Werd I/O

[Samantha Cole at 404 Media]

"A highly-praised AI video generation tool made by multi-billion dollar company Runway was secretly trained by scraping thousands of videos from popular YouTube creators and brands, as well as pirated films."

404 Media has linked to the spreadsheet itself, which seems to be a pretty clear list of YouTube channels and individual videos.

Google is clear that this violates YouTube's rules. The team at Runway also by necessity downloaded the videos first using a third-party tool, which itself is a violation of the rules.

This is just a video version of the kinds of copyright and terms violations we've already seen copious amounts of in static media. But Google might be a stauncher defender of its rules than most - although not necessarily for principled reasons, because it, too, is in the business of training AI models on web data, and likely on YouTube content.

#AI

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[Gerben Wierda at R&A IT Strategy & Architecture]

"ChatGPT doesn’t summarise. When you ask ChatGPT to summarise this text, it instead shortens the text. And there is a fundamental difference between the two."

The distinction is indeed important: it's akin to making an easy reader version, albeit one with the odd error here and there.

This is particularly important for newsrooms and product teams that are looking at AI to generate takeaways from articles. There's a huge chance that it'll miss the main, most pertinent points, and simply shorten the text in the way it sees fit.

#AI

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[Cloudflare]

"To help preserve a safe Internet for content creators, we’ve just launched a brand new “easy button” to block all AI bots. It’s available for all customers, including those on our free tier."

This is really neat! Whatever you land on AI scraping, giving site owners the one-click ability to make a choice is great. Some will choose not to use this; others will hit the button. Making it this easy means it's a choice about the principles, not any kind of technical considerations. Which is what it should be.

Not every site is on Cloudflare (and some also choose not to use it because of how it's historically dealt with white supremacist / Nazi content). But many are, and this makes it easy for them. Other, similar providers will likely follow quickly.

#AI

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[Molly White]

"I fear that media outlets and other websites, in attempting to "protect" their material from AI scrapers, will go too far in the anti-human direction."

I've been struggling with this.

I'm not in favor of the 404 Media approach, which is to stick an auth wall in front of your content, forcing everyone to register before they can load your article. That isn't a great experience for anyone, and I don't think it's sustainable for a publisher in the long run.

At the same time, I think it's fair to try and prevent some bot access at the moment. Adding AI agents to your robots.txt - although, as recent news has shown, perhaps not as effective a move as it might be - seems like the right call to me.

Clearly an AI agent isn't a human. For ad hoc queries - where an agent is retrieving content from a website in direct response to a user query - it clearly is acting on behalf of a human. Is it a browser, then? Maybe? If it is, we should just let it through.

It's accessing articles as training data that I really take issue with (as well as the subterfuge of not always advertising what it is when it accesses a site). In these cases, content is copied into a corpus in a manner that's outside of its licensing, without the author's knowledge. That sucks - not because I'm in favor of DRM, but because often the people whose work is being taken are living on a shoestring, and the software is run by very large corporations who will make a fortune.

But yes: I don't think auth walls, CAPTCHAs, paywalls, or any added friction between content and audience are a good idea. These things make the web worse for everybody.

Molly's post is in response to an original by Manu Moreale, which is also worth reading.

#AI

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[Hunter Walk]

"The best commerce platforms will be constantly grooming you, priming you, shaping you to buy. The combination of short-term and long-term value that leads to the optimal financial outcome for the business."

I think this is inevitably correct: the web will devolve into a battle between different entities who are all trying to persuade you to take different actions. That's already been true for decades, but it's been ambient until now; generative AI gives it the ability to literally argue with us. Which means we're going to need our own bots to argue back.

Hunter's analogy of a bot that's supposedly in your corner calling bullshit on all the bots trying to sell things to you is a good one. Except, who will build the bot that's in your corner? Why will it definitely be so? Who will profit from it?

What a spiral this will be.

#AI

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[Nikhil Suresh at Ludicity]

"This entire class of person is, to put it simply, abhorrent to right-thinking people. They're an embarrassment to people that are actually making advances in the field, a disgrace to people that know how to sensibly use technology to improve the world, and are also a bunch of tedious know-nothing bastards that should be thrown into Thought Leader Jail until they've learned their lesson, a prison I'm fundraising for."

I enjoyed this very much.

Here's the thing, though: I don't think what Nikhil wants will happen.

I mean, don't get me wrong: it probably should. The author is a leader in his field, and his exasperation at the hype train is well-earned.

But it's not people like Nikhil who actually make the decisions, or invest in the companies, or make the whole industry (or industries) tick over. Again: it should be.

