#scrape Facebook Advertising Data

[realdataapi1]

Facebook Ads Data Scraper | Scrape Facebook Advertising Data

Use our Facebook Ads Data Scraper to Scrape advertising data from one or multiple Facebook Pages. You can obtain page details, reach estimates, publisher platforms, report count, number of impressions, ad IDs, timestamps, and more.

[walks-the-ages]

[ID: a link preview of a stock image coffee table with a laptop with the facebook logo on the screen with text on top that says 'anyone who used facebook in the last 16 years can now get settlement money. here's how." end ID]

-USA Residents Only-

Time Sensitive- Apply before August 25th, 2023 (8/25/23)!

Filing a claim takes less than ten minutes, and can be done HERE

Excerpt from article:

Anyone in the U.S. who used Facebook in the last 16 years can now collect a piece of a $725 million settlement by parent company Meta tied to privacy violations — as long as they fill out a claim on a website set up to pay out money to the social network's users. 

The settlement stems from multiple lawsuits that were brought against Facebook by users who claimed that the company improperly shared their data with third-party sources such as advertisers and data brokers. The litigation began after Facebook was embroiled in a privacy scandal in 2018 with Cambridge Analytica, which scraped user data from the site as part of an effort to profile voters.

Meta denied any liability or wrongdoing under the settlement, according to the recently created class-action website. However, the agreement means that U.S. residents who used Facebook between May 24, 2007, and December 22, 2022, can file a monetary claim as long as they do so before August 25, 2023. 

Please reblog to signal boost this! As many people as possible should know about this to make their claim, if you don't do anything you don't get anything. It takes less than ten minutes to file and pick your payment option including pay/pal and ven/mo .

-USA Residents Only-

This ended August 25th, 2023!

[fabaulti]

I think most of us should take the whole ai scraping situation as a sign that we should maybe stop giving google/facebook/big corps all our data and look into alternatives that actually value your privacy.

i know this is easier said than done because everybody under the sun seems to use these services, but I promise you it’s not impossible. In fact, I made a list of a few alternatives to popular apps and services, alternatives that are privacy first, open source and don’t sell your data.

right off the bat I suggest you stop using gmail. it’s trash and not secure at all. google can read your emails. in fact, google has acces to all the data on your account and while what they do with it is already shady, I don’t even want to know what the whole ai situation is going to bring. a good alternative to a few google services is skiff. they provide a secure, e3ee mail service along with a workspace that can easily import google documents, a calendar and 10 gb free storage. i’ve been using it for a while and it’s great.

a good alternative to google drive is either koofr or filen. I use filen because everything you upload on there is end to end encrypted with zero knowledge. they offer 10 gb of free storage and really affordable lifetime plans.

google docs? i don’t know her. instead, try cryptpad. I don’t have the spoons to list all the great features of this service, you just have to believe me. nothing you write there will be used to train ai and you can share it just as easily. if skiff is too limited for you and you also need stuff like sheets or forms, cryptpad is here for you. the only downside i could think of is that they don’t have a mobile app, but the site works great in a browser too.

since there is no real alternative to youtube I recommend watching your little slime videos through a streaming frontend like freetube or new pipe. besides the fact that they remove ads, they also stop google from tracking what you watch. there is a bit of functionality loss with these services, but if you just want to watch videos privately they’re great.

if you’re looking for an alternative to google photos that is secure and end to end encrypted you might want to look into stingle, although in my experience filen’s photos tab works pretty well too.

oh, also, for the love of god, stop using whatsapp, facebook messenger or instagram for messaging. just stop. signal and telegram are literally here and they’re free. spread the word, educate your friends, ask them if they really want anyone to snoop around their private conversations.

regarding browser, you know the drill. throw google chrome/edge in the trash (they really basically spyware disguised as browsers) and download either librewolf or brave. mozilla can be a great secure option too, with a bit of tinkering.

if you wanna get a vpn (and I recommend you do) be wary that some of them are scammy. do your research, read their terms and conditions, familiarise yourself with their model. if you don’t wanna do that and are willing to trust my word, go with mullvad. they don’t keep any logs. it’s 5 euros a month with no different pricing plans or other bullshit.

lastly, whatever alternative you decide on, what matters most is that you don’t keep all your data in one place. don’t trust a service to take care of your emails, documents, photos and messages. store all these things in different, trustworthy (preferably open source) places. there is absolutely no reason google has to know everything about you.

do your own research as well, don’t just trust the first vpn service your favourite youtube gets sponsored by. don’t trust random tech blogs to tell you what the best cloud storage service is — they get good money for advertising one or the other. compare shit on your own or ask a tech savvy friend to help you. you’ve got this.

[violainebriat]

It's a bit weird typing out a full post here on tumblr. I used to be one of these artists that mostly focused on posting only images, the least amount of opinions/thoughts I could share, the better. Today, the art world online feels weird, not only because of AI, but also the algorithms on every platform and the general way our craft is getting replaced for close to 0 dollars. This website was a huge instrument in kickstarting my career as a professional artist, it was an inspiring place were artists shared their art and where we could make friends with anyone in the world, in any industries. It was pretty much the place that paved the way as a social media website outside of Facebook, where you could search art through tags etc. Anyhow, Tumblr still has a place in my heart even if all artists moved away from it after the infamous nsfw ban (mostly to Instagram and twitter). And now we're all playing a game of whack-a-mole trying to figure out if the social media platform we're using is going to sell their user content to AI / deep learning (looking at you reddit, going into stocks). On the Tumblr side, Matt Mullenweg's interviews and thoughts on the platform shows he's down to use AI, and I guess it could help create posts faster but then again, you have to click through multiple menus to protect your art (and writing) from being scraped. It's really kind of sad to have to be on the defensive with posting art/writing online. It doesn't even reflect my personal philosophy on sharing content. I've always been a bit of a "punk" thinking if people want to bootleg my work, it's like free advertisement and a testament to people liking what I created, so I've never really watermarked anything and posted fairly high-res version of my work. I don't even think my art is big enough to warrant the defensiveness of glazing/nightshading it, but the thought of it going through a program to be grinded into a data mush to be only excreted out as the ghost of its former self is honestly sort of deadening.

Finally, the most defeating trend is the quantity of nonsense and low-quality content that's being fed to the internet, made a million times easier with the use of AI. I truly feel like we're living what Neil Postman saw happening over 40 years ago in "amusing ourselves to death"(the brightness of this man's mind is still unrivaled in my eyes).

I guess this is my big rant to tell y'all now I'm gonna be posting crunchy art because Nightshade and Glaze basically make your crispy art look like a low-res JPEG, and I feel like an idiot for doing it but I'm considering it an act of low effort resistance against data scraping. If I can help "poison" data scrapping by wasting 5 minutes of my life to spit out a crunchy jpeg before posting, listen, it's not such a bad price to pay. Anyhow check out my new sticker coming to my secret shop really soon, and how he looks before and after getting glazed haha....

[tribow]

I don't get the discourse around supporting Tumblr.

Like if you give money to Tumblr you are supporting all of their bad decisions!!!

Okay, but then how do they keep the site alive? Ads? How many people are clicking on ads here? Tumblr hasn't been scraping every tiny piece of data they can get to sell it like Facebook does either. Should they start doing that? Or should they sell more ad space even though they're already known to be a site that isn't all the great for advertisers.

