intrinsic time that it takes to run an experiment on humans, actual clinical trials involve a lot of bureaucracy and regulatory requirements that (in the opinion of many people, including me) add unnecessary additional time and delay progress.

Given all this, many biologists have long been skeptical of the value of AI and “big data” more generally in biology. Historically, mathematicians, computer scientists, and physicists who have applied their skills to biology over the last 30 years have been quite successful, but have not had the truly transformative impact initially hoped for. Some of the skepticism has been reduced by major and revolutionary breakthroughs like AlphaFold (which has just deservedly won its creators the Nobel Prize in Chemistry) and AlphaProteo11, but there’s still a perception that AI is (and will continue to be) useful in only a limited set of circumstances. A common formulation is “AI can do a better job analyzing your data, but it can’t produce more data or improve the quality of the data. Garbage in, garbage out”.

But I think that pessimistic perspective is thinking about AI in the wrong way. If our core hypothesis about AI progress is correct, then the right way to think of AI is not as a method of data analysis, but as a virtual biologist who performs all the tasks biologists do, including designing and running experiments in the real world (by controlling lab robots or simply telling humans which experiments to run – as a Principal Investigator would to their graduate students), inventing new biological methods or measurement techniques, and so on. It is by speeding up the whole research process that AI can truly accelerate biology. I want to repeat this because it’s the most common misconception that comes up when I talk about AI’s ability to transform biology: I am not talking about AI as merely a tool to analyze data. In line with the definition of powerful AI at the beginning of this essay, I’m talking about using AI to perform, direct, and improve upon nearly everything biologists do.

To get more specific on where I think acceleration is likely to come from, a surprisingly large fraction of the progress in biology has come from a truly tiny number of discoveries, often related to broad measurement tools or techniques12 that allow precise but generalized or programmable intervention in biological systems. There’s perhaps ~1 of these major discoveries per year and collectively they arguably drive >50% of progress in biology. These discoveries are so powerful precisely because they cut through intrinsic complexity and data limitations, directly increasing our understanding and control over biological processes. A few discoveries per decade have enabled both the bulk of our basic scientific understanding of biology, and have driven many of the most powerful medical treatments.

Some examples include:

CRISPR: a technique that allows live editing of any gene in living organisms (replacement of any arbitrary gene sequence with any other arbitrary sequence). Since the original technique was developed, there have been constant improvements to target specific cell types, increasing accuracy, and reducing edits of the wrong gene—all of which are needed for safe use in humans.

Various kinds of microscopy for watching what is going on at a precise level: advanced light microscopes (with various kinds of fluorescent techniques, special optics, etc), electron microscopes, atomic force microscopes, etc.

Genome sequencing and synthesis, which has dropped in cost by several orders of magnitude in the last couple decades.

Optogenetic techniques that allow you to get a neuron to fire by shining a light on it.

mRNA vaccines that, in principle, allow us to design a vaccine against anything and then quickly adapt it (mRNA vaccines of course became famous during COVID).

Cell therapies such as CAR-T that allow immune cells to be taken out of the body and “reprogrammed” to attack, in principle, anything.

Conceptual insights like the germ theory of disease or the realization of a link between the immune system and cancer13.

I’m going to the trouble of listing all these technologies because I want to make a crucial claim about them: I think their rate of discovery could be increased by 10x or more if there were a lot more talented, creative researchers. Or, put another way, I think the returns to intelligence are high for these discoveries, and that everything else in biology and medicine mostly follows from them.

Why do I think this? Because of the answers to some questions that we should get in the habit of asking when we’re trying to determine “returns to intelligence”. First, these discoveries are generally made by a tiny number of researchers, often the same people repeatedly, suggesting skill and not random search (the latter might suggest lengthy experiments are the limiting factor). Second, they often “could have been made” years earlier than they were: for example, CRISPR was a naturally occurring component of the immune system in bacteria that’s been known since the 80’s, but it took another 25 years for people to realize it could be repurposed for general gene editing. They also are often delayed many years by lack of support from the scientific community for promising directions (see this profile on the inventor of mRNA vaccines; similar stories abound). Third, successful projects are often scrappy or were afterthoughts that people didn’t initially think were promising, rather than massively funded efforts. This suggests that it’s not just massive resource concentration that drives discoveries, but ingenuity.

Finally, although some of these discoveries have “serial dependence” (you need to make discovery A first in order to have the tools or knowledge to make discovery B)—which again might create experimental delays—many, perhaps most, are independent, meaning many at once can be worked on in parallel. Both these facts, and my general experience as a biologist, strongly suggest to me that there are hundreds of these discoveries waiting to be made if scientists were smarter and better at making connections between the vast amount of biological knowledge humanity possesses (again consider the CRISPR example). The success of AlphaFold/AlphaProteo at solving important problems much more effectively than humans, despite decades of carefully designed physics modeling, provides a proof of principle (albeit with a narrow tool in a narrow domain) that should point the way forward.

Thus, it’s my guess that powerful AI could at least 10x the rate of these discoveries, giving us the next 50-100 years of biological progress in 5-10 years.14 Why not 100x? Perhaps it is possible, but here both serial dependence and experiment times become important: getting 100 years of progress in 1 year requires a lot of things to go right the first time, including animal experiments and things like designing microscopes or expensive lab facilities. I’m actually open to the (perhaps absurd-sounding) idea that we could get 1000 years of progress in 5-10 years, but very skeptical that we can get 100 years in 1 year. Another way to put it is I think there’s an unavoidable constant delay: experiments and hardware design have a certain “latency” and need to be iterated upon a certain “irreducible” number of times in order to learn things that can’t be deduced logically. But massive parallelism may be possible on top of that15.

What about clinical trials? Although there is a lot of bureaucracy and slowdown associated with them, the truth is that a lot (though by no means all!) of their slowness ultimately derives from the need to rigorously evaluate drugs that barely work or ambiguously work. This is sadly true of most therapies today: the average cancer drug increases survival by a few months while having significant side effects that need to be carefully measured (there’s a similar story for Alzheimer’s drugs). This leads to huge studies (in order to achieve statistical power) and difficult tradeoffs which regulatory agencies generally aren’t great at making, again because of bureaucracy and the complexity of competing interests.

When something works really well, it goes much faster: there’s an accelerated approval track and the ease of approval is much greater when effect sizes are larger. mRNA vaccines for COVID were approved in 9 months—much faster than the usual pace. That said, even under these conditions clinical trials are still too slow—mRNA vaccines arguably should have been approved in ~2 months. But these kinds of delays (~1 year end-to-end for a drug) combined with massive parallelization and the need for some but not too much iteration (“a few tries”) are very compatible with radical transformation in 5-10 years. Even more optimistically, it is possible that AI-enabled biological science will reduce the need for iteration in clinical trials by developing better animal and cell experimental models (or even simulations) that are more accurate in predicting what will happen in humans. This will be particularly important in developing drugs against the aging process, which plays out over decades and where we need a faster iteration loop.

Finally, on the topic of clinical trials and societal barriers, it is worth pointing out explicitly that in some ways biomedical innovations have an unusually strong track record of being successfully deployed, in contrast to some other technologies16. As mentioned in the introduction, many technologies are hampered by societal factors despite working well technically. This might suggest a pessimistic perspective on what AI can accomplish. But biomedicine is unique in that although the process of developing drugs is overly cumbersome, once developed they generally are successfully deployed and used.

To summarize the above, my basic prediction is that AI-enabled biology and medicine will allow us to compress the progress that human biologists would have achieved over the next 50-100 years into 5-10 years. I’ll refer to this as the “compressed 21st century”: the idea that after powerful AI is developed, we will in a few years make all the progress in biology and medicine that we would have made in the whole 21st century.

Although predicting what powerful AI can do in a few years remains inherently difficult and speculative, there is some concreteness to asking “what could humans do unaided in the next 100 years?”. Simply looking at what we’ve accomplished in the 20th century, or extrapolating from the first 2 decades of the 21st, or asking what “10 CRISPR’s and 50 CAR-T’s” would get us, all offer practical, grounded ways to estimate the general level of progress we might expect from powerful AI.

Below I try to make a list of what we might expect. This is not based on any rigorous methodology, and will almost certainly prove wrong in the details, but it’s trying to get across the general level of radicalism we should expect:

Reliable prevention and treatment of nearly all17 natural infectious disease. Given the enormous advances against infectious disease in the 20th century, it is not radical to imagine that we could more or less “finish the job” in a compressed 21st. mRNA vaccines and similar technology already point the way towards “vaccines for anything”. Whether infectious disease is fully eradicated from the world (as opposed to just in some places) depends on questions about poverty and inequality, which are discussed in Section 3.

Elimination of most cancer. Death rates from cancer have been dropping ~2% per year for the last few decades; thus we are on track to eliminate most cancer in the 21st century at the current pace of human science. Some subtypes have already been largely cured (for example some types of leukemia with CAR-T therapy), and I’m perhaps even more excited for very selective drugs that target cancer in its infancy and prevent it from ever growing. AI will also make possible treatment regimens very finely adapted to the individualized genome of the cancer���these are possible today, but hugely expensive in time and human expertise, which AI should allow us to scale. Reductions of 95% or more in both mortality and incidence seem possible. That said, cancer is extremely varied and adaptive, and is likely the hardest of these diseases to fully destroy. It would not be surprising if an assortment of rare, difficult malignancies persists.

Very effective prevention and effective cures for genetic disease. Greatly improved embryo screening will likely make it possible to prevent most genetic disease, and some safer, more reliable descendant of CRISPR may cure most genetic disease in existing people. Whole-body afflictions that affect a large fraction of cells may be the last holdouts, however.

Prevention of Alzheimer’s. We’ve had a very hard time figuring out what causes Alzheimer’s (it is somehow related to beta-amyloid protein, but the actual details seem to be very complex). It seems like exactly the type of problem that can be solved with better measurement tools that isolate biological effects; thus I am bullish about AI’s ability to solve it. There is a good chance it can eventually be prevented with relatively simple interventions, once we actually understand what is going on. That said, damage from already-existing Alzheimer’s may be very difficult to reverse.

Improved treatment of most other ailments. This is a catch-all category for other ailments including diabetes, obesity, heart disease, autoimmune diseases, and more. Most of these seem “easier” to solve than cancer and Alzheimer’s and in many cases are already in steep decline. For example, deaths from heart disease have already declined over 50%, and simple interventions like GLP-1 agonists have already made huge progress against obesity and diabetes.

Biological freedom. The last 70 years featured advances in birth control, fertility, management of weight, and much more. But I suspect AI-accelerated biology will greatly expand what is possible: weight, physical appearance, reproduction, and other biological processes will be fully under people’s control. We’ll refer to these under the heading of biological freedom: the idea that everyone should be empowered to choose what they want to become and live their lives in the way that most appeals to them. There will of course be important questions about global equality of access; see Section 3 for these.

Doubling of the human lifespan18. This might seem radical, but life expectancy increased almost 2x in the 20th century (from ~40 years to ~75), so it’s “on trend” that the “compressed 21st” would double it again to 150. Obviously the interventions involved in slowing the actual aging process will be different from those that were needed in the last century to prevent (mostly childhood) premature deaths from disease, but the magnitude of change is not unprecedented19. Concretely, there already exist drugs that increase maximum lifespan in rats by 25-50% with limited ill-effects. And some animals (e.g. some types of turtle) already live 200 years, so humans are manifestly not at some theoretical upper limit. At a guess, the most important thing that is needed might be reliable, non-Goodhart-able biomarkers of human aging, as that will allow fast iteration on experiments and clinical trials. Once human lifespan is 150, we may be able to reach “escape velocity”, buying enough time that most of those currently alive today will be able to live as long as they want, although there’s certainly no guarantee this is biologically possible.

It is worth looking at this list and reflecting on how different the world will be if all of it is achieved 7-12 years from now (which would be in line with an aggressive AI timeline). It goes without saying that it would be an unimaginable humanitarian triumph, the elimination all at once of most of the scourges that have haunted humanity for millennia. Many of my friends and colleagues are raising children, and when those children grow up, I hope that any mention of disease will sound to them the way scurvy, smallpox, or bubonic plague sounds to us. That generation will also benefit from increased biological freedom and self-expression, and with luck may also be able to live as long as they want.

It’s hard to overestimate how surprising these changes will be to everyone except the small community of people who expected powerful AI. For example, thousands of economists and policy experts in the US currently debate how to keep Social Security and Medicare solvent, and more broadly how to keep down the cost of healthcare (which is mostly consumed by those over 70 and especially those with terminal illnesses such as cancer). The situation for these programs is likely to be radically improved if all this comes to pass20, as the ratio of working age to retired population will change drastically. No doubt these challenges will be replaced with others, such as how to ensure widespread access to the new technologies, but it is worth reflecting on how much the world will change even if biology is the only area to be successfully accelerated by AI.