What happens again and again is that people who see that they can make money out of a particularly hyped technology leap onto the bandwagon, and then market the bandwagon within an inch of everybody's lives. Stuff that shouldn't be widespread becomes widespread.

And here we are again with AI.

This is exactly right:

"Unless you are one of a tiny handful of businesses who know exactly what they're going to use AI for, you do not need AI for anything - or rather, you do not need to do anything to reap the benefits. Artificial intelligence, as it exists and is useful now, is probably already baked into your businesses software supply chain."

And this:

"It did not end up being the crazy productivity booster that I thought it would be, because programming is designing and these tools aren't good enough (yet) to assist me with this seriously."

There is work that will be improved with AI, but it's not something that most industries will have to stop everything and leap on top of. The human use cases must come first with any technology: if you have a problem that AI can solve, by all means, use AI. But if you don't, hopping on the hype train is just going to burn you a lot of money and slow your actual core business down.

#AI

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[Michael Atleson at the FTC Division of Advertising Practices]

"Don’t misrepresent what these services are or can do. Your therapy bots aren’t licensed psychologists, your AI girlfriends are neither girls nor friends, your griefbots have no soul, and your AI copilots are not gods."

The FTC gets involved in the obviously rife practice of overselling the capabilities of AI services. These are solid guidelines, and hopefully the precursor to more meaningful action when vendors inevitably cross the line.

While these points are all important, for me the most pertinent is the last:

"Don’t violate consumer privacy rights. These avatars and bots can collect or infer a lot of intensely personal information. Indeed, some companies are marketing as a feature the ability of such AI services to know everything about us. It’s imperative that companies are honest and transparent about the collection and use of this information and that they don’t surreptitiously change privacy policies or relevant terms of service."

It's often unclear how much extra data is being gathered behind the scenes when AI features are added. This is where battles will be fought and lines will be drawn, particularly in enterprises and well-regulated industries.

#AI

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[Robb Knight]

Perplexity AI doesn't use its advertised browser string or IP range to load content from third-party websites:

"So they're using headless browsers to scrape content, ignoring robots.txt, and not sending their user agent string. I can't even block their IP ranges because it appears these headless browsers are not on their IP ranges."

On one level, I understand why this is happening, as everyone who's ever written a scraper (or scraper mitigations) might: the crawler for training the model likely does use the correct browser string, but on-demand calls likely don't to prevent them from being blocked. That's not a good excuse at all, but I bet that's what's going on.

This is another example of the core issue with robots.txt: it's a handshake agreement at best. There are no legal or technical restrictions imposed by it; we all just hope that bots do the right thing. Some of them do, but a lot of them don't.

The only real way to restrict these services is through legal rules that create meaningful consequences for these companies. Until then, there will be no sure-fire way to prevent your content from being accessed by an AI agent.

#AI

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[Heather Bryant]

"What generative AI creates is not any one person's creative expression. Generative AI is only possible because of the work that has been taken from others. It simply would not exist without the millions of data points that the models are based upon. Those data points were taken without permission, consent, compensation or even notification because the logistics of doing so would have made it logistically improbable and financially impossible."

This is a wonderful piece from Heather Bryant that explores the humanity - the effort, the emotion, the lived experience, the community, the unique combination of things - behind real-world art that is created by people, and the theft of those things that generative AI represents.

It's the definition of superficiality, and as Heather says here, living in a world made by people, rooted in experiences and relationships and reflecting actual human thought, is what I hope for. Generative AI is a technical accomplishment, for sure, but it is not a humanist accomplishment. There are no shortcuts to the human experience. And wanting a shortcut to human experience in itself devalues being human.

#AI

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[Janet Vertesi at Public Books]

"Our lives are consumed with the consumption of content, but we no longer know the truth when we see it. And when we don’t know how to weigh different truths, or to coordinate among different real-world experiences to look behind the veil, there is either cacophony or a single victor: a loudest voice that wins."

This is a piece about information, trust, the effect that AI is already having on knowledge.

When people said that books were more trustworthy than the internet, we scoffed; I scoffed. Books were not infallible; the stamp of a traditional publisher was not a sign that the information was correct or trustworthy. The web allowed more diverse voices to be heard. It allowed more people to share information. It was good.

The flood of automated content means that this is no longer the case. Our search engines can't be trusted; YouTube is certainly full of the worst automated dreck. I propose that we reclaim the phrase pink slime to encompass this nonsense: stuff that's been generated by a computer at scale in order to get attention.