This is the only two routes I can think of for attempting to stay sustainable without the use of getting money directly from their users.

Someone's gotta pay to maintain this site and also pay all employees working to do so. This isn't a one man job you need a whole team for this. Tumblr costs quite a bit to maintain.

Is it wrong to pay for an online service you frequently use? I mean, let's imagine every Tumblr user magically unite to protest against all the changes to Tumblr they disagree with by making sure Tumblr gets no financial support. What would happen? Who is paying Tumblr's staff to listen to the demands of its community? Does anyone know how long that could take? Would that really save the site or would that send it straight to its doom?

To change topic a bit. Is financially supporting a company indicative of you agreeing with what they are doing? Is it not entirely possoble to critique a company in spite of your support? There's still things like review bombing and disrupting customer service. Besides, without being a paying customer you wouldn't have much of anything to threaten Tumblr with. If majority of the userbased was supporting with money it would be very scary for Tumblr if a ton of people really pulled out.

I....

I don't know it just seems to me that people want to protest to Tumblr staff by just....doing nothing and continueing to use Tumblr. What does that do??? Do YOU want to become the product??? Tumblr could axe Tumblr Live right now all of those people complaining wouldn't give Tumblr a dime for it. These devs are fairly communicative. They have several blogs dedicated to development, there's devs with their own blogs who respond to the community and even post surveys for suggestions to other staff, they did a Q&A in Tumblr Live (annoyingly), and have been fairly transparent in clearly communicating their plans while keeping it very open to criticism.

I can't really say that about many other companies. Tumblr staff gives its users SO MANY avenues to communicate. It's almost too open. The staff can get harassed very easily (I'm sure some do). Are the people complaining about this site not using these avenues to get staff's attention? I don't see how not giving them money will get their attention. If anything it would make them more desparate to get money from us through other means than something as inoffensive as merch.

This is a website that you are using. Is it wrong to compensate those maintaining/providing this service as you use it? If it is wrong, then what are the alternatives? Am I just stupid am I missing something?

[anniekoh]

elsewhere on the internet: AI and advertising

Bubble Trouble (about AIs trained on AI output and the impending model collapse) (Ed Zitron, Mar 2024)

A Wall Street Journal piece from this week has sounded the alarm that some believe AI models will run out of "high-quality text-based data" within the next two years in what an AI researcher called "a frontier research problem."  Modern AI models are trained by feeding them "publicly-available" text from the internet, scraped from billions of websites (everything from Wikipedia to Tumblr, to Reddit), which the model then uses to discern patterns and, in turn, answer questions based on the probability of an answer being correct. Theoretically, the more training data that these models receive, the more accurate their responses will be, or at least that's what the major AI companies would have you believe. Yet AI researcher Pablo Villalobos told the Journal that he believes that GPT-5 (OpenAI's next model) will require at least five times the training data of GPT-4. In layman's terms, these machines require tons of information to discern what the "right" answer to a prompt is, and "rightness" can only be derived from seeing lots of examples of what "right" looks like. ... One (very) funny idea posed by the Journal's piece is that AI companies are creating their own "synthetic" data to train their models, a "computer-science version of inbreeding" that Jathan Sadowski calls Habsburg AI.  This is, of course, a terrible idea. A research paper from last year found that feeding model-generated data to models creates "model collapse" — a "degenerative learning process where models start forgetting improbable events over time as the model becomes poisoned with its own projection of reality."

...

The AI boom has driven global stock markets to their best first quarter in 5 years, yet I fear that said boom is driven by a terrifyingly specious and unstable hype cycle. The companies benefitting from AI aren't the ones integrating it or even selling it, but those powering the means to use it — and while "demand" is allegedly up for cloud-based AI services, every major cloud provider is building out massive data center efforts to capture further demand for a technology yet to prove its necessity, all while saying that AI isn't actually contributing much revenue at all. Amazon is spending nearly $150 billion in the next 15 years on data centers to, and I quote Bloomberg, "handle an expected explosion in demand for artificial intelligence applications" as it tells its salespeople to temper their expectations of what AI can actually do.  I feel like a crazy person every time I read glossy pieces about AI "shaking up" industries only for the substance of the story to be "we use a coding copilot and our HR team uses it to generate emails." I feel like I'm going insane when I read about the billions of dollars being sunk into data centers, or another headline about how AI will change everything that is mostly made up of the reporter guessing what it could do.

They're Looting the Internet (Ed Zitron, Apr 2024)

An investigation from late last year found that a third of advertisements on Facebook Marketplace in the UK were scams, and earlier in the year UK financial services authorities said it had banned more than 10,000 illegal investment ads across Instagram, Facebook, YouTube and TikTok in 2022 — a 1,500% increase over the previous year. Last week, Meta revealed that Instagram made an astonishing $32.4 billion in advertising revenue in 2021. That figure becomes even more shocking when you consider Google's YouTube made $28.8 billion in the same period . Even the giants haven’t resisted the temptation to screw their users. CNN, one of the most influential news publications in the world, hosts both its own journalism and spammy content from "chum box" companies that make hundreds of millions of dollars driving clicks to everything from scams to outright disinformation. And you'll find them on CNN, NBC and other major news outlets, which by proxy endorse stories like "2 Steps To Tell When A Slot Is Close To Hitting The Jackpot."  These “chum box” companies are ubiquitous because they pay well, making them an attractive proposition for cash-strapped media entities that have seen their fortunes decline as print revenues evaporated. But they’re just so incredibly awful. In 2018, the (late, great) podcast Reply All had an episode that centered around a widower whose wife’s death had been hijacked by one of these chum box advertisers to push content that, using stolen family photos, heavily implied she had been unfaithful to him. The title of the episode — An Ad for the Worst Day of your Life — was fitting, and it was only until a massively popular podcast intervened did these networks ban the advert.  These networks are harmful to the user experience, and they’re arguably harmful to the news brands that host them. If I was working for a major news company, I’d be humiliated to see my work juxtaposed with specious celebrity bilge, diet scams, and get-rich-quick schemes.

...

While OpenAI, Google and Meta would like to claim that these are "publicly-available" works that they are "training on," the actual word for what they're doing is "stealing." These models are not "learning" or, let's be honest, "training" on this data, because that's not how they work — they're using mathematics to plagiarize it based on the likelihood that somebody else's answer is the correct one. If we did this as a human being — authoritatively quoting somebody else's figures without quoting them — this would be considered plagiarism, especially if we represented the information as our own. Generative AI allows you to generate lots of stuff from a prompt, allowing you to pretend to do the research much like LLMs pretend to know stuff. It's good for cheating at papers, or generating lots of mediocre stuff LLMs also tend to hallucinate, a virtually-unsolvable problem where they authoritatively make incorrect statements that creates horrifying results in generative art and renders them too unreliable for any kind of mission critical work. Like I’ve said previously, this is a feature, not a bug. These models don’t know anything — they’re guessing, based on mathematical calculations, as to the right answer. And that means they’ll present something that feels right, even though it has no basis in reality. LLMs are the poster child for Stephen Colbert’s concept of truthiness.

