generative ai

Scientists once hoarded pre-nuclear steel; now we’re hoarding pre-AI content

AI, AI criticism, AI writing, Biz & IT, chatbots, cultural singularity, data science, generative ai, large language models, machine learning, Open Source / Kris Guyer / June 18, 2025

A time capsule of human expression

Graham-Cumming is no stranger to tech preservation efforts. He’s a British software engineer and writer best known for creating POPFile, an open source email spam filtering program, and for successfully petitioning the UK government to apologize for its persecution of codebreaker Alan Turing—an apology that Prime Minister Gordon Brown issued in 2009.

As it turns out, his pre-AI website isn’t new, but it has languished unannounced until now. “I created it back in March 2023 as a clearinghouse for online resources that hadn’t been contaminated with AI-generated content,” he wrote on his blog.

The website points to several major archives of pre-AI content, including a Wikipedia dump from August 2022 (before ChatGPT’s November 2022 release), Project Gutenberg’s collection of public domain books, the Library of Congress photo archive, and GitHub’s Arctic Code Vault—a snapshot of open source code buried in a former coal mine near the North Pole in February 2020. The wordfreq project appears on the list as well, flash-frozen from a time before AI contamination made its methodology untenable.

The site accepts submissions of other pre-AI content sources through its Tumblr page. Graham-Cumming emphasizes that the project aims to document human creativity from before the AI era, not to make a statement against AI itself. As atmospheric nuclear testing ended and background radiation returned to natural levels, low-background steel eventually became unnecessary for most uses. Whether pre-AI content will follow a similar trajectory remains a question.

Still, it feels reasonable to protect sources of human creativity now, including archival ones, because these repositories may become useful in ways that few appreciate at the moment. For example, in 2020, I proposed creating a so-called “cryptographic ark”—a timestamped archive of pre-AI media that future historians could verify as authentic, collected before my then-arbitrary cutoff date of January 1, 2022. AI slop pollutes more than the current discourse—it could cloud the historical record as well.

For now, lowbackgroundsteel.ai stands as a modest catalog of human expression from what may someday be seen as the last pre-AI era. It’s a digital archaeology project marking the boundary between human-generated and hybrid human-AI cultures. In an age where distinguishing between human and machine output grows increasingly difficult, these archives may prove valuable for understanding how human communication evolved before AI entered the chat.

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Hollywood studios target AI image generator in copyright lawsuit

AI, AI development tools, AI ethics, AI image generator, AI image generators, AI law, AI lawsuits, Biz & IT, copyright, Darth Vader, Disney, entertainment industry, generative ai, Hollywood, image synthesis, intellectual property, machine learning, MidJourney, Policy, star wars, universal / Rejus Almole / June 12, 2025

The legal action follows similar moves in other creative industries, with more than a dozen major news companies suing AI company Cohere in February over copyright concerns. In 2023, a group of visual artists sued Midjourney for similar reasons.

Studios claim Midjourney knows what it’s doing

Beyond allowing users to create these images, the studios argue that Midjourney actively promotes copyright infringement by displaying user-generated content featuring copyrighted characters in its “Explore” section. The complaint states this curation “show[s] that Midjourney knows that its platform regularly reproduces Plaintiffs’ Copyrighted Works.”

The studios also allege that Midjourney has technical protection measures available that could prevent outputs featuring copyrighted material but has “affirmatively chosen not to use copyright protection measures to limit the infringement.” They cite Midjourney CEO David Holz admitting the company “pulls off all the data it can, all the text it can, all the images it can” for training purposes.

According to Axios, Disney and NBCUniversal attempted to address the issue with Midjourney before filing suit. While the studios say other AI platforms agreed to implement measures to stop IP theft, Midjourney “continued to release new versions of its Image Service” with what Holz allegedly described as “even higher quality infringing images.”

“We are bringing this action today to protect the hard work of all the artists whose work entertains and inspires us and the significant investment we make in our content,” said Kim Harris, NBCUniversal’s executive vice president and general counsel, in a statement.