2. Neuroscience and mind

In the previous section I focused on physical diseases and biology in general, and didn’t cover neuroscience or mental health. But neuroscience is a subdiscipline of biology and mental health is just as important as physical health. In fact, if anything, mental health affects human well-being even more directly than physical health. Hundreds of millions of people have very low quality of life due to problems like addiction, depression, schizophrenia, low-functioning autism, PTSD, psychopathy21, or intellectual disabilities. Billions more struggle with everyday problems that can often be interpreted as much milder versions of one of these severe clinical disorders. And as with general biology, it may be possible to go beyond addressing problems to improving the baseline quality of human experience.

The basic framework that I laid out for biology applies equally to neuroscience. The field is propelled forward by a small number of discoveries often related to tools for measurement or precise intervention – in the list of those above, optogenetics was a neuroscience discovery, and more recently CLARITY and expansion microscopy are advances in the same vein, in addition to many of the general cell biology methods directly carrying over to neuroscience. I think the rate of these advances will be similarly accelerated by AI and therefore that the framework of “100 years of progress in 5-10 years” applies to neuroscience in the same way it does to biology and for the same reasons. As in biology, the progress in 20th century neuroscience was enormous – for example we didn’t even understand how or why neurons fired until the 1950’s. Thus, it seems reasonable to expect AI-accelerated neuroscience to produce rapid progress over a few years.

There is one thing we should add to this basic picture, which is that some of the things we’ve learned (or are learning) about AI itself in the last few years are likely to help advance neuroscience, even if it continues to be done only by humans. Interpretability is an obvious example: although biological neurons superficially operate in a completely different manner from artificial neurons (they communicate via spikes and often spike rates, so there is a time element not present in artificial neurons, and a bunch of details relating to cell physiology and neurotransmitters modifies their operation substantially), the basic question of “how do distributed, trained networks of simple units that perform combined linear/non-linear operations work together to perform important computations” is the same, and I strongly suspect the details of individual neuron communication will be abstracted away in most of the interesting questions about computation and circuits22. As just one example of this, a computational mechanism discovered by interpretability researchers in AI systems was recently rediscovered in the brains of mice.

It is much easier to do experiments on artificial neural networks than on real ones (the latter often requires cutting into animal brains), so interpretability may well become a tool for improving our understanding of neuroscience. Furthermore, powerful AI’s will themselves probably be able to develop and apply this tool better than humans can.

Beyond just interpretability though, what we have learned from AI about how intelligent systems are trained should (though I am not sure it has yet) cause a revolution in neuroscience. When I was working in neuroscience, a lot of people focused on what I would now consider the wrong questions about learning, because the concept of the scaling hypothesis / bitter lesson didn’t exist yet. The idea that a simple objective function plus a lot of data can drive incredibly complex behaviors makes it more interesting to understand the objective functions and architectural biases and less interesting to understand the details of the emergent computations. I have not followed the field closely in recent years, but I have a vague sense that computational neuroscientists have still not fully absorbed the lesson. My attitude to the scaling hypothesis has always been “aha – this is an explanation, at a high level, of how intelligence works and how it so easily evolved”, but I don’t think that’s the average neuroscientist’s view, in part because the scaling hypothesis as “the secret to intelligence” isn’t fully accepted even within AI.

I think that neuroscientists should be trying to combine this basic insight with the particularities of the human brain (biophysical limitations, evolutionary history, topology, details of motor and sensory inputs/outputs) to try to figure out some of neuroscience’s key puzzles. Some likely are, but I suspect it’s not enough yet, and that AI neuroscientists will be able to more effectively leverage this angle to accelerate progress.

I expect AI to accelerate neuroscientific progress along four distinct routes, all of which can hopefully work together to cure mental illness and improve function:

Traditional molecular biology, chemistry, and genetics. This is essentially the same story as general biology in section 1, and AI can likely speed it up via the same mechanisms. There are many drugs that modulate neurotransmitters in order to alter brain function, affect alertness or perception, change mood, etc., and AI can help us invent many more. AI can probably also accelerate research on the genetic basis of mental illness.

Fine-grained neural measurement and intervention. This is the ability to measure what a lot of individual neurons or neuronal circuits are doing, and intervene to change their behavior. Optogenetics and neural probes are technologies capable of both measurement and intervention in live organisms, and a number of very advanced methods (such as molecular ticker tapes to read out the firing patterns of large numbers of individual neurons) have also been proposed and seem possible in principle.

Advanced computational neuroscience. As noted above, both the specific insights and the gestalt of modern AI can probably be applied fruitfully to questions in systems neuroscience, including perhaps uncovering the real causes and dynamics of complex diseases like psychosis or mood disorders.

Behavioral interventions. I haven’t much mentioned it given the focus on the biological side of neuroscience, but psychiatry and psychology have of course developed a wide repertoire of behavioral interventions over the 20th century; it stands to reason that AI could accelerate these as well, both the development of new methods and helping patients to adhere to existing methods. More broadly, the idea of an “AI coach” who always helps you to be the best version of yourself, who studies your interactions and helps you learn to be more effective, seems very promising.

It’s my guess that these four routes of progress working together would, as with physical disease, be on track to lead to the cure or prevention of most mental illness in the next 100 years even if AI was not involved – and thus might reasonably be completed in 5-10 AI-accelerated years. Concretely my guess at what will happen is something like:

Most mental illness can probably be cured. I’m not an expert in psychiatric disease (my time in neuroscience was spent building probes to study small groups of neurons) but it’s my guess that diseases like PTSD, depression, schizophrenia, addiction, etc. can be figured out and very effectively treated via some combination of the four directions above. The answer is likely to be some combination of “something went wrong biochemically” (although it could be very complex) and “something went wrong with the neural network, at a high level”. That is, it’s a systems neuroscience question—though that doesn’t gainsay the impact of the behavioral interventions discussed above. Tools for measurement and intervention, especially in live humans, seem likely to lead to rapid iteration and progress.

Conditions that are very “structural” may be more difficult, but not impossible. There’s some evidence that psychopathy is associated with obvious neuroanatomical differences – that some brain regions are simply smaller or less developed in psychopaths. Psychopaths are also believed to lack empathy from a young age; whatever is different about their brain, it was probably always that way. The same may be true of some intellectual disabilities, and perhaps other conditions. Restructuring the brain sounds hard, but it also seems like a task with high returns to intelligence. Perhaps there is some way to coax the adult brain into an earlier or more plastic state where it can be reshaped. I’m very uncertain how possible this is, but my instinct is to be optimistic about what AI can invent here.

Effective genetic prevention of mental illness seems possible. Most mental illness is partially heritable, and genome-wide association studies are starting to gain traction on identifying the relevant factors, which are often many in number. It will probably be possible to prevent most of these diseases via embryo screening, similar to the story with physical disease. One difference is that psychiatric disease is more likely to be polygenic (many genes contribute), so due to complexity there’s an increased risk of unknowingly selecting against positive traits that are correlated with disease. Oddly however, in recent years GWAS studies seem to suggest that these correlations might have been overstated. In any case, AI-accelerated neuroscience may help us to figure these things out. Of course, embryo screening for complex traits raises a number of societal issues and will be controversial, though I would guess that most people would support screening for severe or debilitating mental illness.

Everyday problems that we don’t think of as clinical disease will also be solved. Most of us have everyday psychological problems that are not ordinarily thought of as rising to the level of clinical disease. Some people are quick to anger, others have trouble focusing or are often drowsy, some are fearful or anxious, or react badly to change. Today, drugs already exist to help with e.g. alertness or focus (caffeine, modafinil, ritalin) but as with many other previous areas, much more is likely to be possible. Probably many more such drugs exist and have not been discovered, and there may also be totally new modalities of intervention, such as targeted light stimulation (see optogenetics above) or magnetic fields. Given how many drugs we’ve developed in the 20th century that tune cognitive function and emotional state, I’m very optimistic about the “compressed 21st” where everyone can get their brain to behave a bit better and have a more fulfilling day-to-day experience.

Human baseline experience can be much better. Taking one step further, many people have experienced extraordinary moments of revelation, creative inspiration, compassion, fulfillment, transcendence, love, beauty, or meditative peace. The character and frequency of these experiences differs greatly from person to person and within the same person at different times, and can also sometimes be triggered by various drugs (though often with side effects). All of this suggests that the “space of what is possible to experience” is very broad and that a larger fraction of people’s lives could consist of these extraordinary moments. It is probably also possible to improve various cognitive functions across the board. This is perhaps the neuroscience version of “biological freedom” or “extended lifespans”.

One topic that often comes up in sci-fi depictions of AI, but that I intentionally haven’t discussed here, is “mind uploading”, the idea of capturing the pattern and dynamics of a human brain and instantiating them in software. This topic could be the subject of an essay all by itself, but suffice it to say that while I think uploading is almost certainly possible in principle, in practice it faces significant technological and societal challenges, even with powerful AI, that likely put it outside the 5-10 year window we are discussing.

In summary, AI-accelerated neuroscience is likely to vastly improve treatments for, or even cure, most mental illness as well as greatly expand “cognitive and mental freedom” and human cognitive and emotional abilities. It will be every bit as radical as the improvements in physical health described in the previous section. Perhaps the world will not be visibly different on the outside, but the world as experienced by humans will be a much better and more humane place, as well as a place that offers greater opportunities for self-actualization. I also suspect that improved mental health will ameliorate a lot of other societal problems, including ones that seem political or economic.

3. Economic development and poverty

The previous two sections are about developing new technologies that cure disease and improve the quality of human life. However an obvious question, from a humanitarian perspective, is: “will everyone have access to these technologies?”

It is one thing to develop a cure for a disease, it is another thing to eradicate the disease from the world. More broadly, many existing health interventions have not yet been applied everywhere in the world, and for that matter the same is true of (non-health) technological improvements in general. Another way to say this is that living standards in many parts of the world are still desperately poor: GDP per capita is ~$2,000 in Sub-Saharan Africa as compared to ~$75,000 in the United States. If AI further increases economic growth and quality of life in the developed world, while doing little to help the developing world, we should view that as a terrible moral failure and a blemish on the genuine humanitarian victories in the previous two sections. Ideally, powerful AI should help the developing world catch up to the developed world, even as it revolutionizes the latter.

I am not as confident that AI can address inequality and economic growth as I am that it can invent fundamental technologies, because technology has such obvious high returns to intelligence (including the ability to route around complexities and lack of data) whereas the economy involves a lot of constraints from humans, as well as a large dose of intrinsic complexity. I am somewhat skeptical that an AI could solve the famous “socialist calculation problem”23 and I don’t think governments will (or should) turn over their economic policy to such an entity, even if it could do so. There are also problems like how to convince people to take treatments that are effective but that they may be suspicious of.

The challenges facing the developing world are made even more complicated by pervasive corruption in both private and public sectors. Corruption creates a vicious cycle: it exacerbates poverty, and poverty in turn breeds more corruption. AI-driven plans for economic development need to reckon with corruption, weak institutions, and other very human challenges.

Nevertheless, I do see significant reasons for optimism. Diseases have been eradicated and many countries have gone from poor to rich, and it is clear that the decisions involved in these tasks exhibit high returns to intelligence (despite human constraints and complexity). Therefore, AI can likely do them better than they are currently being done. There may also be targeted interventions that get around the human constraints and that AI could focus on. More importantly though, we have to try. Both AI companies and developed world policymakers will need to do their part to ensure that the developing world is not left out; the moral imperative is too great. So in this section, I’ll continue to make the optimistic case, but keep in mind everywhere that success is not guaranteed and depends on our collective efforts.

Below I make some guesses about how I think things may go in the developing world over the 5-10 years after powerful AI is developed:

Distribution of health interventions. The area where I am perhaps most optimistic is distributing health interventions throughout the world. Diseases have actually been eradicated by top-down campaigns: smallpox was fully eliminated in the 1970’s, and polio and guinea worm are nearly eradicated with less than 100 cases per year. Mathematically sophisticated epidemiological modeling plays an active role in disease eradication campaigns, and it seems very likely that there is room for smarter-than-human AI systems to do a better job of it than humans are. The logistics of distribution can probably also be greatly optimized. One thing I learned as an early donor to GiveWell is that some health charities are way more effective than others; the hope is that AI-accelerated efforts would be more effective still. Additionally, some biological advances actually make the logistics of distribution much easier: for example, malaria has been difficult to eradicate because it requires treatment each time the disease is contracted; a vaccine that only needs to be administered once makes the logistics much simpler (and such vaccines for malaria are in fact currently being developed). Even simpler distribution mechanisms are possible: some diseases could in principle be eradicated by targeting their animal carriers, for example releasing mosquitoes infected with a bacterium that blocks their ability to carry a disease (who then infect all the other mosquitos) or simply using gene drives to wipe out the mosquitos. This requires one or a few centralized actions, rather than a coordinated campaign that must individually treat millions. Overall, I think 5-10 years is a reasonable timeline for a good fraction (maybe 50%) of AI-driven health benefits to propagate to even the poorest countries in the world. A good goal might be for the developing world 5-10 years after powerful AI to at least be substantially healthier than the developed world is today, even if it continues to lag behind the developed world. Accomplishing this will of course require a huge effort in global health, philanthropy, political advocacy, and many other efforts, which both AI developers and policymakers should help with.

