#cathy o'neill

[mikexx2]

Yunaissance SP child roundup, p1

Let’s check in on how SP is chugging along with the gene pool, shall we? A lot of these kids are born of sims in my downtownie pool with @katatty and @kooli-sims and dormie pool with @moocha-muses​ and of course this iconic townie pool.

First up!

The O’Neill siblings: Eric, Kitty and Cathy, born to Ann O’Neill and Laura Lee, who is always pregnant and whose mouth and brown hair is obviously very recessive.

Then a lightning round of singles:

Trixie Harbin, born to Sasha Harbin and Asha Nazari.

Danica Woodbine, born to Theresa Woodbine and Abigail O’Rourke.

Bronson Rossi, born to Sheena Rossi (Vivian) and Tamsin Henry (Aiyanna).

Annabelle Walker, born to “Shark Eyes” Walker and Zenith Chastain.

And lastly, my personal favourite...

Jean Tak, born to Jae-kyung Tak and Matteo Flores-Fonseca. That floppy hair framing those cheekbones? I live!

[novemberhope]

[fortressofserenity]

Actually normal

When it comes to creating an audience surrogate character, sometimes this is accidental since such a character like that could simply be an ordinary person reacting to extraordinary people and circumstances. At other times, the audience surrogate character is relatable to just a few people. So this character wouldn’t be relatable to anybody else, no matter how likable or charismatic they are. April O’Neil from the Teenage Mutant Ninja Turtles comics falls into the former category, if because she’s often just an ordinary human woman interacting with more outrageous, larger than life figures. This also makes it harder to give her a consistent ethnicity, given anybody would act the same as she would if they were in her position.

If you’re a human being interacting with either anthropomorphic animals, therianthropic humans or humans losing their humanity in one way or another then you’d easily be April O’Neil, as she’s one of the few recurring human characters to remain a normal person for this long. Admittedly this is based on my recollections of the TMNT comics I’ve read and the TMNT cartoons I’ve watched, but it seems to me that April O’Neil is one of the truest audience surrogate characters to exist in fiction. If because anybody could easily be her if they were to interact with talking animals and people who lose their humanity like Baxter Stockman, which is why she worked too well as an audience surrogate as to not have a consistent ethnicity.

She doesn’t even have a consistent hair colour, especially outside of animation where in the comics she had dark hair and in the 1990s movie she seemed to be blonde. Felicity Smoak most likely falls into the latter category, especially as time went on where she not only dated Oliver Queen but also got to marry him. That actually makes her less relatable to other people in the sense that not everybody gets to marry the cream of the crop, everybody else just dates and marries those who’re good enough and within their reach. If anything, the average woman is more like Cathy Guisewite’s Cathy than she will be with Felicity Smoak, Cathy is neither extraordinarily talented at something nor is she ridiculously incompetent.

She’s neither rich nor poor, her boyfriends aren’t particularly the most glamourous or at least the most sexualised, Irving could be intended to be tall, dark and handsome but he ended up being rather desexualised for some reason. But that also makes him more attainable as a spouse and lover because not everybody gets to marry smoking hot billionaires, that one could make a good argument for Irving being one of those boy next door love interests in comics. Even among celebrities and athletes, women marry men who are interesting and charismatic in some way, but they aren’t particularly sexualised a lot either. Irving could easily be one of those men in a way.

It seems when it comes to crafting a true audience surrogate, if April O’Neil’s any indication they are often a lightning in a bottle. They also work best when they’re actually ordinary people, that they come off more relatable and grounded this way too.

[sidewalkchemistry]

[Paul Piff:] We've been finding that wealthier individuals are more likely to perceive the pursuit of self-interest, as opposed to collective interest, as moral and favorable. We're even observing this moralization of greed, this 'greed is good' mentality. [Cathy O'Neil:] This country absolutely selects for psychopathic thinkers, you know, people who have no empathy whatsoever. Because once you have successfully have cleaved off ethical considerations, you're incredibly efficient. - Growing Economy, Miserable Citizens: Why Are Rich Countries So Unhappy?