[mariacallous]

As few as 2 percent of New York City’s previous 22,000 short-term rentals on Airbnb have been registered with the city since a new law banning most listings came into effect in early September. But many illegal short-term rental listings are now being advertised on social media and lesser known platforms, with some still seemingly being listed on Airbnb itself.

The number of short-term listings on Airbnb has fallen by more than 80 percent, from 22,434 in August to just 3,227 by October 1, according to Inside Airbnb, a watchdog group that tracks the booking platform. But just 417 properties have been registered with the city, suggesting that very few of the city’s short-term rentals have been able to get permission to continue operating.

The crackdown in New York has created a “black market” for short-term rentals in the city, claims Lisa Grossman, a spokesperson for Restore Homeowner Autonomy and Rights (RHOAR), a local group that opposed the law. Grossman says she’s seen the short-term rental market pick up steam on places like Facebook since the ban. “People are going underground,” she says.

New York’s crackdown on short-term rentals has dramatically reshaped the vacation rental market in the city. People are using sites like Craigslist, Facebook, Houfy, and others, where they can search for guests or places to book without the checks and balances of booking platforms like Airbnb. Hotel prices are expected to rise with more demand.

Search for a short stay on Airbnb, and there are few places scattered across the map. Many of those old listings have turned into stays of 30 days or longer—meaning they do not need to be registered.

AirDNA, a short-term rental intelligence firm, found just 2,300 short-term rentals on Airbnb in New York City by late September. The number of stays advertised as long-term rentals now makes up 94 percent of Airbnb’s listings in the city, AirDNA’s data shows. Hosts must meet strict requirements to be approved as a short-term rental—they can have only two guests, and the host must be present in the home during the stay. This change banned many whole apartment listings, except for those that fell under a Class B dwelling category, like hotels, boarding houses, and clubs.

But people are finding ways around the rules. Many listings on Airbnb now include a space in the property’s description for hosts to enter a registration number or state that they are exempt. WIRED searched Airbnb for stays in New York and found many short-term rentals that list themselves as exempt from the city’s registration rules, but there are still several entire units available for short stays that do not appear to be hotels or exempt units.

In one listing marked as exempt, the host asks for guests to avoid interacting with the building’s concierge. On another listing, a host claims they used to live in the unit but have moved to New Jersey and now rent it out. One appears to be a rowhome in a mostly residential neighborhood in Brooklyn. Airbnb uses the city’s verification system to flag unregistered units. The company did not provide comment for this story addressing these specific listings flagged by WIRED. Nathan Rotman, the public policy regional lead for Airbnb, says the company is “working closely” with the city as it implements the new registration law.

Inside Airbnb’s data shows some 2,300 short-term properties have listed themselves as exempt from registration on Airbnb. There are a few hundred more that do not say whether they are exempt or registered, according to the data. Another 35,000 are long-term rentals. Airbnb did not confirm the numbers in the data scraped by Inside Airbnb. The Mayor's Office of Special Enforcement in New York, which manages the registration program, did not provide an update on the total number of short-term rentals it has registered, or whether it has issued violations for illegal listings. 

The New York City law is just one striking way cities are fighting back against short-term rentals. Supporters of the rule argued it would free up apartments for New Yorkers, who pay high rent prices and are facing housing shortages and insecurity. But others, including small-time landlords, said it would take away a source of flexible extra income without making a dent in the housing supply crisis.

Those smaller landlords are still pushing New York City councilors to change the rules to allow them to rent out their units. RHOAR is made up of hosts who own and occupy single-family homes or homes with two dwelling units. These hosts feel they have been unfairly looped in with big landlords. Grossman says RHOAR has met with city councilors in hopes of changing the law so that smaller hosts can still legally do short-term renting.

Outside of Airbnb, people are posting listings and seeking short-term rentals in Facebook groups. Ads on Craigslist for rentals have weekly or nightly prices listed—WIRED found one listing with a weekly and nightly price on Craigslist that also appears on Airbnb, but can only be booked for 30 days or longer on Airbnb. These off-platform rentals pose risks to both guests and hosts, who could get scammed without the protections of bigger companies like Airbnb. 

Craigslist did not respond to a request for comment. Meta, Facebook's parent company, did not comment on specific listings flagged by WIRED, but the company's policies require buyers and sellers in Facebook Marketplace to comply with local laws, and the company prohibits people from promoting illegal activity in Facebook pages and groups.  

Then there’s Houfy, another website listing short-term rentals. WIRED found that many of the listings come from guests who joined the site in September, the same month New York’s new registration rules took effect. The intention is for guests to book directly with hosts—think Airbnb without the fees. The site compares prices for the same property on Airbnb and Houfy and claims to show how much people can save by avoiding Airbnb’s fees.

Houfy has received a notice from New York City about the new rule and is “reviewing how to comply with their rules,” Thijs Aaftink, CEO of Houfy, tells WIRED. Aaftink says Houfy, unlike Airbnb and other rental sites, does not take commissions on transactions between hosts and guests, and argues the company “is therefore not part of the transaction.” He says hosts are responsible for complying with local laws when listing properties.

After the rule change, Airbnb is shifting attention away from New York, which was once its biggest market. Airbnb CEO Brian Chesky has recently said the company is exploring longer rentals, as well as car rentals and dining pop-ups. And it has got its eyes on Paris, its largest market and home to the 2024 Summer Olympics.

“I was always hopeful that New York City would lead the way—that we would find a solution in New York, and people would say, ‘If they can make it in New York, they can make it anywhere,’” Chesky said during an event in September hosted by Skift, a travel industry news site. “I think, unfortunately, New York is no longer leading the way—it’s probably a cautionary tale.”

[tangibletechnomancy]

What frustrates me about The Discourse about AI art is that everyone feels the need to have An Opinion...and no one is willing to look into the conversations that have been going on for DECADES surrounding the relevant issues, or the cases that set precedent for what we can do here going back CENTURIES.

Let me lay out two very important things here:

The dataset ethics issue is more of an issue of digital privacy than copyright.

The labor issue has been seen MANY times throughout history; we can look to MANY other times new tech has shaken up a job market for precedent before AI even STARTS being used on large commercial projects.

Point #1 is true because, I have said before and I will say again, image synthesis is not collaging. It is not copy-pasting. It does not composite images in the dataset. It doesn't even save the images. It looks for patterns in the pixels and tries to recreate similar patterns from random or semi-random noise. This is why it often sucks at anatomy without human guidance - it recognizes that the word "hair" usually corresponds to a pattern that usually goes near a pattern that corresponds to a "head", it recognizes that "hands" usually have a certain pattern of repeating light and shadows, but it doesn't understand the intricacies of where those things belong or how many times a pattern might repeat. This is why images of architecture often have impossible geometry - it understands the shapes that these things tend to take; it doesn't understand the logic of what connects to what. People can use it to plagiarize - they can, intentionally or otherwise, force a result that is overfitted to a specific piece of data in the set - but to say that's ALL it does is comparable to the asinine claim that ALL referencing is plagiarism, because SOME people will just straight up trace or recreate a full piece that already exists, sometimes even by accident. (And some people - not all, not even most, but some who claim plagiarism, whether from AI or traditional art, are just...really? Do you really think you are the only person who has ever drawn, say, a pink fairy sitting under a purple luminescent mushroom, gazing at a full moon in the upper left, composed with the 1/3s rule? Do you really?)