So, yeah, I totally sympathize with the urge to buy a real-world encyclopedia again. Projects like Wikipedia must be preserved at all costs. But we have to consider if all this will result in the effective end of a web where humans publish and share information. And if that's the case, what's next?

#AI

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[The Markup]

"Now all three men are speaking out against pending California legislation that would make it illegal for police to use face recognition technology as the sole reason for a search or arrest. Instead it would require corroborating indicators."

Even with mitigations, it will lead to wrongful arrests: so-called "corroborating indicators" don't assist with the fact that the technology is racially biased and unreliable, and in fact may provide justification for using it.

And the stories of this technology being used are intensely bad miscarriages of justice:

“Other than a photo lineup, the detective did no other investigation. So it’s easy to say that it’s the officer’s fault, that he did a poor job or no investigation. But he relied on (face recognition), believing it must be right. That’s the automation bias this has been referenced in these sessions.”

"Believing it must be right" is one of core social problems widespread AI is introducing. Many people think of computers as being coldly logical deterministic thinkers. Instead, there's always the underlying biases of the people who built the systems and, in the case of AI, in the vast amounts of public data used to train them. False positives are bad in any scenario; in law enforcement, it can destroy or even end lives.

#AI

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"Chamber of Progress, a tech industry coalition whose members include Amazon, Apple and Meta, is launching a campaign to defend the legality of using copyrighted works to train artificial intelligence systems."

I understand why they're making this push, but I don't know that it's the right PR move for some of the wealthiest corporations in the world to push back on independent artists. I wish they were actually reaching out and finding stronger ways to support the people who make creative work.

The net impression I'm left with is not support of user freedom, but bullying. Left out of the equation is the scope of fair use, which is painted here as being under attack as a principle by the artists rather than by large companies that seek to use peoples' work for free to make products that they will make billions of dollars from.

The whole thing is disingenuous and disappointing, and is likely to backfire. It's particularly sad to see Apple participate in this mess. So much for bicycles of the mind.

#AI

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Eric Yuan has a really bizarre vision of what the future should look like:

"Today for this session, ideally, I do not need to join. I can send a digital version of myself to join so I can go to the beach. Or I do not need to check my emails; the digital version of myself can read most of the emails. Maybe one or two emails will tell me, “Eric, it’s hard for the digital version to reply. Can you do that?” Again, today we all spend a lot of time either making phone calls, joining meetings, sending emails, deleting some spam emails and replying to some text messages, still very busy. How [do we] leverage AI, how do we leverage Zoom Workplace, to fully automate that kind of work? That’s something that is very important for us."

The solution to having too many meetings that you don't really need to attend, and too many emails that are informational only, is to not have the meetings and emails. It's not to let AI do it for you, which in effect creates a world where our avatars are doing a bunch of makework drudgery for no reason.

Instead of building better business cultures and reinventing our work rhythms to adapt to information overload and an abundance of busywork, the vision here is to let the busywork happen between AI. It's an office full of ghosts, speaking to each other on our behalf, going to standup meetings with each other just because.

I mean, I get it. Meetings are Zoom's business. But count me out.

#AI

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On answering programming questions: "We found that 52 percent of ChatGPT answers contain misinformation, 77 percent of the answers are more verbose than human answers, and 78 percent of the answers suffer from different degrees of inconsistency to human answers."

To be fair, I do expect AI answers to get better over time, but it's certainly premature to use it as a trusted toolkit for software development today. One might argue that its answers are more like suggestions for an engineer to check and adapt as appropriate, but will they really be used that way?

I think it's more likely that AI agents will be used to build software by people who want to avoid engaging with a real, human engineer, or people who want to cut corners for one reason or another. So I think the warnings are appropriate: LLMs are bad at coding and we shouldn't trust what they say. #AI

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"It’s simply too early to get into bed with the companies that trained their models on professional content without permission and have no compelling case for how they will help build the news business."

This piece ends on the most important point: nobody is coming to save the news industry, and certainly not the AI vendors. Software companies don't care about news. They don't think your content is more valuable because it's fact-checked and edited. They don't have a vested interest in ensuring you survive. They just want the training data - all of it, in order to build what they consider to be the best product possible. Everything else is irrelevant. #AI

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Simon Willison has a perfect name for unreviewed content that is shared with other people: "slop".

He goes on:

"I’m happy to use LLMs for all sorts of purposes, but I’m not going to use them to produce slop. I attach my name and stake my credibility on the things that I publish."

I think that's right. I'm less worried about using LLMs internally - as long as you understand that they're not impartial or perfectly factual sources, and as long as you take into account the methods used to generate the datasets that were used to train them. (Those are some big "if"s.)