This lawsuit signals a new front in Hollywood’s conflict over AI. Axios highlights this shift: While actors and writers have fought to protect their name, image, and likeness from studio exploitation, now the studios are taking on tech companies over intellectual property concerns. Other major studios, including Amazon, Netflix, Paramount Pictures, Sony, and Warner Bros., have not yet joined the lawsuit, though they share membership with Disney and Universal in the Motion Picture Association.

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It’s too expensive to fight every AI copyright battle, Getty CEO says

AI, Artificial Intelligence, copyright, fair use, generative ai, Getty Images, image generators, Policy, Stability AI, Stable Diffusion / Tim Belzer / May 29, 2025

Getty dumped “millions and millions” into just one AI copyright fight, CEO says.

In some ways, Getty Images has emerged as one of the most steadfast defenders of artists’ rights in AI copyright fights. Starting in 2022, when some of the most sophisticated image generators today first started testing new models offering better compositions, Getty banned AI-generated uploads to its service. And by the next year, Getty released a “socially responsible” image generator to prove it was possible to build a tool while rewarding artists, while suing an AI firm that refused to pay artists.

But in the years since, Getty Images CEO Craig Peters recently told CNBC that the media company has discovered that it’s simply way too expensive to fight every AI copyright battle.

According to Peters, Getty has dumped millions into just one copyright fight against Stability AI.

It’s “extraordinarily expensive,” Peters told CNBC. “Even for a company like Getty Images, we can’t pursue all the infringements that happen in one week.” He confirmed that “we can’t pursue it because the courts are just prohibitively expensive. We are spending millions and millions of dollars in one court case.”

Fair use?

Getty sued Stability AI in 2023, after the AI company’s image generator, Stable Diffusion, started spitting out images that replicated Getty’s famous trademark. In the complaint, Getty alleged that Stability AI had trained Stable Diffusion on “more than 12 million photographs from Getty Images’ collection, along with the associated captions and metadata, without permission from or compensation to Getty Images, as part of its efforts to build a competing business.”

As Getty saw it, Stability AI had plenty of opportunity to license the images from Getty and seemingly “chose to ignore viable licensing options and long-standing legal protections in pursuit of their stand-alone commercial interests.”

Stability AI, like all AI firms, has argued that AI training based on freely scraping images from the web is a “fair use” protected under copyright law.

So far, courts have not settled this debate, while many AI companies have urged judges and governments globally to settle it for the courts, for the sake of safeguarding national security and securing economic prosperity by winning the AI race. According to AI companies, paying artists to train on their works threatens to slow innovation, while rivals in China—who aren’t bound by US copyright law—continue scraping the web to advance their models.

Peters called out Stability AI for adopting this stance, arguing that rightsholders shouldn’t have to spend millions fighting against a claim that paying out licensing fees would “kill innovation.” Some critics have likened AI firms’ argument to a defense of forced labor, suggesting the US would never value “innovation” about human rights, and the same logic should follow for artists’ rights.

“We’re battling a world of rhetoric,” Peters said, alleging that these firms “are taking copyrighted material to develop their powerful AI models under the guise of innovation and then ‘just turning those services right back on existing commercial markets.'”

To Peters, that’s simply “disruption under the notion of ‘move fast and break things,’” and Getty believes “that’s unfair competition.”

“We’re not against competition,” Peters said. “There’s constant new competition coming in all the time from new technologies or just new companies. But that [AI scraping] is just unfair competition, that’s theft.”

Broader Internet backlash over AI firms’ rhetoric

Peters’ comments come after a former Meta head of global affairs, Nick Clegg, received Internet backlash this week after making the same claim that AI firms raise time and again: that asking artists for consent for AI training would “kill” the AI industry, The Verge reported.

According to Clegg, the only viable solution to the tension between artists and AI companies would be to give artists ways to opt out of training, which Stability AI notably started doing in 2022.