And the thing is, I agree that the kind of broad data scrapes that have been used to create most AI models should be reserved solely for scientific curiosity if they're used at all, and I respect anyone who doesn't want to touch image synthesis until that issue is resolved. The only reason it doesn't bother me too much to play with it myself is that...unfortunately, we're all interacting with much worse as we speak. Ever heard the word "spyware?" If you're old enough to know it, notice how you stopped hearing it when Facebook normalized making literally the majority of the internet into spyware?

You can't really use the internet while wholly blocking Google, and their evils are pretty well documented. (Remember when we rolled our eyes at their internal "don't be evil" slogan? And how deeply unsettling it was to then watch them REMOVE that while ramping up aggressive datamining?) Amazon made Alexa to harvest your data to sell you shit more effectively. If you have a smartphone, Google or Apple or both are harvesting your data for all kinds of much more malicious purposes than making pretty pictures. Twitter uses your tweets and browsing patterns to force you to interact with people you will hate because negative emotions hold your attention better than positive ones and they want that sweet sweet advertiser money from your constant engagement; this was the case even long before Elongated Muskrat took over. Spotify Wrapped and knockoffs thereof are ~fun tools~ that...normalize just handing data about some pretty personal things over to anyone who dangles a shiny novelty in front of you made with it. It's used for invasive surveillance and policing, and Facebook's for-profit datamining even ended up being a tool of election interference - had it not been for them we might not be in nearly such a bad state with the rise of global fascism.

Image synthesis is one of the most harmless and even potentially BENEFICIAL things to be created as a result of this disturbing norm.

The fact is, small artists: copyright law may protect you a little, sometimes, but it wasn't made for us (and yes, I say "us", because even if you don't count my partially AI work as art, I do traditional art too, guys). It was made for Disney and their ilk. It is designed to protect corporate interests, not artistic ones. That notwithstanding, the copyright angle is a weak one in the first place - it's easy to argue that, because the process is transformative enough, and the dataset is large enough and abstracted enough from anything it was derived from, AI training on online art would fall under fair use, and it is only individual misuses that would constitute infringement. It's especially easy to argue this when you recognize that, at this point, that's more where the corporate interest lies, and remember who the laws are made for!

Digital privacy, on the other hand? The right to your own data? The right to be forgotten? The need to have regulations on where robots can and cannot crawl, and for what purposes? THAT is a critical conversation that we need to be having here, and if everyone with An Opinion on AI art focused their energy there instead of mostly just misinformed screaming about the sky falling and Art Dying And Society Degrading (which is HORRIFYING to hear from leftists in knowing its history as a fascist talking point), we could probably get some MAJOR good done.

Furthermore, even if someone ruled that AI training doesn't constitute fair use under copyright law, that won't stop big companies from using AI - Disney has PLENTY of frames of animation to feed a model to make something entirely their own. So do most animation studios. I have even been in talks with people trying to work on a 100% public domain AI model - the biggest concern about it is that if we complete and finalize it before the labor side of the issue is being worked around properly, it will EMBOLDEN unethical use in industry by getting rid of the potential legal complications.

So let's talk about the labor side and recognize - this isn't the first time new tech has threatened to make major changes to the way something is done in industry, potentially resulting in workforce downsizing. It won't be the last. Honestly, as a person who's been both machining and doing mixed media art since I was a kid (and sometimes both at the same time), I find it deeply disheartening how many people have not cared about this side of the issue until it was certain art jobs that might get automated...and even more frustrating how people refuse to look to past cases for how the harms of new tech shaking up employment have been mitigated.

What we could and should be fighting for is a government program to compensate and optionally retrain employees who were laid off due to automation (ANY automation, not just in art!!), as well as independent workers who see a drop in income due to increased market saturation. We can do this. We've done it before.

We could and should also be fighting for UBI - this will be harder, but it's more popular now than it ever has been and some places are even TESTING it while the internet watches; it is not nearly as much of a pipe dream as it once was.

What's NOT going to help anyone is devaluing the labor of new automation tech operators - that INCENTIVIZES the corporations to adopt it FASTER where possible, and treat both new and existing employees WORSE. "I could replace you with a robot; you're employed out of the goodness of my heart" is one of the most common justifications for abusing and underpaying employees in relevant positions. Big media companies already rely on crunch at poverty wages; they're only going to get worse about it with AI tech because "oh you're just pushing buttons, what do you mean you can't do that for 20 hours at barely minimum wage, how lazy can you get?" if we continue this line of thinking. However, if we recommend and enable new automation operators - in all industries - to UNIONIZE before their work and thus their mistreatment even starts, it will make the transition a hell of a lot easier on both new and existing workers.

Tl;dr: It's great that we have a lot of people concerned about artists' labor rights and tech transparency now PLEASE LEARN YOUR HISTORY AND DIRECT YOUR ENERGY WHERE IT IS NEEDED INSTEAD OF ASSUMING YOU KNOW EVERYTHING FROM A FEW SENSATIONALIZED ARTICLES I BEG OF YOU

[songofsaraneth]

i'll be honest i do not trust any up&coming social media site that claims it will be free to use and also not sell your data and also have zero ads. WHERE are you getting money then? like sure you can rely on donations for sustainability for like... a couple years at best probably, if you're aiming to wildly increase growth/number of users. donation based works ok for small highly invested communities or for online repositories of data (wikipedia, ao3). but like facebook/instagram/tiktok are profitable becuase they harvest data and use ads. tumblr is BARELY scraping by because it only relies on ads. if you take away even that, as soon as you have enough users to surpass the limits of free hosting, you're operating at a deficit.

like not writing this to say don't give it a shot, sincerely wish them good luck and hope they figure it out, it's hard! but also i just don't consider those kinds of websites/communities a reliable "backup" plan compared to tumblr itself which has kept chugging along for years despite Everything. it's a shiny new social media but it is weird to profess that a social media site advertising NO revenue streams will last longer than this one here.

[datascraping001]

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Car Dealership Email Lists

Contact information for car dealerships across the country is available in Car Dealership Email Lists. The search engine gives you a Car Dealership Email Lists - Car Dealership Mailing Lists of all car dealerships, or you can filter by 'new' or 'used' dealers. You can search by States, Counties, Cities and Zip Codes, and search by 100's of demographics, such as employee size and annual sales volume. Car Dealership Email Lists - Car Dealership Mailing Lists in USA, UK, Canada, Australia, Germany, France, UAE and Europe.

Data Scraping Services strives to deliver an outstanding Car Dealership Email Lists - Car Dealership Mailing Lists for its customers. You will be able to target automobile dealers, automobile manufacturing and auto retail sector through our Car Dealership Email Lists - Car Dealership Mailing Lists. Our Car Dealership Database offers accurate, real-time access to a national database of potential auto dealers and car dealers. This document includes names, physical addresses, phone numbers, e- mail addresses, revenue information, license details, etc. Everything you need to know is included within this comprehensive Car Dealership Email Lists. With an accurate Car Dealership Email Lists - Car Dealership Mailing Lists of potential customers, you can channel your marketing efforts on your targeted audience easily and with a greater incidence of success.