[lizziethereader]

I last read...

'The Shame Machine' by Cathy O'Neil

what I wanted: to see if the book delivers on the intriguing title

what I got: more economy than I expected (I should have considered the author)

what I thought: This was really interesting! Although I was hoping for a little more psychology and/or philosophy, I enjoyed the economy-related and autobiographical nature of this book. It is definitely worth reading and provides plenty of food for thought that encourages reflection about to one's shame mindset. I rate this 3 out of 5 things to hide embarrassing mistakes with.

[radicalandmathematical]

Would you recommend me some books or blogposts that helps you be interested in maths. I can’t seem to like it, lmao🙃🙃

Honestly? I haven't read many books (beyond textbooks) or blog posts about math, because I was genuinely just interested from the get go, and got more interested the more advanced math classes I took at uni, so I don't have any personal recommendations. I mostly just... hear about cool stuff by word of mouth or in class.

There are some recommendations of books for non-mathematicians from various people here. I'd give that a scroll through and see if anything sounds a bit interesting.

Also, a book I haven't read, but am personally interested in is Weapons of Math Destruction by Cathy O'Neil. It goes into detail about the social impacts and harms that can be done by algorithms, which might interest you if you care about social issues.

If you're open to some youtube channels, PBS Infinite Series has some interesting videos from what I recall, though I'm not sure how advanced you need to be to understand them.

I don't know how much math you've been exposed to, but if you've only done like, high school math or just first year university calculus, then know that being uninterested in that is not the same as being uninterested in math. I personally hate calculus and all that stuff. It's not my cup of tea. But often we're not exposed to what else there is at that level, and there is so much more.

Combinatorics is pretty accessible without a lot of math background and is very different from the kind of stuff you do in high school once you get past the basics. It can answer questions like "are there two people on the planet with the exact same number of hairs on their body?" (Which I believe was covered in one of the PBS infinite series videos!) or questions like the Königsberg Bridge Problem, which is about whether you could cross each bridge in that town exactly once.

Cryptography is also another way to look at math that's interesting and fun. I recommend looking into the Enigma Machine from world war 2. You can find a bunch of videos on youtube about it, I think this one gives a pretty good overview of how it worked and how many different settings it had. Cryptography is interesting in general, because, I mean. It's using math to send and break secret messages. The history of it is also really interesting, especially since there really weren't a lot of developments until fairly recently in history.

There are of course, loads of other areas of math that are interesting and very different from high school level math. It's a huge field.

[joys-of-everyday]

I was tagged by @stardust-falling ^.^ Thank you!

1. three ships: T_T choosing from my babies. Hualian (TGCF). They invented love with their godly powers or smth. 9S/2B (Nier Automata) The inherent eroticism of killing someone over and over. ...and omg this is going to get me killed, but Cao Cao and Guo Jia as a semi-platonic ship for their redonkulus chemistry in 三国机密/Secret of the Three Kingdoms (and others).

2. first ever ship: Killugon from HunterxHunter way way back now. Had such importance to me growing up. Nostalgia U-U

3. last song: Focus, by Liu Yu

4. last movie: Honor Among Thieves (twas great. Recommend for all dnd fans and non-fans)

5. currently reading: Weapons of Math Destruction by Cathy O'Neil (An excellent book if you want to know in greater detail to what extent algorithms screw people over. tl;dr is 'far more than you would expect')

6. currently watching: 大军师司马懿之军师联盟/Advisors Alliance and Foundation (Apple TV). Two extremely different flavours of Empire politics.