“Quite a lot of voices say, ‘You can only train on my content, [if you] first ask,'” Clegg reportedly said. “And I have to say that strikes me as somewhat implausible because these systems train on vast amounts of data.”

On X, the CEO of Fairly Trained—a nonprofit that supports artists’ fight against nonconsensual AI training—Ed Newton-Rex (who is also a former Stability AI vice president of audio) pushed back on Clegg’s claim in a post viewed by thousands.

“Nick Clegg is wrong to say artists’ demands on AI & copyright are unworkable,” Newton-Rex said. “Every argument he makes could equally have been made about Napster:” First, that “the tech is out there,” second that “licensing takes time,” and third that, “we can’t control what other countries do.” If Napster’s operations weren’t legal, neither should AI firms’ training, Newton-Rex said, writing, “These are not reasons not to uphold the law and treat creators fairly.”

Other social media users mocked Clegg with jokes meant to destroy AI firms’ favorite go-to argument against copyright claims.

“Blackbeard says asking sailors for permission to board and loot their ships would ‘kill’ the piracy on the high seas industry,” an X user with the handle “Seanchuckle” wrote.

On Bluesky, a trial lawyer, Max Kennerly, effectively satirized Clegg and the whole AI industry by writing, “Our product creates such little value that it is simply not viable in the marketplace, not even as a niche product. Therefore, we must be allowed to unilaterally extract value from the work of others and convert that value into our profits.”

Other ways to fight

Getty plans to continue fighting against the AI firms that are impressing this “world of rhetoric” on judges and lawmakers, but court battles will likely remain few and far between due to the price tag, Peters has suggested.

There are other ways to fight, though. In a submission last month, Getty pushed the Trump administration to reject “those seeking to weaken US copyright protections by creating a ‘right to learn’ exemption” for AI firms when building Trump’s AI Action Plan.

“US copyright laws are not obstructing the path to continued AI progress,” Getty wrote. “Instead, US copyright laws are a path to sustainable AI and a path that broadens society’s participation in AI’s economic benefits, which reduces downstream economic burdens on the Federal, State and local governments. US copyright laws provide incentives to invest and create.”

In Getty’s submission, the media company emphasized that requiring consent for AI training is not an “overly restrictive” control on AI’s development such as those sought by stauncher critics “that could harm US competitiveness, national security or societal advances such as curing cancer.” And Getty claimed it also wasn’t “requesting protection from existing and new sources of competition,” despite the lawsuit’s suggestion that Stability AI and other image generators threaten to replace Getty’s image library in the market.

What Getty said it hopes Trump’s AI plan will ensure is a world where the rights and opportunities of rightsholders are not “usurped for the commercial benefits” of AI companies.

In 2023, when Getty was first suing Stability AI, Peters suggested that, otherwise, allowing AI firms to widely avoid paying artists would create “a sad world,” perhaps disincentivizing creativity.

Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.

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Netflix will show generative AI ads midway through streams in 2026

ads, AI, generative ai, netflix, streaming, Tech / Rejus Almole / May 15, 2025

Netflix is joining its streaming rivals in testing the amount and types of advertisements its subscribers are willing to endure for lower prices.

Today, at its second annual upfront to advertisers, the streaming leader announced that it has created interactive mid-roll ads and pause ads that incorporate generative AI. Subscribers can expect to start seeing the new types of ads in 2026, Media Play News reported.

“[Netflix] members pay as much attention to midroll ads as they do to the shows and movies themselves,” Amy Reinhard, president of advertising at Netflix, said, per the publication.

Netflix started testing pause ads in July 2024, per The Verge.

Netflix launched its ad subscription tier in November 2022. Today, it said that the tier has 94 million subscribers, compared to the 300 million total subscribers it claimed in January. The current number of ad subscribers represents a 34 percent increase from November. Half of new Netflix subscribers opt for the $8 per month option rather than ad-free subscriptions, which start at $18 per month, the company says.