What Are The Benefits Of Buying A Car Dealership Email Lists?

With 8% growth in vehicle sales in 2022, there has been a 14.3% increase from the previous year. Our Car Dealership Email Lists - Car Dealership Mailing Lists can give you the edge you need to stay ahead of the competition. Our Car Dealership Email Lists - Car Dealership Mailing Lists can help you find new customers quickly and boost sales if you provide your products or services to car dealerships or plan on getting into business with them.

Do You Want To Advertise To Vehicle Owners In Your Area?

We have Car Dealership Email Lists - Car Dealership Mailing Lists of specific types of vehicle owners who live near the dealership, so you can mail them promotions and advertisements. With our service, you don't have to spend hours searching for new leads on the Internet or in white pages directories; we've done the work for you! Get in touch with top decision makers at Car Dealers using our high- quality, current contact information. 90+% of our Car Dealership Email Lists - Car Dealership Mailing Lists are accurate. Our prices are extremely competitive and we have low minimums. There is one email address per location in the Car Dealership Email Lists - Car Dealership Mailing Lists.  

Top-Performing Industry Mailing Lists

Tattoo Parlors Email List

Tanning Salons Email List

Bowling Centers Email List

Beauty Schools Email List

Sporting Goods Email List

Photographers Email List

Mortgage Consultants Email List

Audiologist Mailing List

Facebook Data Scraping

Wineries Email List

Architect Email List Scraping

Scraping Plumbers Email List

Switzerland B2B Database Provider

Keywords

Car Dealership Email Lists

Car Dealership Mailing Lists

Auto Dealer Email List

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Auto Dealer Database

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Used Car Dealer Email List

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Mesa, Phoenix, Bakersfield, Seattle, Wichita, Memphis, Portland, Long Beach, Jacksonville, Tucson, Washington, Houston, Detroit, Oklahoma City, San Jose, Columbus, Denver, Kansas City, El Paso, Honolulu, San Francisco, Las Vegas, Raleigh Fresno, Austin, Boston, Sacramento, Nashville, Omaha, New York, Tulsa, Arlington, Miami, Milwaukee, Virginia Beach, New Orleans, Colorado Springs, Chicago, Dallas, Orlando, Fort Worth, Charlotte, Atlanta, San Antonio, Baltimore, Albuquerque, San Diego, Los Angeles, Philadelphia, Indianapolis and Louisville.

If you are looking for Car Dealership Email Lists - Car Dealership Mailing Lists then drop us an email at info@datascrapingservices.com.

[realdataapi1]

Facebook Ads Data Scraper | Scrape Facebook Advertising Data

RealdataAPI / facebook-ads-scraper

Easily Scrape advertising data from one or multiple Facebook Pages with the Facebook Ads Data Scraper. Obtain page details, reach estimates, publisher platforms, report count, number of impressions, ad IDs, timestamps, and other helpful information. The data can be downloaded in JSON, CSV, and Excel formats for use in various applications, spreadsheets, and reports. This tool is available in several countries, including Australia, Canada, Germany, France, Singapore, the USA, the UK, the UAE, and India.

 Customize me!  Report an issue Business E-commerce Social Media

Readme

API

Input

Related actors

What is Facebook Ads Data Extractor?

It Is A Powerful And Straightforward Actor That Allows You To Extract Facebook Ads Data Like Reach Estimates, Page Information, Publisher Platform, Report Analytics, And More. To Collect That Data, Place The Page Link And Click On The Save And Start Option.

Why extract Facebook ads data?

It Will Help You In Market Research, Trend Monitoring, Competitor Intelligence, Social Media Study, Brand Sentiment, Etc.

How to use Facebook Ads Scraper?

We've Designed This Scraper To Collect Facebook Ads Data To Quickly Start The Process Even If You Are Beginning To Scrape The Data. Here Is The Process To Scrape Information Using This API.

Create a free Real Data API account with your email.

Open Facebook ads data scraper on our platform.

Place multiple URLs of Facebook pages to scrape ad data.

Click the Start button and allow some time for the scraper to get you the required data.

Export the data in any usable format of your choice.

Note That This Actor Shows The Scraped Outputs Only At The End Of Execution. While Running, The Scraper Won't Update Outputs. You Can Allow The Scraper To Finish The Execution To See The Output.

Input

It Would Help If You Fed The Input To This Scraper As Below.

URL of the page like https://www.facebook.com/drive4quantix/

Or the URL of the advertisement, like https://www.facebook.com/ads/library/?active_status=all&ad_type=all&coun try=ALL&q=%7B%7D&sort_data[direction]=desc&sort_data[mode]=relevan cy_monthly_grouped&start_date[min]=2022-10- 12&start_date[max]=&search_type=keyword_unordered&media_type=vid You can get a longer URL in the ads library of Facebook. Before pasting the link, mention filters, settings, and amounts per page.

Keep in mind that zero scrolls reflect the first few ad sets. Every scroll can deliver 30 advertisements. Facebook restricted the maximum number of ads shown per page, so you may not see all the ads.

Open The Input Tab To See The JSON Example.{ "StartUrls": [ { "Url": "Https://Www.Facebook.Com/AndrejBabis" } ], "ScrollsAmount": 4 }

Output

Note: You'll See The Start And End Dates Below In The ISO Value Format. StartDateFormatted: "2022-10-12T07:00:00.000Z" And EndDateFormatted: "2022- 10-12T07:00:00.000Z".

What is the cost of using a Facebook Ads scraper?

Suppose You Use This Scraper On The Real Data API Platform For Result-Oriented Facebook Data Extraction. In That Case, You Need Residential Proxy Servers In The Monthly Personal Plan Of Real Data API, Which Is Around 50 USD Per Month.

To Know More About How We Offer Pricing, Proxies And Usages, And Platform Credits, Check The Pricing Page On Our Platform.

Do you want to collect Facebook groups or comments data?

If You Want To Collect Detailed Facebook Data, We've Dedicated A Scraper For Them Below.

Facebook Groups Scraper

Facebook Reviews Scraper

Facebook Comments Scraper

Facebook Photos Scraper

Facebook Ads scraper with Integrations

Lastly, You Can Connect This Actor With Any Web Application Or Cloud Service With Real Data API Integrations. You Can Connect With Slack, Zapier, GitHub, Make, Google Drives, Airbyte, Google Drive, Etc.

You Can Also Use Webhooks To Commence The Action At The Time Of The Event, Like Getting An Alert In The Successful Execution Of This API.

Using Facebook Ads Scraper with the Real Data API

The Real Data API Allows You To Access Actors Programmatically. It Also Allows You To Use Datasets, Track API Performances, Generate Results, Update And Develop Versions, Etc. To Use The Actor In Python, Use Our Client PyPl Package, And To Use In Node.Js, Use Our Client NPM Package.

See The Real Data API Actor Reference Document For Details, Or Open The API Tab For Codes.

Can I extract Facebook Ads data legally?

We Follow All The Rules And Regulations To Maintain Ethics And Don't Scrape Any Private Data Like Location, Gender, Or Email Ids Of Personal Accounts. But The Scraped Data May Contain Some Personal Information Unintentionally, So Be Aware And Don't Scrape Any Personal Data Without Genuine Reason.