7. currently consuming: supermarket brand British tea with milk XD

8. currently craving: something spicy

if you want to do it and haven't done it yet (or want to do it again!) @meridissa @rainy-days-and-cabbage @lryghe @slytherinzidian @zykamiliah @settlein4580

[mikexx2]

And in other developments:

[thefugitivesaint]

It’s one of my rare re-bloggings (breath deep and take it in people). Give the Rolling Stones article a read. Here’s a snippet: “As AI has exploded into the public consciousness, the men who created them have cried crisis. On May 2, Gebru’s former Google colleague Geoffrey Hinton appeared on the front page of The New York Times under the headline: “He Warns of Risks of AI He Helped Create.” That Hinton article accelerated the trend of powerful men in the industry speaking out against the technology they’d just released into the world; the group has been dubbed the AI Doomers. Later that month, there was an open letter signed by more than 350 of them — executives, researchers, and engineers working in AI. Hinton signed it along with OpenAI CEO Sam Altman and his rival Dario Amodei of Anthropic. The letter consisted of a single gut-dropping sentence: “Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.” How would that risk have changed if we’d listened to Gebru? What if we had heard the voices of the women like her who’ve been waving the flag about AI and machine learning? Researchers — including many women of color — have been saying for years that these systems interact differently with people of color and that the societal effects could be disastrous: that they’re a fun-house-style distorted mirror magnifying biases and stripping out the context from which their information comes; that they’re tested on those without the choice to opt out; and will wipe out the jobs of some marginalized communities. Gebru and her colleagues have also expressed concern about the exploitation of heavily surveilled and low-wage workers helping support AI systems; content moderators and data annotators are often from poor and underserved communities, like refugees and incarcerated people. Content moderators in Kenya have reported experiencing severe trauma, anxiety, and depression from watching videos of child sexual abuse, murders, rapes, and suicide in order to train ChatGPT on what is explicit content. Some of them take home as little as $1.32 an hour to do so. In other words, the problems with AI aren’t hypothetical. They don’t just exist in some SkyNet-controlled, Matrix version of the future. The problems with it are already here. “I’ve been yelling about this for a long time,” Gebru says. “This is a movement that’s been more than a decade in the making.” Edit: I failed to suggest that you, dear reader, should peruse Cathy O'Neil's 2016 book, 'Weapons Of Math Destruction' which details the opaque nature of algorithms and the biases that are baked into them. As O'Neil puts it, "Algorithms are opinions embedded in code." O'Neil is careful in what kinds of algorithms she targets with her critiques and isn't offering a blanket denunciation of algorithms per se, just the large, scalable and, in her evaluation, unfair algorithms that have begun to have direct impacts on people's lives, often in destructive ways. "I worried about the separation between technical models and real people, and about the moral repercussions of that separation," O'Neill writes."

These Women Tried to Warn Us About AI

[mintmatcha]

Hello hope Sunday is treating you well ❤️☀️ Two things

Who is author of Weapons of Math Destruction? That sounds like a good read.

Also up to 15 lbs of free weights Ive gained muscles 😂 and my mom is being funny and will ask me to flex and then whistle. I'm now the official jar opener of the house.

Cathy O'Neil is the author!!

and congrats! staying consistent is truly the hardest part!!! you're doing so well

[quotes-by-dilanka]

The privileged are processed by people, whereas the poor are processed by algorithms.

—Cathy O'Neill, in her book Weapons of Math Destruction

[fouralignments]

Ai is out of control. I was not prepared for that hair. And as a black person I...actually have a cousin who looks like this [minus the curls] and I don't know how to process that information.

AI has a bunch of problems, which is the understatement of the year. However, I would say that ChatGPT and AI art is just the latest iteration of Big Tech's Big Data and their algorithm and other issues like AI in the job process, police, political ads on Facebook, etc. Its been here awhile.

This is not ok.

I've read once in Weapons of Math Destruction by Cathy O'Neil that despite the appearances of naturality of a model and even their impartiality; but, they're not, models reflect the ideologies, goals, biases and blindspots. I think the same is true for 'AI.' It also picks up gender/sex/class/race/etc. in the big data that it gets fed. Scientists or techbros forget that things change and so does the model, however forget to feed it new data or expanding other variables all because profit is synonymous with the truth and winds up hurting the folks on the other side of the transaction.