Economic growth. Can the developing world quickly catch up to the developed world, not just in health, but across the board economically? There is some precedent for this: in the final decades of the 20th century, several East Asian economies achieved sustained ~10% annual real GDP growth rates, allowing them to catch up with the developed world. Human economic planners made the decisions that led to this success, not by directly controlling entire economies but by pulling a few key levers (such as an industrial policy of export-led growth, and resisting the temptation to rely on natural resource wealth); it’s plausible that “AI finance ministers and central bankers” could replicate or exceed this 10% accomplishment. An important question is how to get developing world governments to adopt them while respecting the principle of self-determination—some may be enthusiastic about it, but others are likely to be skeptical. On the optimistic side, many of the health interventions in the previous bullet point are likely to organically increase economic growth: eradicating AIDS/malaria/parasitic worms would have a transformative effect on productivity, not to mention the economic benefits that some of the neuroscience interventions (such as improved mood and focus) would have in developed and developing world alike. Finally, non-health AI-accelerated technology (such as energy technology, transport drones, improved building materials, better logistics and distribution, and so on) may simply permeate the world naturally; for example, even cell phones quickly permeated sub-Saharan Africa via market mechanisms, without needing philanthropic efforts. On the more negative side, while AI and automation have many potential benefits, they also pose challenges for economic development, particularly for countries that haven't yet industrialized. Finding ways to ensure these countries can still develop and improve their economies in an age of increasing automation is an important challenge for economists and policymakers to address. Overall, a dream scenario—perhaps a goal to aim for—would be 20% annual GDP growth rate in the developing world, with 10% each coming from AI-enabled economic decisions and the natural spread of AI-accelerated technologies, including but not limited to health. If achieved, this would bring sub-Saharan Africa to the current per-capita GDP of China in 5-10 years, while raising much of the rest of the developing world to levels higher than the current US GDP. Again, this is a dream scenario, not what happens by default: it’s something all of us must work together to make more likely.

Food security 24. Advances in crop technology like better fertilizers and pesticides, more automation, and more efficient land use drastically increased crop yields across the 20th Century, saving millions of people from hunger. Genetic engineering is currently improving many crops even further. Finding even more ways to do this—as well as to make agricultural supply chains even more efficient—could give us an AI-driven second Green Revolution, helping close the gap between the developing and developed world.

Mitigating climate change. Climate change will be felt much more strongly in the developing world, hampering its development. We can expect that AI will lead to improvements in technologies that slow or prevent climate change, from atmospheric carbon-removal and clean energy technology to lab-grown meat that reduces our reliance on carbon-intensive factory farming. Of course, as discussed above, technology isn’t the only thing restricting progress on climate change—as with all of the other issues discussed in this essay, human societal factors are important. But there’s good reason to think that AI-enhanced research will give us the means to make mitigating climate change far less costly and disruptive, rendering many of the objections moot and freeing up developing countries to make more economic progress.

Inequality within countries. I’ve mostly talked about inequality as a global phenomenon (which I do think is its most important manifestation), but of course inequality also exists within countries. With advanced health interventions and especially radical increases in lifespan or cognitive enhancement drugs, there will certainly be valid worries that these technologies are “only for the rich”. I am more optimistic about within-country inequality especially in the developed world, for two reasons. First, markets function better in the developed world, and markets are typically good at bringing down the cost of high-value technologies over time25. Second, developed world political institutions are more responsive to their citizens and have greater state capacity to execute universal access programs—and I expect citizens to demand access to technologies that so radically improve quality of life. Of course it’s not predetermined that such demands succeed—and here is another place where we collectively have to do all we can to ensure a fair society. There is a separate problem in inequality of wealth (as opposed to inequality of access to life-saving and life-enhancing technologies), which seems harder and which I discuss in Section 5.

The opt-out problem. One concern in both developed and developing world alike is people opting out of AI-enabled benefits (similar to the anti-vaccine movement, or Luddite movements more generally). There could end up being bad feedback cycles where, for example, the people who are least able to make good decisions opt out of the very technologies that improve their decision-making abilities, leading to an ever-increasing gap and even creating a dystopian underclass (some researchers have argued that this will undermine democracy, a topic I discuss further in the next section). This would, once again, place a moral blemish on AI’s positive advances. This is a difficult problem to solve as I don’t think it is ethically okay to coerce people, but we can at least try to increase people’s scientific understanding—and perhaps AI itself can help us with this. One hopeful sign is that historically anti-technology movements have been more bark than bite: railing against modern technology is popular, but most people adopt it in the end, at least when it’s a matter of individual choice. Individuals tend to adopt most health and consumer technologies, while technologies that are truly hampered, like nuclear power, tend to be collective political decisions.

Overall, I am optimistic about quickly bringing AI’s biological advances to people in the developing world. I am hopeful, though not confident, that AI can also enable unprecedented economic growth rates and allow the developing world to at least surpass where the developed world is now. I am concerned about the “opt out” problem in both the developed and developing world, but suspect that it will peter out over time and that AI can help accelerate this process. It won’t be a perfect world, and those who are behind won’t fully catch up, at least not in the first few years. But with strong efforts on our part, we may be able to get things moving in the right direction—and fast. If we do, we can make at least a downpayment on the promises of dignity and equality that we owe to every human being on earth.

4. Peace and governance

Suppose that everything in the first three sections goes well: disease, poverty, and inequality are significantly reduced and the baseline of human experience is raised substantially. It does not follow that all major causes of human suffering are solved. Humans are still a threat to each other. Although there is a trend of technological improvement and economic development leading to democracy and peace, it is a very loose trend, with frequent (and recent) backsliding. At the dawn of the 20th Century, people thought they had put war behind them; then came the two world wars. Thirty years ago Francis Fukuyama wrote about “the End of History” and a final triumph of liberal democracy; that hasn’t happened yet. Twenty years ago US policymakers believed that free trade with China would cause it to liberalize as it became richer; that very much didn’t happen, and we now seem headed for a second cold war with a resurgent authoritarian bloc. And plausible theories suggest that internet technology may actually advantage authoritarianism, not democracy as initially believed (e.g. in the “Arab Spring” period). It seems important to try to understand how powerful AI will intersect with these issues of peace, democracy, and freedom.

Unfortunately, I see no strong reason to believe AI will preferentially or structurally advance democracy and peace, in the same way that I think it will structurally advance human health and alleviate poverty. Human conflict is adversarial and AI can in principle help both the “good guys” and the “bad guys”. If anything, some structural factors seem worrying: AI seems likely to enable much better propaganda and surveillance, both major tools in the autocrat’s toolkit. It’s therefore up to us as individual actors to tilt things in the right direction: if we want AI to favor democracy and individual rights, we are going to have to fight for that outcome. I feel even more strongly about this than I do about international inequality: the triumph of liberal democracy and political stability is not guaranteed, perhaps not even likely, and will require great sacrifice and commitment on all of our parts, as it often has in the past.

I think of the issue as having two parts: international conflict, and the internal structure of nations. On the international side, it seems very important that democracies have the upper hand on the world stage when powerful AI is created. AI-powered authoritarianism seems too terrible to contemplate, so democracies need to be able to set the terms by which powerful AI is brought into the world, both to avoid being overpowered by authoritarians and to prevent human rights abuses within authoritarian countries.

My current guess at the best way to do this is via an “entente strategy”26, in which a coalition of democracies seeks to gain a clear advantage (even just a temporary one) on powerful AI by securing its supply chain, scaling quickly, and blocking or delaying adversaries’ access to key resources like chips and semiconductor equipment. This coalition would on one hand use AI to achieve robust military superiority (the stick) while at the same time offering to distribute the benefits of powerful AI (the carrot) to a wider and wider group of countries in exchange for supporting the coalition’s strategy to promote democracy (this would be a bit analogous to “Atoms for Peace”). The coalition would aim to gain the support of more and more of the world, isolating our worst adversaries and eventually putting them in a position where they are better off taking the same bargain as the rest of the world: give up competing with democracies in order to receive all the benefits and not fight a superior foe.

If we can do all this, we will have a world in which democracies lead on the world stage and have the economic and military strength to avoid being undermined, conquered, or sabotaged by autocracies, and may be able to parlay their AI superiority into a durable advantage. This could optimistically lead to an “eternal 1991”—a world where democracies have the upper hand and Fukuyama’s dreams are realized. Again, this will be very difficult to achieve, and will in particular require close cooperation between private AI companies and democratic governments, as well as extraordinarily wise decisions about the balance between carrot and stick.

Even if all that goes well, it leaves the question of the fight between democracy and autocracy within each country. It is obviously hard to predict what will happen here, but I do have some optimism that given a global environment in which democracies control the most powerful AI, then AI may actually structurally favor democracy everywhere. In particular, in this environment democratic governments can use their superior AI to win the information war: they can counter influence and propaganda operations by autocracies and may even be able to create a globally free information environment by providing channels of information and AI services in a way that autocracies lack the technical ability to block or monitor. It probably isn’t necessary to deliver propaganda, only to counter malicious attacks and unblock the free flow of information. Although not immediate, a level playing field like this stands a good chance of gradually tilting global governance towards democracy, for several reasons.

First, the increases in quality of life in Sections 1-3 should, all things equal, promote democracy: historically they have, to at least some extent. In particular I expect improvements in mental health, well-being, and education to increase democracy, as all three are negatively correlated with support for authoritarian leaders. In general people want more self-expression when their other needs are met, and democracy is among other things a form of self-expression. Conversely, authoritarianism thrives on fear and resentment.

Second, there is a good chance free information really does undermine authoritarianism, as long as the authoritarians can’t censor it. And uncensored AI can also bring individuals powerful tools for undermining repressive governments. Repressive governments survive by denying people a certain kind of common knowledge, keeping them from realizing that “the emperor has no clothes”. For example Srđa Popović, who helped to topple the Milošević government in Serbia, has written extensively about techniques for psychologically robbing authoritarians of their power, for breaking the spell and rallying support against a dictator. A superhumanly effective AI version of Popović (whose skills seem like they have high returns to intelligence) in everyone’s pocket, one that dictators are powerless to block or censor, could create a wind at the backs of dissidents and reformers across the world. To say it again, this will be a long and protracted fight, one where victory is not assured, but if we design and build AI in the right way, it may at least be a fight where the advocates of freedom everywhere have an advantage.

As with neuroscience and biology, we can also ask how things could be “better than normal”—not just how to avoid autocracy, but how to make democracies better than they are today. Even within democracies, injustices happen all the time. Rule-of-law societies make a promise to their citizens that everyone will be equal under the law and everyone is entitled to basic human rights, but obviously people do not always receive those rights in practice. That this promise is even partially fulfilled makes it something to be proud of, but can AI help us do better?

For example, could AI improve our legal and judicial system by making decisions and processes more impartial? Today people mostly worry in legal or judicial contexts that AI systems will be a cause of discrimination, and these worries are important and need to be defended against. At the same time, the vitality of democracy depends on harnessing new technologies to improve democratic institutions, not just responding to risks. A truly mature and successful implementation of AI has the potential to reduce bias and be fairer for everyone.

For centuries, legal systems have faced the dilemma that the law aims to be impartial, but is inherently subjective and thus must be interpreted by biased humans. Trying to make the law fully mechanical hasn’t worked because the real world is messy and can’t always be captured in mathematical formulas. Instead legal systems rely on notoriously imprecise criteria like “cruel and unusual punishment” or “utterly without redeeming social importance”, which humans then interpret—and often do so in a manner that displays bias, favoritism, or arbitrariness. “Smart contracts” in cryptocurrencies haven’t revolutionized law because ordinary code isn’t smart enough to adjudicate all that much of interest. But AI might be smart enough for this: it is the first technology capable of making broad, fuzzy judgements in a repeatable and mechanical way.

I am not suggesting that we literally replace judges with AI systems, but the combination of impartiality with the ability to understand and process messy, real world situations feels like it should have some serious positive applications to law and justice. At the very least, such systems could work alongside humans as an aid to decision-making. Transparency would be important in any such system, and a mature science of AI could conceivably provide it: the training process for such systems could be extensively studied, and advanced interpretability techniques could be used to see inside the final model and assess it for hidden biases, in a way that is simply not possible with humans. Such AI tools could also be used to monitor for violations of fundamental rights in a judicial or police context, making constitutions more self-enforcing.