You Can Consult Advocates If You Are Confused About Whether Your Reason Is Legal

[raddagher]

Things my Firefox Plugins Do:

spam advertisers while blocking their ads to waste their money (privacy possum)

gives trackers false data instead of my actual data (ad nauseum)

auto-select the lowest number of cookies possible to still run pages (ghostery)

skip ads on youtube (ublock origin)

skip sponsored sections in actual youtube videos (sponsorblock)

block facebook trackers (facebook container)

blocks (some) Google conversion links that contribute to Google's data scraping (don't track me google)

encrypts every webpage I use (https everywhere)

download firefox

download firefox

[iwebdatascrape]

Role of Meta Ads Scraping Services in AI-Driven Advertising Campaigns

What Role Do Meta Ads Data Scraping Services Play in AI-Driven Advertising Campaigns?

In the ever-evolving digital marketing landscape, the key to driving successful advertising campaigns lies in understanding what works and why. With the vast amount of ads flooding the internet daily, gaining insights into high-performing advertisements can be the differentiator for brands looking to maximize their return on ad spend (ROAS). One valuable resource for marketers in this pursuit is the Meta Ads Data Scraping Services, a publicly accessible database containing a wealth of information about ads running across Meta platforms, including Facebook and Instagram.

This article will delve into the significance of Meta ad campaign Data Collection, how these insights can enhance AI-driven marketing strategies, and how brands can leverage high- performing ads to fuel their campaigns. By extracting valuable data from this resource, advertisers can harness the power of artificial intelligence to supercharge their marketing efforts and maintain a competitive edge.

The Meta Ads Library: A Treasure Trove of Advertising Insights

Meta introduced the Ads Library in response to growing demands for greater transparency in digital advertising. This tool allows users to explore various active ads on its platforms. This promotes ethical advertising practices and offers marketers valuable insights into their competitors' strategies. Covering diverse ad formats, industries, and regions, the library is an indispensable resource for businesses looking to refine their campaigns.

While marketers can manually browse the library to analyze active ads, observe trends, and assess creative formats, the process can be time-consuming. A more efficient way to tap into this data is by using a Facebook Ads Library Scraper to collect data automatically, unlocking deeper insights faster.

Why Scrape the Meta Ads Library?

Web scraping refers to the automated extraction of data from websites. In the case of the Meta Ads Library, this means collecting and analyzing large volumes of data about ads in a structured and meaningful way. But why is web scraping necessary?

1. Scaling Insights: Manually examining individual ads in the Meta Ads Library can be time-consuming and inefficient, mainly when dealing with thousands of ads. Web Scraping Facebook Data enables marketers to collect and analyze data at scale, generating actionable insights more quickly.

2. Competitive Benchmarking: One of the most effective uses of the Meta Ads Library is competitive benchmarking. Scrape Facebook ads data to help brands track trends over time, compare their performance, and learn from high-performing ads in their industry.

3. Ad Trend Analysis: Tracking ad trends is essential for staying relevant. Web scraping allows marketers to gather data on ad copy, design elements, calls to action (CTAs), and target demographics, helping them to identify which elements drive higher engagement and conversions. This process also helps to extract Facebook Ads performance metrics that inform future campaigns.

4. AI-Driven Personalization: Artificial intelligence thrives on data. By scraping large volumes of ad data, brands can feed their AI algorithms to create personalized ad experiences. AI can analyze patterns, extract insights, and predict the success of different ad variations, ultimately enhancing social media data collection efforts to create more relevant and engaging campaigns.

Uncovering High-Performing Ads with Web Scraping

The value of web scraping the Meta Ads Library becomes even more apparent when brands focus on identifying high-performing ads. But what constitutes a high-performing ad? While the answer varies based on campaign goals, specific metrics and attributes can explain an ad's effectiveness. Here's how web scraping can help marketers unlock high-performing ads:

1. Engagement Metrics: Social media data scraper can pull data on engagement metrics such as likes, shares, comments, and clicks. By analyzing this information, marketers can identify ads that generate the most audience interaction and engagement. Ads with high engagement are often considered more successful as they resonate with viewers.

2. Ad Duration: High-performing ads often run for longer periods. By scraping data on how long specific ads remain active, marketers can determine which ads sustain performance and may warrant further investigation.

3. Ad Creatives and Copy: One of the Meta Ads Library's most significant advantages is the ability to view competitors' ad creatives and copy. By scraping these elements, marketers can identify common themes among successful ads, including the type of visuals used, the tone of the messaging, and the use of attention-grabbing headlines or CTAs. This process can be streamlined using social media data scraping APIs, enabling quicker access for deeper analysis.

4. Target Audience Insights: Another powerful feature of the Meta Ads Library is its transparency around targeting information. Brands can scrape data on audience demographics, locations, and interests, helping them understand how their competitors target their ads. The social media datasets can then be used to optimize their targeting strategies.

5. Campaign Objectives: Web scraping can also help brands categorize ads based on their campaign objectives, such as brand awareness, lead generation, or conversions. By understanding which ads achieve specific objectives, marketers can tailor their strategies to align with their goals.

Leveraging Meta Ads Library for AI-Driven Campaign Optimization

The future of digital marketing lies in leveraging AI to optimize campaigns, and the data from the Meta Ads Library can be a goldmine for AI-driven solutions. Once high-performing ads are identified through web scraping, AI can take those insights to the next level by making data-driven decisions and enhancing campaign performance. Here's how:

1. Predictive Analytics

AI-powered algorithms can analyze the vast amount of ad data from the Meta Ads Library to predict future trends. By identifying patterns in the data, AI can forecast which ad creatives, formats, and targeting strategies are most likely to succeed. Predictive analytics helps marketers stay ahead, optimizing their campaigns to anticipate customer behavior and drive better results.

2. Personalized Ad Creation

AI excels in personalization, and the data collected through web scraping provides the foundation for hyper-personalized campaigns. AI can create tailored ad experiences that resonate with individual users by analyzing audience demographics, interests, and behaviors. This level of personalization causes higher engagement rates and better conversions, as users tend to respond to ads that speak directly to their needs and preferences.

3. A/B Testing at Scale

Web scraping the Meta Ads Library allows brands to analyze various ad variations, providing the data needed for large-scale A/B testing. AI can take this process a step further by automating A/B testing, running multiple versions of an ad simultaneously, and determining the best-performing variation in real time. This enables marketers to refine their ads for optimal performance continuously.

4. Ad Spend Optimization

AI can also help optimize ad spend by analyzing the performance of ads scraped from the Meta Ads Library. By comparing the cost-per-click (CPC), cost-per-impression (CPM), and return on ad spend (ROAS) of various ads, AI can allocate budget more efficiently, ensuring that marketers get the most value out of their advertising investments.

5. Real-Time Ad Adjustments

One of the most powerful applications of AI in advertising is the ability to make real-time adjustments to campaigns. By continuously analyzing the data collected from web scraping, AI can monitor ads' performance and make real-time adjustments, such as changing targeting parameters, tweaking ad copy, or adjusting the budget. This ensures that campaigns remain optimized and responsive to changes in audience behavior.