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Copyright Office head fired after reporting AI training isn’t always fair use

AI, Artificial Intelligence, chatbots, copyright, Donald Trump, fair use, generative ai, openai, Policy, US Copyright Office / Mike M. / May 13, 2025

Cops scuffle with Trump picks at Copyright Office after AI report stuns tech industry.

A man holds a flag that reads “Shame” outside the Library of Congress on May 12, 2025 in Washington, DC. On May 8th, President Donald Trump fired Carla Hayden, the head of the Library of Congress, and Shira Perlmutter, the head of the US Copyright Office, just days after. Credit: Kayla Bartkowski / Staff | Getty Images News

A day after the US Copyright Office dropped a bombshell pre-publication report challenging artificial intelligence firms’ argument that all AI training should be considered fair use, the Trump administration fired the head of the Copyright Office, Shira Perlmutter—sparking speculation that the controversial report hastened her removal.

Tensions have apparently only escalated since. Now, as industry advocates decry the report as overstepping the office’s authority, social media posts on Monday described an apparent standoff at the Copyright Office between Capitol Police and men rumored to be with Elon Musk’s Department of Government Efficiency (DOGE).

A source familiar with the matter told Wired that the men were actually “Brian Nieves, who claimed he was the new deputy librarian, and Paul Perkins, who said he was the new acting director of the Copyright Office, as well as acting Registrar,” but it remains “unclear whether the men accurately identified themselves.” A spokesperson for the Capitol Police told Wired that no one was escorted off the premises or denied entry to the office.

Perlmutter’s firing followed Donald Trump’s removal of Librarian of Congress Carla Hayden, who, NPR noted, was the first African American to hold the post. Responding to public backlash, White House Press Secretary Karoline Leavitt claimed that the firing was due to “quite concerning things that she had done at the Library of Congress in the pursuit of DEI and putting inappropriate books in the library for children.”

The Library of Congress houses the Copyright Office, and critics suggested Trump’s firings were unacceptable intrusions into cultural institutions that are supposed to operate independently of the executive branch. In a statement, Rep. Joe Morelle (D.-N.Y.) condemned Perlmutter’s removal as “a brazen, unprecedented power grab with no legal basis.”

Accusing Trump of trampling Congress’ authority, he suggested that Musk and other tech leaders racing to dominate the AI industry stood to directly benefit from Trump’s meddling at the Copyright Office. Likely most threatening to tech firms, the guidance from Perlmutter’s Office not only suggested that AI training on copyrighted works may not be fair use when outputs threaten to disrupt creative markets—as publishers and authors have argued in several lawsuits aimed at the biggest AI firms—but also encouraged more licensing to compensate creators.

“It is surely no coincidence [Trump] acted less than a day after she refused to rubber-stamp Elon Musk’s efforts to mine troves of copyrighted works to train AI models,” Morelle said, seemingly referencing Musk’s xAI chatbot, Grok.

Agreeing with Morelle, Courtney Radsch—the director of the Center for Journalism & Liberty at the left-leaning think tank the Open Markets Institute—said in a statement provided to Ars that Perlmutter’s firing “appears directly linked to her office’s new AI report questioning unlimited harvesting of copyrighted materials.”

“This unprecedented executive intrusion into the Library of Congress comes directly after Perlmutter released a copyright report challenging the tech elite’s fundamental claim: unlimited access to creators’ work without permission or compensation,” Radsch said. And it comes “after months of lobbying by the corporate billionaires” who “donated” millions to Trump’s inauguration and “have lapped up the largess of government subsidies as they pursue AI dominance.”

What the Copyright Office says about fair use

The report that the Copyright Office released on Friday is not finalized but is not expected to change radically, unless Trump’s new acting head potentially intervenes to overhaul the guidance.

It comes after the Copyright Office parsed more than 10,000 comments debating whether creators should and could feasibly be compensated for the use of their works in AI training.