But don't just take that output and share it with the public. And *certainly* don't do it so that you can publish content at scale without having to hire real writers. Not only is that not a good look, but you're going to harm your brand and your reputation in the process. #AI

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"Users who disagree with having their content scraped by ChatGPT are particularly outraged by Stack Overflow's rapid flip-flop on its policy concerning generative AI. For years, the site had a standing policy that prevented the use of generative AI in writing or rewording any questions or answers posted. Moderators were allowed and encouraged to use AI-detection software when reviewing posts."

This is all about money: "partnering" with OpenAI clearly means a significant sum has changed hands. The same thing may have happened at Valve, which also unblocked AI-generated art from its marketplace.

This feels like short-term thinking to me: while Stack will clearly make some near-term revenue through the deal, it comes at a cost to the health of its community, which is ultimately what drives the company's value. If motivated contributors drop off, the only thing left will be the AI-generated content - and there's no way that this will be as valuable over time.

I'd love to have been a fly on the wall of the boardroom where this deal was undoubtedly decided. What are they measuring that made this seem like a good idea - and what are they not measuring that means they're blind to the community dynamics that drive their actual sustainability? It's all fascinating to me. #AI

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"We found the company's phony authors and their work everywhere from celebrity gossip outlets like Hollywood Life and Us Weekly to venerable newspapers like the Los Angeles Times, the latter of which also told us that it had broken off its relationship with AdVon after finding its work unsatisfactory."

Even if the LA Times broke off its relationship because the work was unsatisfactory, the fact that this was attempted in the first place is unsettling. What if the work hadn't been "unsatisfactory"? What if it had been "good enough"?

It's not so much the technology itself as the intention behind it: to produce content at scale without employing human journalists, largely to generate pageviews in order to sell ads. There's no public service mission here, or even a mission to provide something that people might really want to read. It's all about arbitrage. #AI

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A detail I hadn't noticed: while the New York Times OpenAI lawsuit rested on copyright infringement, the Intercept, Raw Story, and AlterNet are claiming a DMCA violation.

"A study released this month by Patronus AI, a startup launched by former Meta researchers, found that GPT-4 reproduced copyrighted content at the highest rate among popular LLMs. When asked to finish a passage of a copyrighted novel, GPT-4 reproduced the text verbatim 60% of the time. The new lawsuits similarly allege that ChatGPT reproduces journalistic works near-verbatim when prompted." #AI

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"Sure, our articles maintain a rigid SEO template that creatively resembles the kitchen at a poorly run Quiznos, and granted, all our story ideas are gleaned from better-written magazine articles from seven months ago (that we’re totally not plagiarizing), but imagine if AI wrote those articles? So much would be lost."

Touché. #AI

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"Researchers have discovered a new way to hack AI assistants that uses a surprisingly old-school method: ASCII art."

So many LLM exploits come down to finding ways to convince an engine to disregard its own programming. It's straight out of 1980s science fiction, like teaching an android to lie. To be successful, you have to understand how LLMs "think", and then exploit that.

This one in particular is so much fun. By telling it to interpret an ASCII representation of a word and keep the meaning in memory without saying it out loud, front-line harm mitigations can be bypassed. It's like a magic spell. #AI

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Europe once again leads the way by passing meaningful AI regulation. Banned unacceptable-risk uses of AI include facial recognition, social scoring, and emotion recognition at schools and workplaces.

"The use of real-time facial recognition systems by law enforcement is permitted “in exhaustively listed and narrowly defined situations,” when the geographic area and the length of deployment are constrained."

I'm all in favor of these changes, but it's a little bit sad that this sort of regulation is always left up to the EU. American regulators appear to be sleeping. #AI

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"What I thought would be helpful, instead, is to survey the current state of AI-powered journalism, from the very bad to really good, and try to draw some lessons from those examples. I'm only speaking for myself today, but this certainly reflects how I'm thinking about the role AI could play in The Times newsroom and beyond."

A pretty good roundup, including the mistakes, folks using AI for pattern-recognition, and newsrooms that are actually using generative models. #AI

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I can't share a quote from this one without ruining it. But you should go read it. #AI

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"Users mistake decreasing levels of overt prejudice for a sign that racism in LLMs has been solved, when LLMs are in fact reaching increasing levels of covert prejudice."

Or to put it another way: AI is wildly racist. Although it has been trained to be less overtly so, it is now covertly discriminatory. For example, if it analyzes text written in AAE rather than Standardized American English, it is more likely to assign the death penalty, penalize job applicants, and so on. #AI

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