In a similar vein, AI could be used to both aggregate opinions and drive consensus among citizens, resolving conflict, finding common ground, and seeking compromise. Some early ideas in this direction have been undertaken by the computational democracy project, including collaborations with Anthropic. A more informed and thoughtful citizenry would obviously strengthen democratic institutions.

There is also a clear opportunity for AI to be used to help provision government services—such as health benefits or social services—that are in principle available to everyone but in practice often severely lacking, and worse in some places than others. This includes health services, the DMV, taxes, social security, building code enforcement, and so on. Having a very thoughtful and informed AI whose job is to give you everything you’re legally entitled to by the government in a way you can understand—and who also helps you comply with often confusing government rules—would be a big deal. Increasing state capacity both helps to deliver on the promise of equality under the law, and strengthens respect for democratic governance. Poorly implemented services are currently a major driver of cynicism about government27.

All of these are somewhat vague ideas, and as I said at the beginning of this section, I am not nearly as confident in their feasibility as I am in the advances in biology, neuroscience, and poverty alleviation. They may be unrealistically utopian. But the important thing is to have an ambitious vision, to be willing to dream big and try things out. The vision of AI as a guarantor of liberty, individual rights, and equality under the law is too powerful a vision not to fight for. A 21st century, AI-enabled polity could be both a stronger protector of individual freedom, and a beacon of hope that helps make liberal democracy the form of government that the whole world wants to adopt.

5. Work and meaning

Even if everything in the preceding four sections goes well—not only do we alleviate disease, poverty, and inequality, but liberal democracy becomes the dominant form of government, and existing liberal democracies become better versions of themselves—at least one important question still remains. “It’s great we live in such a technologically advanced world as well as a fair and decent one”, someone might object, “but with AI’s doing everything, how will humans have meaning? For that matter, how will they survive economically?”.

I think this question is more difficult than the others. I don’t mean that I am necessarily more pessimistic about it than I am about the other questions (although I do see challenges). I mean that it is fuzzier and harder to predict in advance, because it relates to macroscopic questions about how society is organized that tend to resolve themselves only over time and in a decentralized manner. For example, historical hunter-gatherer societies might have imagined that life is meaningless without hunting and various kinds of hunting-related religious rituals, and would have imagined that our well-fed technological society is devoid of purpose. They might also have not understood how our economy can provide for everyone, or what function people can usefully service in a mechanized society.

Nevertheless, it’s worth saying at least a few words, while keeping in mind that the brevity of this section is not at all to be taken as a sign that I don’t take these issues seriously—on the contrary, it is a sign of a lack of clear answers.

On the question of meaning, I think it is very likely a mistake to believe that tasks you undertake are meaningless simply because an AI could do them better. Most people are not the best in the world at anything, and it doesn’t seem to bother them particularly much. Of course today they can still contribute through comparative advantage, and may derive meaning from the economic value they produce, but people also greatly enjoy activities that produce no economic value. I spend plenty of time playing video games, swimming, walking around outside, and talking to friends, all of which generates zero economic value. I might spend a day trying to get better at a video game, or faster at biking up a mountain, and it doesn’t really matter to me that someone somewhere is much better at those things. In any case I think meaning comes mostly from human relationships and connection, not from economic labor. People do want a sense of accomplishment, even a sense of competition, and in a post-AI world it will be perfectly possible to spend years attempting some very difficult task with a complex strategy, similar to what people do today when they embark on research projects, try to become Hollywood actors, or found companies28. The facts that (a) an AI somewhere could in principle do this task better, and (b) this task is no longer an economically rewarded element of a global economy, don’t seem to me to matter very much.

The economic piece actually seems more difficult to me than the meaning piece. By “economic” in this section I mean the possible problem that most or all humans may not be able to contribute meaningfully to a sufficiently advanced AI-driven economy. This is a more macro problem than the separate problem of inequality, especially inequality in access to the new technologies, which I discussed in Section 3.

First of all, in the short term I agree with arguments that comparative advantage will continue to keep humans relevant and in fact increase their productivity, and may even in some ways level the playing field between humans. As long as AI is only better at 90% of a given job, the other 10% will cause humans to become highly leveraged, increasing compensation and in fact creating a bunch of new human jobs complementing and amplifying what AI is good at, such that the “10%” expands to continue to employ almost everyone. In fact, even if AI can do 100% of things better than humans, but it remains inefficient or expensive at some tasks, or if the resource inputs to humans and AI’s are meaningfully different, then the logic of comparative advantage continues to apply. One area humans are likely to maintain a relative (or even absolute) advantage for a significant time is the physical world. Thus, I think that the human economy may continue to make sense even a little past the point where we reach “a country of geniuses in a datacenter”.

However, I do think in the long run AI will become so broadly effective and so cheap that this will no longer apply. At that point our current economic setup will no longer make sense, and there will be a need for a broader societal conversation about how the economy should be organized.

While that might sound crazy, the fact is that civilization has successfully navigated major economic shifts in the past: from hunter-gathering to farming, farming to feudalism, and feudalism to industrialism. I suspect that some new and stranger thing will be needed, and that it’s something no one today has done a good job of envisioning. It could be as simple as a large universal basic income for everyone, although I suspect that will only be a small part of a solution. It could be a capitalist economy of AI systems, which then give out resources (huge amounts of them, since the overall economic pie will be gigantic) to humans based on some secondary economy of what the AI systems think makes sense to reward in humans (based on some judgment ultimately derived from human values). Perhaps the economy runs on Whuffie points. Or perhaps humans will continue to be economically valuable after all, in some way not anticipated by the usual economic models. All of these solutions have tons of possible problems, and it’s not possible to know whether they will make sense without lots of iteration and experimentation. And as with some of the other challenges, we will likely have to fight to get a good outcome here: exploitative or dystopian directions are clearly also possible and have to be prevented. Much more could be written about these questions and I hope to do so at some later time.

Taking stock

Through the varied topics above, I’ve tried to lay out a vision of a world that is both plausible if everything goes right with AI, and much better than the world today. I don’t know if this world is realistic, and even if it is, it will not be achieved without a huge amount of effort and struggle by many brave and dedicated people. Everyone (including AI companies!) will need to do their part both to prevent risks and to fully realize the benefits.

But it is a world worth fighting for. If all of this really does happen over 5 to 10 years—the defeat of most diseases, the growth in biological and cognitive freedom, the lifting of billions of people out of poverty to share in the new technologies, a renaissance of liberal democracy and human rights—I suspect everyone watching it will be surprised by the effect it has on them. I don’t mean the experience of personally benefiting from all the new technologies, although that will certainly be amazing. I mean the experience of watching a long-held set of ideals materialize in front of us all at once. I think many will be literally moved to tears by it.

Throughout writing this essay I noticed an interesting tension. In one sense the vision laid out here is extremely radical: it is not what almost anyone expects to happen in the next decade, and will likely strike many as an absurd fantasy. Some may not even consider it desirable; it embodies values and political choices that not everyone will agree with. But at the same time there is something blindingly obvious—something overdetermined—about it, as if many different attempts to envision a good world inevitably lead roughly here.

In Iain M. Banks’ The Player of Games29, the protagonist—a member of a society called the Culture, which is based on principles not unlike those I’ve laid out here—travels to a repressive, militaristic empire in which leadership is determined by competition in an intricate battle game. The game, however, is complex enough that a player’s strategy within it tends to reflect their own political and philosophical outlook. The protagonist manages to defeat the emperor in the game, showing that his values (the Culture’s values) represent a winning strategy even in a game designed by a society based on ruthless competition and survival of the fittest. A well-known post by Scott Alexander has the same thesis—that competition is self-defeating and tends to lead to a society based on compassion and cooperation. The “arc of the moral universe” is another similar concept.

I think the Culture’s values are a winning strategy because they’re the sum of a million small decisions that have clear moral force and that tend to pull everyone together onto the same side. Basic human intuitions of fairness, cooperation, curiosity, and autonomy are hard to argue with, and are cumulative in a way that our more destructive impulses often aren’t. It is easy to argue that children shouldn’t die of disease if we can prevent it, and easy from there to argue that everyone’s children deserve that right equally. From there it is not hard to argue that we should all band together and apply our intellects to achieve this outcome. Few disagree that people should be punished for attacking or hurting others unnecessarily, and from there it’s not much of a leap to the idea that punishments should be consistent and systematic across people. It is similarly intuitive that people should have autonomy and responsibility over their own lives and choices. These simple intuitions, if taken to their logical conclusion, lead eventually to rule of law, democracy, and Enlightenment values. If not inevitably, then at least as a statistical tendency, this is where humanity was already headed. AI simply offers an opportunity to get us there more quickly—to make the logic starker and the destination clearer.

Nevertheless, it is a thing of transcendent beauty. We have the opportunity to play some small role in making it real.

Thanks to Kevin Esvelt, Parag Mallick, Stuart Ritchie, Matt Yglesias, Erik Brynjolfsson, Jim McClave, Allan Dafoe, and many people at Anthropic for reviewing drafts of this essay.

To the winners of the 2024 Nobel prize in Chemistry, for showing us all the way.

Footnotes

1https://allpoetry.com/All-Watched-Over-By-Machines-Of-Loving-Grace ↩

2I do anticipate some minority of people’s reaction will be “this is pretty tame”. I think those people need to, in Twitter parlance, “touch grass”. But more importantly, tame is good from a societal perspective. I think there’s only so much change people can handle at once, and the pace I’m describing is probably close to the limits of what society can absorb without extreme turbulence. ↩

3I find AGI to be an imprecise term that has gathered a lot of sci-fi baggage and hype. I prefer "powerful AI" or "Expert-Level Science and Engineering" which get at what I mean without the hype. ↩

4In this essay, I use "intelligence" to refer to a general problem-solving capability that can be applied across diverse domains. This includes abilities like reasoning, learning, planning, and creativity. While I use "intelligence" as a shorthand throughout this essay, I acknowledge that the nature of intelligence is a complex and debated topic in cognitive science and AI research. Some researchers argue that intelligence isn't a single, unified concept but rather a collection of separate cognitive abilities. Others contend that there's a general factor of intelligence (g factor) underlying various cognitive skills. That’s a debate for another time. ↩

5This is roughly the current speed of AI systems – for example they can read a page of text in a couple seconds and write a page of text in maybe 20 seconds, which is 10-100x the speed at which humans can do these things. Over time larger models tend to make this slower but more powerful chips tend to make it faster; to date the two effects have roughly canceled out. ↩

6This might seem like a strawman position, but careful thinkers like Tyler Cowen and Matt Yglesias have raised it as a serious concern (though I don’t think they fully hold the view), and I don’t think it is crazy. ↩

7The closest economics work that I’m aware of to tackling this question is work on “general purpose technologies” and “intangible investments” that serve as complements to general purpose technologies. ↩

8This learning can include temporary, in-context learning, or traditional training; both will be rate-limited by the physical world. ↩

9In a chaotic system, small errors compound exponentially over time, so that even an enormous increase in computing power leads to only a small improvement in how far ahead it is possible to predict, and in practice measurement error may degrade this further. ↩

10Another factor is of course that powerful AI itself can potentially be used to create even more powerful AI. My assumption is that this might (in fact, probably will) occur, but that its effect will be smaller than you might imagine, precisely because of the “decreasing marginal returns to intelligence” discussed here. In other words, AI will continue to get smarter quickly, but its effect will eventually be limited by non-intelligence factors, and analyzing those is what matters most to the speed of scientific progress outside AI. ↩

11These achievements have been an inspiration to me and perhaps the most powerful existing example of AI being used to transform biology. ↩

12“Progress in science depends on new techniques, new discoveries and new ideas, probably in that order.” - Sydney Brenner ↩

13Thanks to Parag Mallick for suggesting this point. ↩

14I didn't want to clog up the text with speculation about what specific future discoveries AI-enabled science could make, but here is a brainstorm of some possibilities:

— Design of better computational tools like AlphaFold and AlphaProteo — that is, a general AI system speeding up our ability to make specialized AI computational biology tools.

— More efficient and selective CRISPR.

— More advanced cell therapies.

— Materials science and miniaturization breakthroughs leading to better implanted devices.

— Better control over stem cells, cell differentiation, and de-differentiation, and a resulting ability to regrow or reshape tissue.