“The stakes are high,” the office acknowledged, but ultimately, there must be an effective balance struck between the public interests in “maintaining a thriving creative community” and “allowing technological innovation to flourish.” Notably, the office concluded that the first and fourth factors of fair use—which assess the character of the use (and whether it is transformative) and how that use affects the market—are likely to hold the most weight in court.

According to Radsch, the report “raised crucial points that the tech elite don’t want acknowledged.” First, the Copyright Office acknowledged that it’s an open question how much data an AI developer needs to build an effective model. Then, they noted that there’s a need for a consent framework beyond putting the onus on creators to opt their works out of AI training, and perhaps most alarmingly, they concluded that “AI trained on copyrighted works could replace original creators in the marketplace.”

“Commenters painted a dire picture of what unlicensed training would mean for artists’ livelihoods,” the Copyright Office said, while industry advocates argued that giving artists the power to hamper or “kill” AI development could result in “far less competition, far less innovation, and very likely the loss of the United States’ position as the leader in global AI development.”

To prevent both harms, the Copyright Office expects that some AI training will be deemed fair use, such as training viewed as transformative, because resulting models don’t compete with creative works. Those uses threaten no market harm but rather solve a societal need, such as language models translating texts, moderating content, or correcting grammar. Or in the case of audio models, technology that helps producers clean up unwanted distortion might be fair use, where models that generate songs in the style of popular artists might not, the office opined.

But while “training a generative AI foundation model on a large and diverse dataset will often be transformative,” the office said that “not every transformative use is a fair one,” especially if the AI model’s function performs the same purpose as the copyrighted works they were trained on. Consider an example like chatbots regurgitating news articles, as is alleged in The New York Times’ dispute with OpenAI over ChatGPT.

“In such cases, unless the original work itself is being targeted for comment or parody, it is hard to see the use as transformative,” the Copyright Office said. One possible solution for AI firms hoping to preserve utility of their chatbots could be effective filters that “prevent the generation of infringing content,” though.

Tech industry accuses Copyright Office of overreach

Only courts can effectively weigh the balance of fair use, the Copyright Office said. Perhaps importantly, however, the thinking of one of the first judges to weigh the question—in a case challenging Meta’s torrenting of a pirated books dataset to train its AI models—seemed to align with the Copyright Office guidance at a recent hearing. Mulling whether Meta infringed on book authors’ rights, US District Judge Vince Chhabria explained why he doesn’t immediately “understand how that can be fair use.”

“You have companies using copyright-protected material to create a product that is capable of producing an infinite number of competing products,” Chhabria said. “You are dramatically changing, you might even say obliterating, the market for that person’s work, and you’re saying that you don’t even have to pay a license to that person.”

Some AI critics think the courts have already indicated which way they are leaning. In a statement to Ars, a New York Times spokesperson suggested that “both the Copyright Office and courts have recognized what should be obvious: when generative AI products give users outputs that compete with the original works on which they were trained, that unprecedented theft of millions of copyrighted works by developers for their own commercial benefit is not fair use.”

The NYT spokesperson further praised the Copyright Office for agreeing that using Retrieval-Augmented Generation (RAG) AI to surface copyrighted content “is less likely to be transformative where the purpose is to generate outputs that summarize or provide abridged versions of retrieved copyrighted works, such as news articles, as opposed to hyperlinks.” If courts agreed on the RAG finding, that could potentially disrupt AI search models from every major tech company.

The backlash from industry stakeholders was immediate.

The president and CEO of a trade association called the Computer & Communications Industry Association, Matt Schruers, said the report raised several concerns, particularly by endorsing “an expansive theory of market harm for fair use purposes that would allow rightsholders to block any use that might have a general effect on the market for copyrighted works, even if it doesn’t impact the rightsholder themself.”

Similarly, the tech industry policy coalition Chamber of Progress warned that “the report does not go far enough to support innovation and unnecessarily muddies the waters on what should be clear cases of transformative use with copyrighted works.” Both groups celebrated the fact that the final decision on fair use would rest with courts.