Ethical Considerations and Compliance

While web scraping offers significant benefits for marketers, it is essential to approach it ethically and within the bounds of legal compliance. Meta has clear policies around data usage and scraping, and marketers must ensure that their web scraping activities comply with these guidelines. Failure to do so can result in penalties or account suspensions.

Additionally, web scraping should not infringe on user privacy or violate data protection regulations like the General Data Protection Regulation (GDPR). Marketers must ensure that the data they collect is used responsibly and in a way that respects user rights.

The Future of AI-Driven Campaigns

As digital marketing evolves, AI-driven campaigns will become essential for staying competitive. The ability to scrape and analyze data from the Meta Ads Library gives marketers a wealth of insights to fuel their AI-powered strategies. By unlocking the secrets of high-performing ads, brands can create more personalized, efficient, and effective campaigns.

In the future, we expect AI to play an even more significant role in the advertising landscape. From automated content creation to dynamic ad targeting, AI will enable marketers to deliver highly relevant and engaging ads to their audiences at scale. The data scraped from the Meta Ads Library will serve as the foundation for these innovations, providing the raw material needed to train AI algorithms and optimize campaigns.

Conclusion

Web scraping the Meta Ads Library unlocks a world of possibilities for marketers looking to optimize their campaigns and drive better results. By extracting and analyzing valuable data on high-performing ads, brands can gain a competitive edge and fuel their AI-driven strategies. Whether through predictive analytics, personalized ad creation, or real-time campaign adjustments, the combination of web scraping and AI presents a powerful opportunity for marketers to succeed in digital advertising.

As we move forward, integrating AI and data-driven insights will be the key to unlocking advertising's full potential. By staying ahead of trends, leveraging high-performing ads, and embracing AI-powered solutions, brands can ensure that their campaigns remain at the cutting edge of digital marketing innovation.

Experience top-notch web scraping service and mobile app scraping solutions with iWeb Data Scraping. Our skilled team excels in extracting various data sets, including retail store locations and beyond. Connect with us today to learn how our customized services can address your unique project needs, delivering the highest efficiency and dependability for all your data requirements.

Source: https://www.iwebdatascraping.com/role-of-meta-ads-scraping-services-in-ai-driven-advertising-campaigns.php

[proxiware]

Understanding Static Residential Proxies: A Comprehensive Guide

In today’s digital age, online privacy and security have become paramount for businesses and individuals alike. One effective tool for enhancing online anonymity and bypassing restrictions is the use of static residential proxies. Static Residential Proxies This article will explore what static residential proxies are, their benefits, and how they can be effectively utilized.

What Are Static Residential Proxies?

Static residential proxies are IP addresses assigned to physical locations by Internet Service Providers (ISPs). Unlike dynamic proxies, which change frequently, static proxies maintain the same IP address over time. This stability allows users to establish a consistent online presence, making it ideal for various applications such as web scraping, social media management, and ad verification.

Benefits of Using Static Residential Proxies

Enhanced Privacy and Anonymity

Static residential proxies help mask your actual IP address, making it difficult for websites to track your online activities. This is particularly beneficial for businesses conducting market research or for individuals accessing geo-restricted content.

Improved Access to Geo-Restricted Content

Many online services restrict content based on geographical location. By using a static residential proxy, you can appear as though you are browsing from a different region, allowing access to exclusive content and services.

Consistent Performance

Since static residential proxies provide the same IP address, users experience fewer disruptions and connection issues. This consistency is essential for tasks that require a stable connection, such as managing multiple social media accounts or performing extensive data scraping.

Lower Ban Rates

Websites are less likely to flag or ban static residential proxies compared to datacenter proxies. This is because residential proxies appear to originate from real users rather than bots, making them a safer choice for web scraping and automated tasks.

Use Cases for Static Residential Proxies

Web Scraping: Businesses often use static residential proxies to gather data from various websites without getting blocked. The consistent IP addresses help maintain a low profile during scraping activities.

Ad Verification: Marketers can use these proxies to ensure their advertisements are displayed correctly across different locations and platforms, verifying the effectiveness of their campaigns.

Account Management: For individuals managing multiple accounts on platforms like Instagram or Facebook, static residential proxies provide a safe way to access and operate these accounts without risking bans.

Market Research: Companies can leverage static residential proxies to monitor competitors, gather pricing information, and conduct market analysis while remaining anonymous.

Conclusion

Static residential proxies are a powerful tool for enhancing online privacy, accessing geo-restricted content, Static Residential Proxies and ensuring consistent performance across various online activities. Whether you're a business looking to improve your web scraping efforts or an individual seeking greater anonymity, investing in static residential proxies can provide significant advantages.

For those interested in exploring static residential proxies further, Proxiware offers reliable ISP proxies tailored to meet your needs. Visit Proxiware ISP Proxy to learn more about how these proxies can benefit you.

[711proxy]

Proxy IP's main use of people, you belong to which category?

Proxy IP has become a common tool in Internet operations, especially in the context of today's information technology globalization, proxy IP application scenarios are more and more extensive. So, which groups of people use proxy IP most often?

1. Data Scraping and Web Crawling Engineers

Data crawling and web crawling are the most common applications of proxy IP. Crawler engineers can bypass the anti-crawler mechanism of websites through proxy IP, and collect data from websites in a large scale and efficiently. The switching function of proxy IP can help crawlers to perform large-scale data crawling without exposing themselves, and avoid being blocked due to frequent visits to the same IP. For enterprises or individuals engaged in market research and competitive analysis, proxy IP is undoubtedly a powerful tool.

2. Cross-border e-commerce and foreign trade practitioners

Cross-border e-commerce and foreign trade practitioners are also heavy users of proxy IP. In cross-border e-commerce operations, merchants need to frequently log in to e-commerce platforms in different countries, such as Amazon, eBay, etc., and monitor market trends in multiple countries at the same time. By using residential proxies, they can easily switch to the IP address of the target country for accurate localization and avoid account risks caused by mismatched IP addresses.

3. Overseas Ad Placement and Promoters

When making overseas advertisement placement, proxy IP can help advertising practitioners operate their accounts more flexibly, manage ad campaigns, and conduct data monitoring. Especially when advertising globally on Facebook, Google Ads and other platforms, proxy IP can solve the problems of regional restrictions and IP blocking to ensure the safety and smooth operation of advertising accounts.

4. Social media operators

Social media operators, especially those engaged in account management, usually need to operate multiple accounts at the same time. While social platforms have strict restrictions on logging into multiple accounts with the same IP, the use of proxy IPs can effectively circumvent such restrictions. Especially on social platforms such as Facebook, Instagram, Twitter, etc., proxy IPs can help with multi-account operations, maintain IP diversity, and reduce the risk of account blocking.

5. Gamers and proxy trainers

Proxy IPs are also crucial for certain international gamers or surrogates. As the servers of some games are distributed all over the world and the network latency is high in certain regions, proxy IP can help gamers optimize their network connection and improve their gaming experience. At the same time, by switching IP addresses of different countries, gamers can also unlock game content in specific regions and enjoy more gaming fun.

6. Security and Privacy Protection Users

Some users attach great importance to network privacy and security, and they hide their real IP address through proxy IP to avoid being attacked or monitored by the network. Most of these users are engaged in network security or have strong awareness of personal information protection, proxy IP can effectively enhance their privacy and security.