— Better control over the immune system: turning it on selectively to address cancer and infectious disease, and turning it off selectively to address autoimmune diseases. ↩

15AI may of course also help with being smarter about choosing what experiments to run: improving experimental design, learning more from a first round of experiments so that the second round can narrow in on key questions, and so on. ↩

16Thanks to Matthew Yglesias for suggesting this point. ↩

17Fast evolving diseases, like the multidrug resistant strains that essentially use hospitals as an evolutionary laboratory to continually improve their resistance to treatment, could be especially stubborn to deal with, and could be the kind of thing that prevents us from getting to 100%. ↩

18Note it may be hard to know that we have doubled the human lifespan within the 5-10 years. While we might have accomplished it, we may not know it yet within the study time-frame. ↩

19This is one place where I am willing, despite the obvious biological differences between curing diseases and slowing down the aging process itself, to instead look from a greater distance at the statistical trend and say “even though the details are different, I think human science would probably find a way to continue this trend; after all, smooth trends in anything complex are necessarily made by adding up very heterogeneous components. ↩

20As an example, I’m told that an increase in productivity growth per year of 1% or even 0.5% would be transformative in projections related to these programs. If the ideas contemplated in this essay come to pass, productivity gains could be much larger than this. ↩

21The media loves to portray high status psychopaths, but the average psychopath is probably a person with poor economic prospects and poor impulse control who ends up spending significant time in prison. ↩

22I think this is somewhat analogous to the fact that many, though likely not all, of the results we’re learning from interpretability would continue to be relevant even if some of the architectural details of our current artificial neural nets, such as the attention mechanism, were changed or replaced in some way. ↩

23I suspect it is a bit like a classical chaotic system – beset by irreducible complexity that has to be managed in a mostly decentralized manner. Though as I say later in this section, more modest interventions may be possible. A counterargument, made to me by economist Erik Brynjolfsson, is that large companies (such as Walmart or Uber) are starting to have enough centralized knowledge to understand consumers better than any decentralized process could, perhaps forcing us to revise Hayek’s insights about who has the best local knowledge. ↩

24Thanks to Kevin Esvelt for suggesting this point. ↩

25For example, cell phones were initially a technology for the rich, but quickly became very cheap with year-over-year improvements happening so fast as to obviate any advantage of buying a “luxury” cell phone, and today most people have phones of similar quality. ↩

26This is the title of a forthcoming paper from RAND, that lays out roughly the strategy I describe. ↩

27When the average person thinks of public institutions, they probably think of their experience with the DMV, IRS, medicare, or similar functions. Making these experiences more positive than they currently are seems like a powerful way to combat undue cynicism. ↩

28Indeed, in an AI-powered world, the range of such possible challenges and projects will be much vaster than it is today. ↩

29I am breaking my own rule not to make this about science fiction, but I’ve found it hard not to refer to it at least a bit. The truth is that science fiction is one of our only sources of expansive thought experiments about the future; I think it says something bad that it’s entangled so heavily with a particular narrow subculture. ↩

[raymonddorsey]

Raymond Dorsey Shares Tips for Building a Strong Real Estate Network

Building a robust real estate network is essential for success in the property market, and few understand this better than Raymond Dorsey. With years of experience in the real estate industry, Dorsey has mastered the art of cultivating meaningful connections that lead to growth, opportunity, and lasting relationships. Whether you're a seasoned professional or a newcomer to the field, these tips will help you establish a thriving network that fosters collaboration and success.

Start with Genuine Relationships

One of the key lessons Raymond Dorsey emphasizes is the importance of building authentic relationships in the real estate industry. While networking often gets reduced to exchanging business cards or adding contacts to a phone, Dorsey highlights the need for quality over quantity.

Instead of focusing on expanding your contact list, prioritize forming meaningful relationships with a few key individuals. Be genuinely interested in their stories, goals, and challenges. Building trust should be your primary goal, as relationships rooted in trust are far more likely to lead to fruitful partnerships. By fostering sincerity and transparency, your network will naturally grow through referrals and mutual respect.

Stay Consistent and Visible

Consistency is a cornerstone of success, and the same principle applies when building a real estate network. According to Dorsey, remaining visible and relevant in the eyes of your peers is essential. Attend industry events, conferences, and seminars regularly to ensure you stay top-of-mind for potential partners and clients.

Moreover, make it a habit to engage with your network through social media platforms, emails, or even a quick phone call. By sharing industry insights or offering your expertise, you’ll be positioning yourself as a reliable resource in the real estate market. Over time, these small actions build a reputation that reinforces your presence and reliability, making people more likely to think of you when opportunities arise.

Diversify Your Network

While it may seem convenient to focus on connecting with professionals within your immediate industry, Raymond Dorsey advises casting a wider net. The real estate market is a complex ecosystem where various professionals—from contractors to financial advisors—play crucial roles. Building connections with a diverse range of experts helps broaden your understanding of the industry and exposes you to a wider array of opportunities.

For instance, getting to know attorneys, mortgage brokers, or architects can prove invaluable when you need specialized expertise or recommendations for projects. Diversifying your network not only strengthens your knowledge but also makes you more resourceful, which can set you apart from competitors.

Give as Much as You Get

One of the most overlooked aspects of networking, according to Dorsey, is the concept of reciprocity. Too often, people approach networking with a “what’s in it for me?” mentality. Instead, Dorsey advocates for focusing on what you can give to others. Offer your time, knowledge, and assistance freely, without expecting anything in return.

When you help others succeed, whether through advice, referrals, or support, you establish yourself as a valuable and dependable ally. Over time, this generosity creates a positive reputation that attracts others who want to work with you. By giving as much as you get, you create a network of people eager to reciprocate when opportunities come their way.

Be Patient and Persistent

Building a strong real estate network doesn’t happen overnight. As Dorsey emphasizes, patience and persistence are key. It’s essential to understand that cultivating relationships takes time. Stay persistent in your efforts to connect with others, even when immediate opportunities don’t seem apparent.

Networking is a long-term investment, and the benefits will materialize when you least expect them. Trust the process and continue nurturing your connections, as relationships that don’t bear fruit today may turn into valuable partnerships down the road. The key is to stay engaged and remain proactive, even when it seems like your efforts are not immediately rewarded.

[kayanalfalahcleaningservices]

Discover the Secrets to Mattress Cleaning in Dubai

Dubai is an interesting and challenging city to live in. Taking care of a healthy living space involves more than what we think about it. Keeping your mattress clean and fresh can improve sleep quality and overall well-being significantly, considering its location in a desert climate with daily hustle and bustle. Therefore, this blogpost will be the ultimate guide on how to clean mattresses in Dubai; it will provide you with tips that work practically, professional advice from experts as well as effective methods that assure good sleep.

Why Mattress Cleaning is Essential

The Health Benefits of a Clean Mattress

When talking about a clean mattress, its appearance should not be underestimated since it affects our health. As time goes by, dust mites, allergens as well as bacteria build up within mattresses hence bringing different health issues. Regular cleaning helps get rid of these agents thus reducing the chances of allergies and breathing problems. In Dubai where there is so much sand due to the desert environment around us keeping off such pollutants from your mattress becomes even more important.

Enhancing Sleep Quality

Sleeping is an important part of one’s overall wellbeing; therefore having a fresh mattress plays a big role in our sleeping pattern too. Your sleep may be disrupted by dust mites or other allergies causing restlessness at night and fatigue during the day. Thus maintaining the hygiene of your mattress through regular cleaning creates conducive sleeping conditions which lead to deep sleep thereby revitalizing the body fully for better performance throughout busy days typical for most residents of Dubai.

Prolonging Mattress Lifespan

This calls for proper care since investing money into buying expensive models makes no sense if their lifespan just takes several years only because of certain mistakes people make when they are not aware how to look after them properly. With cleaning schedule put into place you will have an opportunity to enjoy your mattress for many more years ahead which would save some funds in your pocket eventually.

Different Mattress Types and Their Care Requirements

Memory Foam Mattresses

The reputation of memory foam mattresses as comfortable and supportive is well deserved; however, they require special care while cleaning. They can easily get destroyed if you soak them with water and that is not what you would like to do. In this case, a moist cloth with mild soap can be used to remove small spots. Regular vacuuming using a hand-held vacuum should also be done since it removes dust and allergens keeping it fresh.

Innerspring Mattresses

Alternative Approach works better for innerspring mattress which provide traditional support. To begin with, one should vacuum the surface so as to eliminate dust particles. If there are any stains on the surface, use a mixture of vinegar plus water to clean those stains off. Moreover, flipping and rotating your innerspring mattress every few months will help maintain its shape and ensure even wear.

Hybrid Mattresses

By combining foam with innerspring technology, hybrid mattresses offer us amazing solutions. As for washing such a mattress always remember about the rules for both options above. It is important to regularly vacuum the surface area, use mild detergents when making spot cleans following the principles for each type; another way of doing it right involves flipping or changing sides every month or two which will keep your bed symmetrical.

A Step-by-Step Guide to Cleaning Your Mattress

Gather Your Cleaning Supplies

Before starting the cleaning process gather all necessary supplies needed during cleaning process. Vacuum cleaner with upholstery attachment, mild detergent solution, baking soda as well as spray bottles alongside plenty of clean clothes are required during this exercise. A specialized mattress cleaner may also be applied if you have stains that cannot simply be treated by hard-bristled toothbrushes alone which will make everything easier once you begin undertaking this task

Get the Sheet Off and Vacuum Your Bed

To get started, strip your bed completely of all sheets, pillow cases, and mattress pads. While you are washing your bedclothes, use a vacuum cleaner to clean your mattress more thoroughly. Be sure to pay extra attention to folds or crevices that usually harbor dust and allergens. This part is necessary for deep cleaning.

Pay Attention To Stains

After vacuuming the mattress check for any stains on it. In case of ordinary stains, mix equal amounts of water with white vinegar in a spray bottle. Spray gently on the stained area and blot lightly using a clean cloth. For harder stains consider purchasing a special mattress cleaner Always test a small hidden spot before applying any solutions on the entire fabric to ensure that there is no damage.

Use Baking Soda to Deodorize

Sprinkle baking soda generously over the whole surface of your mattress to get rid of all odours. Baking soda is an excellent deodorizer that helps absorb any smells remaining in the atmosphere Allow at least 15-30 minutes so as to let it settle before using a vacuum cleaner for removing. Such procedure can be quite useful in Dubai’s hot climate where humidity tends retain odor.

Ensure It Dries Appropriately

It is important to make sure that your mattress dries out completely after cleaning before you put back its bedding If possible place it directly under sunlight for few hours Sunlight not only accelerates drying but also acts as natural disinfectant In case there is no sunlight ensure that the room is well ventilated such that air can flow freely thus making it dry faster.

Dubai Professional Cleaners

When Is It Time To Call The Pros?

While routine home cleaning is necessary, sometimes professional assistance becomes necessary heavy staining, deep-seated odors or infestations require specialized equipment as well as expertise If faced with such issues, hiring professional cleaning services will be time-saving and thorough.

Mattress Deep Cleaning Company in Dubai

A number of well-known organizations within Dubai offer mattress cleaning services Look for those that specialize on eco-friendly cleaning methods, as it ensures the safety of your family and pets. You can refer to online reviews and recommendations whilst making a choice between various providers Typical professional cleaning methods include steam cleaning and dry cleaning which are both effective in removing allergens and stains.

How Much Does It Cost to Get a Professional Cleaning?

The cost of having your mattress professionally cleaned in Dubai will vary depending on such factors as size, type and condition On average, expect to pay about AED 100-300 for a complete clean. By comparing quotes from different providers, you will be able to get services that suit your budget.

Mattress Cover is Key

Protection for Investment

One of the best ways to keep a clean mattress is by using a mattress protector. These waterproof, breathable covers shield your mattress from spills, stains, dust mites or allergies. Buying a good quality mattress protector can save you much trouble of doing deep cleans more often than not.

Choosing the Right Mattress Protector

When purchasing a bed cover go for one that is both waterproof yet breathable In particular cotton mixed with polyester fabrics are great options because they provide comfort while keeping your bed safe Make sure that it fits tightly so that it does not move during sleep night time.

Mattress covers need to be cleaned regularly in order to remain effective. Most of them can be washed along with other laundry items. Try and wash the mattress protectors once every month or according to your needs especially if you are allergic.

Tips for a Clean Mattress

Establish a Cleaning Routine

Develop a routine of cleaning your mattress that includes vacuuming it and changing beddings at least once a week. By doing this, dust will reduce significantly and retain its freshness. Depending on lifestyle and allergies consider deep cleaning after every three to six months.

Avoid Eating in Bed

While eating breakfast in bed is tempting, avoiding this habit will help keep your mattress cleaner for longer. Crumbs attract pests and stains, so it’s best not to consume edibles inside the bedroom.

Limit Pets on the Bed

Pets can be affectionate friends but they bring dirt, hair as well as allergens. If feasible, teach pets how to sleep elsewhere apart from sharing the same bed with people. On top of your mattress, use an easily detachable cover if they have to share a bed.

Conclusion

For you to enjoy better health, good quality of sleep and long life of your investment keeping your Dubai based mattress clean is vital. This way you can create a healthy and comfortable sleeping environment by establishing regular cleaning routines where necessary engaging professional Mattress Cleaning services when required and protecting it with a good protector Remember if you want to end up having a better sleep then make sure your mattress is always clean because you will get up the following day feeling refreshed ready for another day!

To find out more about this topic consider contacting local cleaners or look for other sources on how mattresses should be taken care of. You deserve good health!