However, do not despair, there's been actual good news on the front. I'm not an expert, but I'm someone likes reading a shit ton.

[sensessences]

Cathy O'Neil's book goes exactly on this point, specifically about how Big Data are huge black boxes of devastating on several different fronts. Here is a bit (sorry the lack of quality, its night)

the book is Weapons of Math Destruction

every so often im struck by the memory of one of my college professors getting very angry with our class (art history of pompeii 250) because when she excitedly detailed the ingenious roman invention of heated floors in bathhouses via hearths in small crawlspaces, we asked who was tending the fires. she said "oh, slaves i suppose. but that isnt the point". and we said that it actually very much was the point. she had just told us that in roman society there were dozens of people, maybe hundreds, who spent every day of their enslaved lives crawling in cramped, hot, smoky tunnels to light fires to warm pools of water (which they were not allowed to swim in). how could that not be the point?

she wanted us to focus on the art, on the innovation of heated plumbing, on the tiles and decorations of the bathhouses, and all we wanted to do was learn more about the people under the floors. and she didn't know anything more about that. in fact, she said she thought we were focusing too much on superfluous details.

it feels almost hokey to put too fine a point on the idea im getting at here but i will anyway: There are a lot of people who are still under the floors. all these beautiful, convenient, brilliant innovations of modern society (think fast fashion, chatgpt, uber, doordash) are still powered by people working in inhumane, untenable conditions.

the people who run these systems want you to focus on the good - who doesnt love warm water? - but if anything is going to improve or change in our lifetimes, you need to examine these things with an attentive, critical, and empathetic eye. and for fucks sake stop ordering from amazon

[lizziethereader]

November 2023 wrapup

Why, yes, this is a November wrapup at the end of December. Work has kept me from doing this earlier, but I still wanted to finally upload this because November was a really fun reading month. I participated in nonfiction November and although it's not a requirement, read almost exclusively nonfiction. The thing with nonfiction is that it's harder for me to get myself to pick it up when there are lots of novels at hand, but I do generally quite enjoy nonfiction as well, so November is always a good reminder of that.

favorite of the month: Having and Being Had by Eula Bliss, Friendaholic by Elizabeth Day

nonfiction of the month (8): The Shame Machine by Cathy O'Neil, Arrangements in Blue by Amy Key, The Psychology of Money by Morgan Housel, Having and Being Had by Eula Bliss, User Friendly by Cliff Kuang and Robert Fabricant, On Friendship by Michel de Montaigne, Music is History by Questlove, Friendaholic by Elizabeth Day

classics (1): On Friendship by Michel de Montaigne

poetry (1): Time is a Mother by Ocean Vuong

graphic novel (1): Crawlspace by Jesse Jacobs

[rohinikasturi1]

Navigating the Analytics Revolution: Voices from Visionary Leaders

In today's rapidly evolving business landscape, the analytics revolution is a transformative force reshaping industries, redefining strategies, and driving innovation. As organizations embrace data-driven approaches, insights from visionary leaders offer valuable guidance on navigating this complex and dynamic terrain.

The Rise of Big Data and Advanced Analytics

The analytics revolution has its roots in the explosion of big data, which has enabled organizations to process and analyze vast amounts of information. Visionary leader Viktor Mayer-Schönberger, co-author of "Big Data: A Revolution That Will Transform How We Live, Work, and Think," emphasizes that the true value of big data lies in its ability to reveal previously hidden patterns and insights. Mayer-Schönberger advocates for a shift from intuition-based decision-making to one grounded in empirical evidence.