Proxy IP is used by a wide range of people, and everyone can use proxy IP to improve the efficiency and security of their work and entertainment. If you also need the support of proxy IP, 711Proxy provides efficient and secure global proxy services to help you easily cope with all kinds of network needs!

[chipped-chimera]

THIS. DEAR LORD THIS. THIS IS WHAT HAS BEEN DRIVING ME INSANE ABOUT AI.

Look I have contemplated writing an AI Analysis post coming from an actual artist's perspective SEVERAL times with the knowledge I've accumulated but rarely have the spoons to do it but I'll just do a short bit of it now.

So when something really upsets me that is happening and I have little control, I habitually do this thing where I will actively go out there and research the shit out of it. Because I've spent enough time in therapy to know the thing that scares us the most is the unknown. Make the unknown known? It becomes significantly less scary.

And I am backing it up when they say 'AI is a buzzword'. It 120% is. What the AI labelling is hiding under the world's biggest and perhaps most obfuscated umbrella-term is machine learning.

So it would probably shock you to know, by that metric we have been using AI for YEARS. Your autocomplete keyboard on your phone that remembers your words according to usage? Machine learning. Facial recognition on mobile phone cameras and facebook? Machine learning. The ALGORITHMS that have been driving a lot of my most beloathed social medias for years? MACHINE. LEARNING. Auto-generated captions on videos, reverse image searching, targeted advertising, analysis of weather systems, handwriting recognition, DNA sequencing, search engines, and of course your dynamic enemy 'AI' in videogames that has to react to your actions as a player - these are ALL products of machine learning and by that metric? You have technically been using AI for years but we just didn't call it that yet.

In my great search of understanding all things AI, what an Australian tech journalist commentator said was - we're basically calling anything 'new' in machine learning that we don't quite understand yet collectively 'AI'. And I agree 100%. The reality is AI has been with us since about the 1960s.

Hang on Chimera/Kery I hear you say, on the Wikipedia page of machine learning it says machine learning is a result of trying to build AI, not AI! Yes, but you literally cannot have the 'Intelligence' part without the machine learning part. You take out the learning and you've just got a brick of data that you can't do shit with. The intelligence part comes in when based on the data it's been fed and the responses it has gotten back from it's environment, whether that is a researcher saying yes or no, or literal environmental feedback in a robot that is learning optimal locomotion through a space - it executes actions. So again, by that metric when you whip out your phone to take a selfie and your phone starts to track where your face is? It is executing an action based on its data-set of 'what is a face'. That. Is. AI.

So everything is AI now? Yeah it's an umbrella term, that's what I said. The disparity between knowing what machine learning and AI is to the point we call specific things AI (image generation, large language models, voice generation) and other things 'not AI' (see my long list again) is down to MARKETING.

Let me take you back to the tail 'end' of the pandemic. You're OpenAI and through scraping a lot of publically available data of just people chatting or writing various things - with dubious consent - you have made a really good chat-bot. Yeah you heard me, CHAT-BOT. If you're old like me, you remember chat-bots - they're those goofy things you played with as a teenager and laughed at because it'd say silly things and it'd be funny to put two together trying to talk to each other because they'd begin spouting nonsense and getting stuck in a loop. Or they're the widely hated artificial help systems on government websites embedded in a chatbox that does jack shit. Or the annoying pop up on some website you're just trying to buy shit from and stock-image-sandra is here in a text box 'ready to help you'. Chat-bots have an image problem. You can't release ChatGPT, your fancy chat-bot as a 'chat-bot', how the hell are you supposed to get investors? You've got some really good projects on the go (with dubiously sourced data) but you're running out of money. You need to do something fast.

So you take out the AI umbrella term, and right before everyone is just about ready to leave their hermit-chronically-online-pandemic-induced lifestyles - you drop the metaphorical bomb. You hand over your tech, now with the shiny new AI label, to the public. The AI label hides the fact from the public that you're basically rebranding shit we've had forever and by keeping it purposefully murky you can (hopefully) get people to ignore the fact that you've basically pulled vast swathes of data with dubious consent because - but it's AI! It's such a superior piece of technology! We can't un-invent the wheel because the ends didn't justify the means! It could change the world!

Despite the fact it's been 'changing the world' since 1960 and the only difference here is you linked enough computers together to make it better than what was currently available. But you now have to pay electricity costs for all that tech so, out into the wild it goes!

And now you've triggered a technological arms race and the use of AI (and your bottom line) is skyrocketing! AI that was previously the domain of government and massive corporate use is now in the hands of people to play with - their personal tech literacy be dammed (no literally be dammed, the less they understand the better). And they won't want to have it taken off them - in fact they'll fight each other over the value of your chat-bot and image generator in spite of the fact you stole data to train it. So your profits keep rolling in and next minute, despite your ethos being 'open source to all' - you're getting approached by Microsoft for a partial buy in and now you're 'semi-private', whatever the hell that means. Who cares! Money!

I have so, so much more to say on all this but I'll leave it for a proper post. But the lesson of this very tl;dr history of OpenAI is this: AI is machine learning. Machine learning is a TOOL. AI is a TOOL.

And a tool is only as ethical as the hand that chooses to wield it. Artificial intelligence is neutral. It is not good. It is not bad. It is just like the knife on your kitchen bench, with all the potential of doing good and useful things like help you make dinner and also horrendous, horrible things like commit a violent crime. And who made the knife in your kitchen? Is it artisan? Handcrafted by someone well paid in their profession? Or was it mass produced in third world conditions? Now is your knife itself bad? Should we ban all kitchen knives?

AI is a marketing buzzword for shit we've had for years - this is just the shiny version that went public to get money and we all fell for it hook, line and sinker.

So I challenge you, the next time something wizz-bang-shiny-tech-whatever is placed in front of you, and maybe it's a bit scary - to do what I do. Instead of filing it into a box of good or bad, start arguments online with someone with only limited information over whether someone is 'good' or 'bad' for participating or not participating in use of this technology because it's now emotionally loaded for you - do what I do. RESEARCH IT. Understand it, deeply. Listen to commentary on it from both sides, learn about the intent of why it was handed to you and for the love of god USE SOME CRITICAL THINKING SKILLS.

Because I guarantee you once you do that? Stuff will quickly become a lot less murky. You'll be able to see where your own blindspots are, and prevent them from being exploited - in this case, being taken advantage of by big corporations who are trying to pull and 'oopsie-woopsie' on unethical datasets for profit. You'll be able to hold them accountable. You'll also be less likely to get pulled into stupid arguments online about shit because you know it is way more nuanced than tech-bro putting out his big titty waifu image soup - he's small game here. Who cares about him. Go for the people at the top of this who are hoping to keep sliding on by with their rolling profits because you're too busy having fights among yourselves. Go for them and go for the fucking throat.

Any technology can be used for weal or woe, and it is entirely about the hand who wields it. Or in this case, the hand who programmed it.

If we want to continue to use AI or Machine Learning in an ethical, revolutionary manner we need to stop falling for the marketing, and hold each other accountable to uses that will continue to benefit humanity. Not pull it apart.

So yes. AI is a buzzword. Stop falling for it.