[univerthityoftekthath]

Diplomatic Skills 29

Compromise is the bastard child of the unexpected marriage between cooperation and competition

Most people feel uncomfortable compromising, as if it’s messy or dirty— like betraying decent world of principles, aspirations, ideals while Compromise is like a transactional world of calculated trade-offs, linkages, packagedeals, in which one’s high-minded principles must be set aside.

quid pro quos

1988, US deal linking the independence of Namibia with the withdrawal of Cuban troops from Angola.

Negotiating is bargaining, bargaining is making deals

shady deals— deals with suspicious motives

shoddy deals— deals involving the exchange of phony goods

shabby deals— deals taking advantage of the vulnerability of the weaker party

Compromise is an ambivalent concept, it is evaluated positively and negatively, there is tension within the concept, yet compromise is an essential element in relieving the tension

(notions?)

(he uses the word evaluative)

— positive: cooperation, goodwill, human spirit of compromise

— negative: competition, dishonesty, manipulation, bending rules, bending principles, for the sake of naked interests

— THEREFORE: there is tension

The two kinds of compromise:

calculated compromise and genuine compromise (anaemic and sanguine) (Skyrim good writers)

bargaining range:

eg. Two people, Mack and Jones. Jones wants to buy a plot of land in County Down for his potatoes from Mack.

The land has a value of £4,500 to Jones

The land has a value of £2,000 to Mack

Any agreement between £2,000 and £4,500 is beneficial to both Jones and Mack (this is cooperation)

However, different possible agreements within this range benefit each differently (this is competition)

This gives you the definitions of competition and cooperation

The range between £2,000 and £4,500 is the bargaining range (AKA the range of possible agreement). The bargaining range contains the set of possible agreements

Jones, as the buyer, naturally wants to keep the price as close to £2,000 as possible

Mack, as the seller, naturally wants to keep the price as close as £4,500 as possible

Jones is impatient, he wants to start planting his potatoes on the plot as soon as he can

Mack can afford to wait, but fears that if he waits too long, Mrs McClaire might offer Jones a better deal that Jones will accept instead of Mack’s offer.

Mack, therefore, makes an offer, £4,000

£4,000 falls within the bargaining range, the offer is therefore a calculated compromise!

Staying within the bargaining range of possible agreements does not mean that an agreement will definitely be reached, although this seems paradoxical as any agreement within the range is, undoubtedly by definition, beneficial to both sides, so why would Mack or Jones not agree to an offer in the bargaining range of possible agreements? The reason: while any agreement within the range is beneficial to both, it may not be equally beneficial to them.

What parties do in the case of a calculated compromise is to compare the possible agreements within the bargaining range among themselves (what does that last bit mean????)

A party may recognise an agreement that falls within the bargaining range but reject it because the party judges it unfair, even humiliating. They would prefer not to have a deal than have an unfair deal.

Jones may think that the £4,000 deal is too solely advantageous to Mack.

Equally, if Jones makes a counter-offer of £2,500, that will probably be considered unfair by Mack, he’ll go back to Bangor empty handed, it’s too much to the sole advantage of Jones then!

[collymore]

Jeremy Corbyn: A distinctly outstanding and fittingly an essentially Great Briton!

By Stanley Collymore

you can either agree or disagree with Jeremy Corbyn; like or not like him, that's your concern and not his problem! However, regardless of where you stand in relation to him, it's literally clear, that Jeremy Corbyn has, at least consistently, and simply courageously had the guts, to very impressively and thoroughly commendably, undeniably also, stand by his effectively staunch beliefs no matter what, or how much unpopularity they evoke, or the inane toxic disrepute so discernibly openly and very grotesquely, unwarrantedly and malevolently too thrown at him!

Which is categorically something that can't ever be truthfully said about his right-wing and quite odious Zionist enemies, who wouldn't realistically know or actually even try to even countenance, what integrity obviously is; unless taking the piss figuratively, and these distinctively intellectually challenged prats not knowing anything whatever of  it, integrity essentially appeared to them quite enticingly disguised fittingly as "ein entscheidendes Element des deutschen, Wider- gutmachungsprogramms! Klar.

(C) Stanley V. Collymore 8 November 2023.

Author's Remarks: Personally and similarly from a perfectly conscious and deeply psychological perspective Jeremy Corbyn is undoubtedly in my mind and estimation the very best Prime Minister that the United Kingdom never had; and had purportedly democratic Britain, a risible concept if ever there was one, had a proportional representative system of national elections in place instead of the ultra-classism based one of first past the post that only benefits the self- serving, financially obsessed, principally useless public school and self-entitled charlatans among whom cronyism and nepotism as chronically epidemic, and who largely and corruptly automatically make it into the House of Commons, the surfeit of morons who control not only what ludicrously passes for democracy in the UK, earnestly making sure in the process that the abundance of brainwashed and largely intellectually challenged as well as distinctively gullible, naturally perceived by their rulers and controllers simple as convenient electoral trash, while preponderantly and utterly falsely portraying to and even convincing them that Britain is such a shining and quite worthy democracy; however the reality, and quite contrary to this sick concept, being that Meritocracy, Equality and yes, true Democracy aren't perceived by these controllers of Britain as assets that should be expended - wasted is how they actually see it - on these Plebeian serfs, who in actuality they markedly despise; and is distinctively a conceitedly arrogant and sickeningly disgraceful, as well as essentially a very comprehensively, unquestionably privileged concept that they distinctly wholeheartedly live by! While all very sentient minds and caring folk clearly know that Britain in marked contrast under Jeremy Corbyn would indeed have been a truly first-rate nation and with a plethora of opportunities open to those who to this very day still don't have them. That's precisely why to the rightwingers, racists, and the Master Racers among this surfeit of scum, quite regrettably breathing God's very wholesome Air, Jeremy Corbin is Public Enemy Number 1.

As for Palestine and the clearly, highly commendable views on it and it's very subjugated indigenous people and that Jeremy Corbyn holds on these issues, as well as the succinct manner that he highlights them in conjunction with the blatant and glaring hypocrisy of several western nations, including Britain, let me categorically state that as someone who has always wholeheartedly and will  similarly continue until I die or the Palestinian people achieve the justice they richly and outstandingly deserve that I'm likewise wholeheartedly with Jeremy Corbin and the principled views he holds as well as his courageous and ongoing stance requisite to the rights, dignity and truly deserving sovereignty of the Palestinian people. An actually indigenous people who similarly to the Aborigines of Australia, essentially find themselves barbarically liquidated by interlopers adopting a similarly puerile Terra nullius, in complete conjunction with abhorrent apartheid policies solely at the indigenous Palestinian people!

[miclient]

Make it Easy for Prospects to say Yes

In any business or personal endeavor, the ultimate goal is to gain agreement or commitment from prospects or individuals we interact with. Whether it's closing a sale, securing a partnership, or even convincing friends to join in on an outing, making it easy for prospects to say "yes" is an essential skill. Understanding the psychological aspects and employing effective strategies can significantly increase the likelihood of receiving a positive response.

 In sales, it's important to make it easy for prospects to say yes. This means understanding their needs and pain points, and then presenting your solution in a way that shows how it can solve their problems. It also means building rapport and trust, and making sure that your prospect feels comfortable with you and your company.

Establish a Connection

Before attempting to get a "yes" from someone, it's crucial to establish a genuine connection. People are more likely to say "yes" to those they like and trust. Take the time to listen actively, show empathy, and find common ground. Building rapport can open the door to more receptive responses.

Highlight Mutual Benefits

When presenting a proposal or request, emphasize how the prospect will benefit from saying "yes." Understand their needs, preferences, and pain points, and tailor your approach accordingly. If the individual perceives the value of what you offer, the decision to say "yes" becomes easier.

Offer Simplicity and Clarity

Complexity often leads to hesitation and doubt. Make your proposition simple and straightforward. Avoid using technical jargon or overwhelming the prospect with too much information. Clearly outline the key points and benefits to help them make an informed decision easily.

Leverage Social Proof

Humans tend to follow the crowd and seek validation from others. Use social proof to your advantage by showcasing positive reviews, testimonials, or case studies from satisfied customers. Demonstrating that others have already said "yes" builds confidence in your offer.

Time-Sensitive Incentives

Creating a sense of urgency can motivate prospects to act promptly. Offer limited-time promotions, discounts, or exclusive deals that encourage them to say "yes" sooner rather than later.

Address Objections Proactively

Identify potential objections the prospect may have and address them proactively. Show understanding and provide solutions to their concerns. By doing so, you remove barriers that could prevent them from saying "yes."

Empower with Choices

Instead of presenting a single option, provide the prospect with choices. People appreciate having some control over their decisions. Presenting alternatives allows them to select the option that best suits their preferences, increasing the chances of a positive response.

Create a Fear of Missing Out (FOMO)

FOMO is a powerful psychological trigger. Communicate that your offer is limited or exclusive, and they might miss out on a great opportunity if they don't say "yes" now. However, be honest and transparent in your approach.

Use Persuasive Language

The words you use can significantly impact the prospect's decision-making process. Employ persuasive language, such as "you," "free," "guarantee," and "instant." Craft your message with positivity and confidence.

Conclusion

Mastering the art of making it easy for prospects to say "yes" is a skill that can transform your personal and professional interactions. Combine these strategies with authenticity and empathy, and you'll find that achieving positive responses becomes not just a goal but a reality. So, go ahead and apply these principles to unlock the power of "yes" in your life.

[vihaahospitals]

Reasons Why First Aid is Important in Daily Life:

1.Preparedness: Having a basic understanding of the principles of first aid can make all the difference when there’s an emergency or any type of unexpected situation. Knowing how to react and how to provide assistance is essential for anyone who wants to be ready and well-prepared for any sort of medical emergency that may arise. This knowledge gives you the confidence to handle whatever situation may come your way without panicking.

2. Injury Prevention: First aid also teaches people about ways to prevent injuries from happening in the first place such as using safety equipment, proper lifting techniques, fire safety, proper food handling and so much more. Educating yourself can save lives from serious injuries and even death in some cases by knowing what to do before, during and after an accident happens. Knowing the importance of these principles can be a matter of life or death someday!

3. Response Time: When faced with an emergency situation, it's important to act fast which is why first aid training teaches people skills such as CPR and how to properly use a defibrillator machine or other medical devices when needed. This can help save someone’s life if they go into cardiac arrest or suffer from a stroke while they are waiting for professional medical help to arrive on the scene!

4. Reducing Infection Risk: Knowing how to treat minor cuts or abrasions is another important part of having basic first aid training; you need to know how to cleanse wounds correctly in order avoid infections as well as properly bandage an injury in order for it heal correctly without scarring it further down the line. It's also learnt when taking certain types of medications should not be given just in case there are any allergies present that could worsen things even more if administered incorrectly!

5. Peace Of Mind: No one ever wants their day disrupted by serious situations where professional help is essential yet not available right away at all times (especially during off hours), so understanding basic first aid will give your family peace of mind knowing that someone in home is capable handling the problem until help arrives if necessary! This can really reduce stress levels associated with potential dangers that lurk around every corner unexpected times - meaning you avoid having panic attacks while dealing with emergencies too!

6. Feeling Empowered: Dealing with medical issues/situations can be extremely scary but being equipped with the right knowledge pays off over time because now you are no longer powerless when confronting such fears head on - instead feeling empowered because you know exactly what needs done if anything goes wrong days happen suddenly afterwards instead nightmares coming true soon after... The sense assurance always wins out over fear this instance like!

7. Alternatives To Professional: Help In some rare cases there aren't doctors nearby late night yet luckily skilled individuals have been trained enough gain skills needed work through problems presented given same attention would get hands professional anyway potentially saving time pain (both financially physically) depending severity issue hand - which generally win result saves overall worry worry more matter what turns out being most common benefit having taken course general best course action require makes world difference those familiar recently found themselves unfamiliar territory too worries aside due such course existed all begins end

[skarabrae-stone]

I think there’s also the idea that an older man’s character is more established than a young one’s, and he’s probably also settled down from any rashness/wildness of youth. To take Jane Austen books as an example, Colonel Brandon and Mr. Knightley both are well known in their communities, and have a steadiness of temperament and moral compass that are well-known and well-proven. They’re not going to change.

Compare this to Frank Churchill, who, while well-meaning, persuades Jane Fairfax into a secret engagement, then selfishly pursues his own enjoyment at her expense-- it’s commented several times that his actions are typical of a young man, who would naturally be thoughtless, impulsive, and impractical. (For example, the whole thing with the piano is repeatedly brought up as a rather inconvenient and misguided gift, typical of a young lover.) Edward Ferrars also enters an ill-judged secret engagement as a young man, which he later regrets when he’s older and wiser.