The Power of AI and Machine Learning

Artificial intelligence (AI) and machine learning (ML) are at the forefront of the analytics revolution, providing powerful tools for predictive and prescriptive analytics. Fei-Fei Li, a pioneering AI researcher and co-director of the Stanford Human-Centered AI Institute, underscores the potential of AI to augment human capabilities and transform industries. Li argues that AI-driven analytics can help organizations anticipate market trends, optimize operations, and enhance customer experiences.

Ensuring Data Integrity and Ethics

As data becomes a critical asset, maintaining its integrity and addressing ethical concerns are paramount. Visionary leader Cathy O'Neil, author of "Weapons of Math Destruction," highlights the risks associated with biased algorithms and data misuse. O'Neil calls for greater transparency and accountability in data practices to ensure fair and ethical use of analytics. She advocates for robust data governance frameworks to protect privacy and build trust.

Democratizing Data Access and Insights

The democratization of data analytics aims to make insights accessible to a broader audience within organizations. Visionary leader Tricia Wang, a global tech ethnographer, champions the concept of "thick data," which combines big data with qualitative insights to provide a more holistic understanding. Wang believes that empowering employees with intuitive analytics tools and fostering data literacy can drive innovation and improve decision-making across all levels of an organization.

Strategic Integration of Analytics

Analytics must be strategically integrated into core business processes to drive meaningful impact. Michael Porter, a leading authority on competitive strategy, argues that data analytics should align with organizational goals and create a sustainable competitive advantage. Porter highlights that companies leveraging analytics to refine their approach, optimize their value chains, and enhance customer engagement are better positioned to succeed in the digital age.

Overcoming Barriers to Adoption

While the benefits of analytics are clear, many organizations need help to adopt, including technical challenges, cultural resistance, and skill gaps. Visionary leader Jeanne G. Harris, co-author of "Analytics at Work," recommends a phased approach to adoption, starting with high-impact pilot projects that demonstrate value. Harris emphasizes the importance of continuous learning and development to equip employees with the skills needed to use analytics tools and methodologies effectively.

Real-World Transformations through Analytics

The transformative power of analytics is evident in numerous real-world applications. Visionary leaders often use case studies to illustrate how organizations leverage data to achieve remarkable results. For instance, Amazon's recommendation engine, powered by advanced analytics, has significantly boosted sales and customer loyalty. In healthcare, analytics predicts patient outcomes and improves treatment plans. These success stories highlight the potential for analytics to drive innovation and deliver tangible benefits.

The Future of Analytics: Trends and Innovations

Looking ahead, visionary leaders foresee continued advancements in analytics technologies and practices. Innovations such as real-time analytics, augmented analytics, and the integration of IoT data are expected to enhance organizational capabilities further. Visionary futurist Amy Webb, author of "The Big Nine," envisions a future where AI-driven analytics play a central role in strategic decision-making, enabling organizations to navigate uncertainty and capitalize on emerging opportunities.

Fostering a Data-Driven Culture

A key theme from visionary leaders is the importance of fostering a data-driven culture within organizations. This involves investing in the right technologies and cultivating a mindset that values data-driven decision-making. Visionary leader Thomas H. Davenport, a professor at Babson College and author of "Competing on Analytics," advises organizations to create an environment where data is accessible, employees are encouraged to experiment, and successes are celebrated. Davenport believes that strong leadership is crucial in driving this cultural shift.

Thriving in the Analytics Revolution

The analytics revolution offers unprecedented opportunities for organizations to innovate, optimize, and grow. By drawing on the insights of visionary leaders, businesses can effectively navigate this landscape and harness the power of data. From embracing AI and machine learning to ensuring data integrity and democratizing insights, a strategic and holistic approach is essential. As the analytics revolution evolves, staying agile, informed, and committed to data-driven practices will be key to thriving in the data-driven era.

[mikexx2]

And just like that, it’s time for Shara’s birthday!

Surrounded by a handful of neighbourhood children that I teleported over.

Shara picks up a cute new look and the Loves the Heat trait.