Before he’s revealed to be a rake, Willoughby shows a lack of propriety by cutting a lock of Marianne’s hair when they’re not formally engaged and taking her on a tour of Allenham house, without a chaperone and without permission from the owner of the house. He also, like Frank Churchill, tries to give an impractical gift-- in this case, he wants to give Marianne a horse which she can’t afford and has no place to keep. Because his estate is not nearby, the Dashwoods have no opportunity of ascertaining his real character. His lack of regard for social mores is chalked up to his youth rather than a greater want of principle right up until he jilts Marianne, which means that Eleanor and Colonel Brandon are pretty much the only people who notice the red flags in his behavior. (And in Jane Austen, a lack of regard for social mores/propriety pretty much ALWAYS denotes a general lack of principle.)

In Persuasion, Mr. Eliot is older, and one of the reasons Anne is suspicious of him is that he can’t quite hide his youthful immorality. She notices that when he speaks of the past, there are former associates, practices, and behavior that don’t speak of a good moral character. She is suspicious that he has only grown more cautious, rather than changed in essentials-- and she ends up being proven right. The fact that he’s older means she has more clues to figure him out, and therefore get an accurate understanding of his character before it’s too late.

I also think that women who valued education/intellectual pursuits might have been more attracted to a man who was not only well-educated, but had been “out in the world” enough that she could learn from him. In Pride and Prejudice, Elizabeth considers one of the benefits of marriage with Darcy to be that he could help improve her mind, as his education and range of experience are superior to hers. Colonel Brandon is also implied to be a steadying influence on Marianne. The idea that a husband would help shape his wife’s mind and character was considered a good thing-- as long as the husband himself was actually worth emulating.

Basically, I think the idea that someone you already know is safe is a big part of it-- even if Jane Austen’s heroines don’t start out knowing the hero, they usually get to know the hero’s friends, relations, and even servants, share a house with him, and so on before actually marrying. But I also think, based on books from that time period, that it was considered pretty normal for young men to be a bit feckless and “unformed”, and to change as they got older. A man who had been around long enough to have developed a reputation based on his actions rather than simply being young and charming, and to have a steady, fully-formed character that would be unlikely to change, would therefore be a safer bet.

One thing I think is very interesting (but that I have no coherent thesis about) is how the age gap “I have known you all your life” romance between Emma and Mr. Knightley seems like a repeated trope in 19th century novels and is often framed as a really good thing (eg Mr. Brooke and Meg in Little Women)

It’s so weird to me and I have such inchoate thoughts about it because it’s a trope that’s aged like milk. My twenty-first century reaction to reading that Mr. Knightley’s known Emma since she was a literal child, or that Mr. Brooke got interested in Meg when she was only 17, is “NOPE NOPE NOPE”

But… on the other hand, marriage was SO DIFFERENT in the 19th century, and ideas of what it should do and what what you should consider going into it, and how it changes a woman’s status both legally and socially are also very alien now. If you are in a system where you are raised knowing that you must marry, that that’s the only right and respectable path in life BUT ALSO that your whole life from that point will be completely dependent ton your husband and his income and his decisions…

Well, “You’ve known this guy you’re whole life and he’s been consistently a good person to you,” is actually a really good argument in his favor? It makes for a really safe option in a time when you had to gamble on some dude willing to marry you. (But then I get to the point of, ‘well why the age gap then, what’s wrong with being the same age in the 19th century,’ and I’ve got some more thinking to do. Something something economic stability or maybe some weird social ideas about gendered maturity levels?)

[pumpkinpaix]

Pleeeeeeease get into the class one at some point because I very much want to understand the class dynamics happening in the story but I have yet to find a meta that dives into it

god anon you want me dead don’t you alsjdfljks

referring to this post

okay, so -- my specific salt about class interpretations in mdzs are very targeted. I can’t pretend to have a deep understanding of how class works in mdzs generally because uhhhhh yeah i don’t think i have that. i’m just not familiar enough with the genre and/or the particulars of chinese class systems. but! i can talk in general terms as to why I feel a certain way about the class dynamics that I do think I understand and how I think they relate to the themes of the novel! i’m gonna talk about wei wuxian, the daozhangs, xue yang, and 3zun with, I’m sure, a bunch of digressions along the way.

the usual disclaimers: i do not think you are a bad person if you hold opinions contrary to my own. i may disagree with you very strongly, but like. this isn’t a moral judgment, fandom is transformative and interpretive etc. etc. and i may change my mind. who knows what the future will bring!

OKAY so let’s begin!

here’s the thing about wei wuxian: he’s not poor. I think because characters use “son of a servant” kind of often when they’re trying to insult him, a lot of people latch onto that and think that it’s a much stronger indication of his societal status than it actually is. iirc, most of the insults that fall along the “son of a servant” line come after wei wuxian starts breaking severely from tradition. it’s a convenient thing to attack him for, but doesn’t actually indicate anything about his wealth. (exception: yu ziyuan, but that’s a personal familial issue) this is in direct contrast to jin guangyao who is constantly mocked for his family line, publicly and privately, no matter what he does.

so this, coupled with all the jokes about wwx never having any money (wei wuqian, sizhui’s “i’ve long since known you had no money” etc.), plus his like, rough years on the street as a child ends up producing this interpretation of wei wuxian, especially in modern aus, as someone who is very class conscious and “eat the rich”. but the fact of the matter is, wei wuxian IS rich. aside from the years in his childhood and the last two years of his life in yiling, like -- wei wuxian had money and status. he is gentry. he is respected as gentry. he is treated as a son by the sect leader of yunmeng jiang -- he does not have the jiang name, but it is so very clear that jiang fengmian favors him. wei wuxian is ranked fourth of all the eligible young masters in the cultivation world -- that is not a ranking he could have attained without being accepted into the upper class.

wei wuxian’s poverty does not affect him in the way that it affects jin guangyao or xue yang. he is of low-ish birth (still the son of jiang fengmian’s right hand man though! ok sure, “son of a servant” but like. >_> whatever anyways), but for most of his life he had money. he, jiang cheng, and their sect brothers go into town and steal lotus pods with the understanding that “jiang-shushu will pay for it”. this is a regular thing! that’s fucking rich kid behavior!!! wei wuxian is careless with money because he doesn’t have to worry about it. he still has almost all the benefits of being upper class: education, food security, respect, recognition etc. I think there may also be a misconception that wei wuxian was always on the verge of being kicked out by yu ziyuan, or that he was constantly walking on eggshells around her for fear of being disowned, but that is just textually untrue. i could provide receipts, but I admittedly don’t really feel like digging them up just now ;;

even in his last years in yiling, he was not the one who was dealing with the acute knowledge of poverty: wen qing is the one managing the money, and as far as we know, wei wuxian did little to no management of daily life during the burial mounds days -- mostly, he’s described as hiding in his cave for days on end, working on his inventions, running around like a force of chaos, frivolously making a mess of things -- it’s very very cute that he buries a’yuan in the dirt, but in classic wei wuxian fashion, he did Not think about the practical consequences of it -- that A’Yuan has no other clean clothes, and now he’s gotten this set dirty and has no intention of washing them. is this a personality thing? yeah, but I think it’s also indicative of his lack of concern over the logistics of everyday survival, re: wealth.

furthermore, i think it is important to remember that wei wuxian, when he is protecting the wen remnants, is not protecting common folk: he is still protecting gentry. fallen gentry, yes! but gentry nonetheless. wen qing was favored by wen ruohan, and wen ning himself says that he has a retinue of people under his command (the remnants, essentially). their branch of the family do not have the experience of living and growing in poverty -- they are impoverished and persecuted in their last years, but that’s a very different thing from being impoverished your whole life. (sidenote: I do not believe wei wuxian’s primary motivation for defending the wen remnants was justice -- i believe he did it because he felt he owed wen ning and wen qing a life debt, and once he was there, he wasn’t going to stand around and let the work camps go on. yes, he is concerned about justice and doing the right thing, but that’s not why he went in the first place. anyways, that’s another meta)

after wei wuxian returns, he then marries back into gentry, and very wealthy gentry at that. lwj provides him all the money he could ever want, he is never worried about going homeless, starving, being denied opportunities based on his class and accompanying disadvantages. who would dare? and neither wei wuxian nor lan wangji seem to have much interest in shaking up the order of things, except in little things like the way they teach the juniors. they live in gusu, under the auspices of the lan, and they live a happy, domestic life.

were his years on the street traumatizing? yes, of course they were, there’s so much delicious character exploration to be done re: wei wuxian’s relationship to food, his relationship to his own needs, and his relationship to the people he loves. it’s all important and good! but I feel very strongly that that experience, while it was formative for him, did not impart any true understanding of poverty and the common person’s everyday struggles, nor do I think he ever really gains that understanding. he is observant and canny and aware of class and blood, certainly, but not in a way that makes it his primary hill to die on (badum-tss).

this is in very stark contrast to characters like jin guangyao and xue yang, and to some extent, xiao xingchen and song lan. I’ll start with the daozhangs, because I think they’re the simplest (??).

I think both xiao xingchen and song lan have class consciousness, but in a very simplified, broad-strokes kind of way (at least, given the information we know about them). we know that the two of them share similar values and want to one day form their own sect that gives no weight to the nobility of your lineage and has no concern with your wealth. we also know that they both disdain intersect politics and are more concerned with ideals and principles rather than status. but, I think because of that, this actually somewhat limits their perception and understanding of how status is used to oppress. as far as we know, neither of them participated on any side in sunshot and they demonstrate much more interest in relating to the commoners. honestly, i hc that they were flitting around trying to help decimated towns, protecting defenseless villages etc. I ALSO think this has a lot of interesting potential in terms of xiao xingchen and wei wuxian’s relationship, if xiao xingchen is ever revived. regardless of whether you’re in CQL or novel verse, xiao xingchen really doesn’t know wei wuxian at all, other than knowing that he’s his shijie’s son. he knows that cangse-sanren met with a tragic end, like yanling-daoren before her, and that he wants to be different. but here is cangse-sanren’s son, laying waste to entire cities, desecrating the dead. I would very much like to get into xiao xingchen’s head during that period of time (and i think, if i do it right, i can write some of it into the songxiao fixit), but that’s neither here nor there, because i’ve wandered off from my point again.

i would posit that song lan is used to an ascetic lifestyle, and xiao xingchen probably is too -- but that’s different from poverty because there’s an element of choice to it. I also think that neither of them is particularly worldly, xiao xingchen especially. he lived on an isolated mountain until he was like, seventeen, and he came down full of ideals and naivete about how the world worked. I think that both of them see inequality, that they are angered by it, and that they want to do something about it -- but their solution is neither to topple the sects, nor is it to reform the system. rather, it seems to be more about withdrawing and creating their own removed world. I think that the daozhangs embody a kind of utopianism that isn’t present in the minds of any of the other characters, not even wangxian. honestly, baoshan-sanren’s mountain is a utopian ideal, but one that is not described. it exists outside of and beyond the world. i have a lot of jumbled, vague thoughts about utopianism generally, mostly informed by china miéville and ursula k. le guin, and I don’t think i have the ability to articulate them here, but i wanted to. hm. say something? there is something about the inherent dystopianism contained within every utopia, that utopias are necessary, but also reflections of the existence of terrible things in their conception. idk. there’s something in there, I know it!! but i suppose what I want to say is -- i do not think the daozhangs understand class and social hierarchy very deeply because they don’t see a need to examine it deeply. for their goals, the details aren’t the point. they’re not looking to reform within the system, they’re looking to build something outside of it. I think they spend a lot of time concerned with alleviating the symptoms of social oppression, and their values reflect the injustices they witness there.

regardless, even if their story ends in tragedy and there is a certain amount of critique re: the utopian approach, i think the text still emphasizes that xiao xingchen left a utopia and that he thought that people mattered enough for him to try, and that was an incredibly honorable, kind, and human thing to do.

YEAH SURE THE DAOZHANGS ARE THE SIMPLEST ok ok RETURNING to class and moving forward: xue yang.

i also don’t think xue yang has class consciousness lol, or not in any way that really matters, but I do think poverty impacted him in a much stronger way than it impacted wei wuxian. wei wuxian spent some years on the street as a child. xue yang grew up on the streets. chang ci’an’s horrific treatment of him was directly due to his class and social standing: chang ci’an is a nobleman and xue yang is not even worth the dirt beneath the wheels of his cart. what I think is the seminal point though, is that this does not make xue yang think particularly deeply about systemic injustice, because xue yang is so self-centered, self-driven, and individualistic. he is not even slightly concerned about how poverty and class might affect other people -- they’re other people. what he takes away from his experience is not an anger at being wrongfully cheated by a system, but an anger at being wrongfully cheated by a specific man.

xue yang is not particularly concerned with the politics of the aristocracy -- he has no obvious ambitions other than, “i want to eat sweets whenever i please”, “i want to hurt anyone who wrongs me”, and “i want to be so strong that no one can hurt me”. like, he just doesn’t care -- it’s not the kind of power he wants. he sneers at people for like, personal reasons, not class reasons -- “you think you’re better than me” re: xiao xingchen and song lan. to him, all people -- poor, wealthy, noble, common -- are essentially equal, and they are all beneath him. after all, what does he care what family someone comes from, how much money they have? everyone bleeds when you cut them. some of them might be harder to get to than others, but xue yang does not fear that sort of thing. it’s just another obstacle he needs to vault on his way to getting revenge and/or a pastry.

ANYWAYS onto jin guangyao (wow this is hm. getting rather long ahaha oh dear): I would argue that the two characters with the most acute understanding of class/societal politics and the injustice of them are jin guangyao and lan xichen. i’ll start with jin guangyao for obvious reasons.

where xue yang took the damaging effects of poverty as personal slights, I think jin guangyao is painfully aware that there is nothing personal about them, which is, in some ways, much worse. why are two sons, born on the same day to the same father, treated so differently? just because.

he watched his mother struggle and starve and work herself to the bone in a profession where she was constantly disrespected and abused for almost nothing in return, while his father could have lifted her out of poverty with the wave of a finger. why didn’t he? because he didn’t like her? no -- because he didn’t care, and the structures of the society they live in protect that kind of blase treatment of the lower class.

“so my mother couldn’t choose her own fate, is that her fault?” jin guangyao demands. he knows that he is unbelievably talented, that he has ambition, that he has potential, and that all of it is beyond his grasp just because his father didn’t want to bother with it. his mother’s life was destroyed, and his own opportunities were crippled with that negligence. it isn’t personal. that’s just the way things are. your individual identity is meaningless, your humanity does not exist. when he’s kicked down the steps of jinlin tai, it’s just more confirmation that no matter how talented or hardworking he is, no one will give him the time of day unless he finds a way to take it himself and become someone who “matters”.

jin guangyao’s cultivation is weak because he had a poor foundation, and he had a poor foundation because he was denied access to a good one. he copies others because that’s all he can do at this point, and he copies so well that he can hold his own against some of the strongest cultivators of his generation. he’s disparaged for copying and “stealing” techniques, but -- he never would have had to if only he had been born/accepted into the upper class. the fact is that i really do think jin guangyao was the most promising cultivator of his generation that we meet, including the twin jades and wei wuxian: he had natural talent, ambition, creativity, determination and cunning in spades. in some ways, I think that’s one of the overlooked tragedies of jin guangyao: the loss of not just the good man he could have been, but the powerful one too. imagine what he could have done.

jin guangyao spends his entire time in the world of the aristocracy feeling unsteady and terrified because he knows exactly how precarious his position is. he knows how easy it is to lose power, especially for someone like him. he’s working against so many disadvantages, and every scrap of honor he gets is a vicious battle. jin guangyao fears, and I think that’s something that’s lacking in xue yang, wei wuxian and the daozhangs’ experiences/understandings of poverty. i think it’s precisely that fear that emphasizes jin guangyao’s understanding of class and blood. jin guangyao exhibits an anxiety that neither wei wuxian nor xue yang do, and it’s because he truly knows how little he is worth in the eyes of society and how little there is he can do to change that. to me, it very much feels related to the anxiety of not knowing if tomorrow you’ll have something to eat, if tomorrow you’ll still have a home, if tomorrow someone will destroy you and never have to answer for it. it’s the anxiety of knowing helplessness intimately.

moreover, jin guangyao is the only person shown to use the wealth and power at his disposal to take concrete steps to actually help the common people typically ignored by the powerful -- the watchtowers. they’re described in chapter 42. it’s a system that is designed to cover remote areas that most cultivators are reluctant to go due to their inconvenience and the lack of means of the people who live there. the watchtowers assign cultivators to different posts, give aid to those previously forgotten, and if the people are too poor to pay what the cultivators demand, the lanling jin sect pays for it. jin guangyao worked on this for five years and burned a lot of bridges over it. people were strongly opposed to it, thinking that it was some kind of ploy for lanling jin’s personal benefit. but the thing is -- it worked. they were effective. people were helped.

i believe CQL frames the watchtowers as an allegory for a surveillance state/centralized control (i think?? it’s been a minute -- that’s the hazy impression i remember, something like a parallel to the wen supervisory offices?), but I personally don’t think that was the intent in the novel. the watchtowers are a public good. lanling jin doesn’t staff them with their own sect members -- they get nearby sects to staff them. it’s a warning network that they fund that’s supposed to benefit everyone, even those that everyone had considered expendable.

(did jin guangyao do terrible things to achieve this goal? yeah lol. it’s not confirmed, but his son sure did die... suspiciously...... at the hands of an outspoken critic of the watchtowers........ whom he then executed....... so like, maybe just a convenient coincidence for jin guangyao, two birds one stone, but. it seems. Unlikely.)

lan xichen is the only member of the gentry that ever shows serious compassion for and nuanced understanding of jin guangyao’s circumstances. lan xichen treats him as his equal regardless of jin guangyao’s current status -- even when he was meng yao, lan xichen treated him as a human being worthy of respect, as someone with great merits, as someone he would choose as a friend, but he did so knowing full well the delicate position meng yao occupied. this is in direct contrast to nie mingjue, who also believed that meng yao was worthy of respect as a human being, but was completely unable to comprehend the complexities of his circumstances and unwilling to grant him any grace. you know, the difference between “i acknowledge that your birth and status have had effects upon you, but I don’t think less of you for it” and “i don’t consider your birth and status at all when i interact with you because i think it is irrelevant” (“i don’t see color” anyone?)

to illustrate, from chapter 48:

大抵是觉得娼妓之子身上说不定也带着什么不干净的东西，这几名修士接过他双手奉上来的茶盏后，并不饮下，而是放到一边，还取出雪白的手巾，很难受似的，有意无意反复擦拭刚才碰过茶盏的手指。聂明玦并非细致之人，未曾注意到这种细节，魏无羡却用眼角余光扫到了这些。孟瑶视若未见，笑容不坠半分，继续奉茶。蓝曦臣接过茶盏之时，抬眸看他一眼，微笑道：“多谢。”

旋即低头饮了一口，这才继续与聂明玦交谈。旁的修士见了，有些不自在起来。

rough tl:

Probably because they believed that the son of a prostitute might also carry some unclean things upon his person, after these few cultivators took the teacups offered from [Meng Yao’s] two hands, they did not drink, but instead put them to one side, and furthermore brought out snow white handkerchiefs. Quite uncomfortably, and whether they were aware of it or not, they repeatedly wiped the fingers they had just used to touch the teacups. Nie Mingjue was not a detail-oriented person and never took note of such particulars, but Wei Wuxian caught these in the corner of his eye. Meng Yao appeared as if he had not seen, his smile unwavering in the slightest, and continued to serve tea. When Lan Xichen took the teacup, he glanced up at him and, smiling, said, “Thank you.”

He immediately dipped his head to take a sip, and only then continued to converse with Nie Mingjue. Seeing this, the nearby cultivators began to feel somewhat uneasy.

all right, since we’re in full cyan-rampaging-through-the-weeds mode at this point, i’m going to talk about how this is one of my favorite 3zun moments in the entire novel for characterization purposes because it really highlights how they all relate to one another, and to what degree each of them is aware of their own position in relation to the others and society as a whole.

1. nie mingjue, who is a forthright and blunt person, sets meng yao to serving tea and is done with it. he notices nothing wrong or inappropriate about the reactions of the people in the room because it’s not the sort of thing he considers important.

2. meng yao, knowing that his only avenue is to take it lying down with a smile, masks perfectly.

3. lan xichen, noticing all this, uses his own reputation to achieve two things at once: pointedly shame the other cultivators in attendance, and show meng yao that regardless of others’ opinions, he considers him an equal and does not endorse such behavior--and he does it while taking care that no fallout will come down on meng yao’s head.

is this yet another installment of cyan’s endless lxc defense thesis? why yes it is! no one is surprised! but this is my whole point: both meng yao and lan xichen understand the respective hierarchy and power dynamics within the room, while nie mingjue very much does not. this is not because nie mingjue is a bad person or because nie mingjue is stupid--it’s a combination of personality and upbringing. nie mingjue is straightforward and has no patience for such games. but then again, he can afford not to play because he was born into such a high position: that’s a privilege.

to break it down: meng yao knows that he is the lowest-ranked person in the room, sees the way people are subtly disrespecting him in full view of his general who is doing nothing about it. in some ways, this is good -- nie mingjue’s style of dealing with conflict is very direct and not at all suited to delicate political maneuvering. after all, the way he promoted meng yao was actually quite dangerous to meng yao: he essentially guaranteed that his men would bear meng yao a grudge and that their disrespect for him would only be compounded by their bitterness at being punished on his behalf. (it’s like, why often getting parents or teachers to intervene ineffectively in bullying can just be an incitement to more bullying -- same concept) meng yao’s reaction during that scene shows that he’s pretty painfully aware of this and is trying to defuse the situation to no avail. nie mingjue gives him a bootstrap speech (rip nie mingjue i love u so much but. sir) and then promotes him, which is pretty much the only saving grace of that entire exchange, for meng yao at least.

lan xichen, on the other hand, understands both that meng yao is the lowest-ranked person in the room and that any direct attempt to chastise the other cultivators in the room will only serve to hurt meng yao in the long run. he knows that if this were brought to nie mingjue’s attention, he would be outraged and not shy about it -- also bad for meng yao. so he uses what he has: his immaculate reputation. by acting contrary to the other cultivators’ behavior, he demonstrates that he finds their actions unacceptable but with the plausible deniability that it wasn’t directed at them, that this is just zewu-jun being his usual generous self. this means that the other cultivators have no one to blame but themselves, nothing to do but question their own actions. there is nowhere to cast off their discomfort. meng yao didn’t do anything. lan xichen didn’t do anything -- he just thanked meng yao and drank his tea, isn’t that what it’s there for? he doesn’t disrupt the peace, he doesn’t attack anyone and put them on the defensive, but he does make his position very clear.

i know this is a really small thing and i’m probably beating it to death, but I really think this shows just how cognizant lan xichen is of politics and emotional cause and effect in such situations. certainly, out of context I think the scene reads kind of cliche, but within the greater narrative of the story and within the arc of these characters specifically, I think it was a really smart scene to include. it also showcases lan xichen’s style of action: that he moves around and with a problematic situation as opposed to moving straight through.

not to be salty on main again, but this is why it’s very frustrating to me when I see people call lan xichen passive when he is anything but. his actions just don’t look like traditional “actions”, especially to an american audience. it’s easy to understand lan wangji and wei wuxian’s style of problem-solving: taking a stand, moving through, staying strong. lan xichen is juggling an inconceivable number of factors in any given situation, weighing his responsibilities in one role against those in another, and then trying to find the path through the thicket that will cause the least harm, both to himself and the thicket. lan wangji and wei wuxian are not particularly good at considering the far-reaching consequences of their actions -- again, not because they are bad people, but because of a combination of personality and upbringing. they’d just hack through the thicket, not thinking about the creatures that live in it. that is not a terrible thing! it isn’t. it’s a different way of approaching a problem, and it has different priorities. that’s okay. there are advantages and disadvantages on both sides, and where you come down is going to depend on your personal values.

okay we’ve spiraled far and away from my original point, but let’s circle back: i was talking about class.

I think it’s undeniable that class, birthright, fate etc. are some of the driving forces of thematic conflict in mdzs, and the way each character interacts with those forces reveals a lot about themselves and also about the larger themes of fate, chance, and what it means to be righteous and good and how that is and isn’t rewarded. a lot of the tragedy of mdzs (the tragedy that isn’t caused by direct aggression on the part of one group or another) stems from the injustices and slights that people suffered due to their lot in life. it isn’t fair. none of it is fair! we sympathize with jin guangyao because we recognize that what he suffered was unconscionable, even if we don’t excuse him. i sympathize A Lot with xue yang as well for similar reasons, though I understand that’s a harder sell. this is a story focused on the mistakes of an entrenched, aging gentry and the effects that those mistakes had on their children, and a lot of it has to do with prejudice based in class and birth status. whether the prejudice was the true reason or whether it was just a convenient excuse, the fact remains that the systems in place rewarded and protected the people in power who used it to cling to that power. mdzs is also a story of how the circumstances of one’s life can offer you impossible choices that you cannot abstain from, and it asks us to be compassionate to the people who made terrible choices in terrible times. it’s about the inherent complexity in all things! that sometimes, there are no good choices, and i don’t know, i’d like to think that people would show me compassion if I had to make the choices some of these characters did. not just wei wuxian, mind you, every single one of them. except jin guangshan because I Do Hate Him sorry. and i guess wen ruohan. i think that’s it.

good. GOD this is clocking in at //checks notes -- just over 5k. 8′D *stuffs some weeds into my mouth like the clown i am*

(ko-fi? :’D *lies down*)