The Copyright Office agreed that “it is not possible to prejudge the result in any particular case” but said that precedent supports some “general observations.” Those included suggesting that licensing deals may be appropriate where uses are not considered fair without disrupting “American leadership” in AI, as some AI firms have claimed.

“These groundbreaking technologies should benefit both the innovators who design them and the creators whose content fuels them, as well as the general public,” the report said, ending with the office promising to continue working with Congress to inform AI laws.

Copyright Office seemingly opposes Meta’s torrenting

Also among those “general observations,” the Copyright Office wrote that “making commercial use of vast troves of copyrighted works to produce expressive content that competes with them in existing markets, especially where this is accomplished through illegal access, goes beyond established fair use boundaries.”

The report seemed to suggest that courts and the Copyright Office may also be aligned on AI firms’ use of pirated or illegally accessed paywalled content for AI training.

Judge Chhabria only considered Meta’s torrenting in the book authors’ case to be “kind of messed up,” prioritizing the fair use question, and the Copyright Office similarly only recommended that “the knowing use of a dataset that consists of pirated or illegally accessed works should weigh against fair use without being determinative.”

However, torrenting should be a black mark, the Copyright Office suggested. “Gaining unlawful access” does bear “on the character of the use,” the office noted, arguing that “training on pirated or illegally accessed material goes a step further” than simply using copyrighted works “despite the owners’ denial of permission.” Perhaps if authors can prove that AI models trained on pirated works led to lost sales, the office suggested that a fair use defense might not fly.

“The use of pirated collections of copyrighted works to build a training library, or the distribution of such a library to the public, would harm the market for access to those Works,” the office wrote. “And where training enables a model to output verbatim or substantially similar copies of the works trained on, and those copies are readily accessible by end users, they can substitute for sales of those works.”

Likely frustrating Meta—which is currently fighting to keep leeching evidence out of the book authors’ case—the Copyright Office suggested that “the copying of expressive works from pirate sources in order to generate unrestricted content that competes in the marketplace, when licensing is reasonably available, is unlikely to qualify as fair use.”

Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.

Time saved by AI offset by new work created, study suggests

AI, AI and work, AI assistants, AI study, Biz & IT, generative ai, large language models, machine learning, The Register, University of Chicago, University of Copenhagen / Tim Belzer / May 2, 2025

A new study analyzing the Danish labor market in 2023 and 2024 suggests that generative AI models like ChatGPT have had almost no significant impact on overall wages or employment yet, despite rapid adoption in some workplaces. The findings, detailed in a working paper by economists from the University of Chicago and the University of Copenhagen, provide an early, large-scale empirical look at AI’s transformative potential.

In “Large Language Models, Small Labor Market Effects,” economists Anders Humlum and Emilie Vestergaard focused specifically on the impact of AI chatbots across 11 occupations often considered vulnerable to automation, including accountants, software developers, and customer support specialists. Their analysis covered data from 25,000 workers and 7,000 workplaces in Denmark.

Despite finding widespread and often employer-encouraged adoption of these tools, the study concluded that “AI chatbots have had no significant impact on earnings or recorded hours in any occupation” during the period studied. The confidence intervals in their statistical analysis ruled out average effects larger than 1 percent.

“The adoption of these chatbots has been remarkably fast,” Humlum told The Register about the study. “Most workers in the exposed occupations have now adopted these chatbots… But then when we look at the economic outcomes, it really has not moved the needle.”

AI creating more work?

During the study, the researchers investigated how company investment in AI affected worker adoption and how chatbots changed workplace processes. While corporate investment boosted AI tool adoption—saving time for 64 to 90 percent of users across studied occupations—the actual benefits were less substantial than expected.

The study revealed that AI chatbots actually created new job tasks for 8.4 percent of workers, including some who did not use the tools themselves, offsetting potential time savings. For example, many teachers now spend time detecting whether students use ChatGPT for homework, while other workers review AI output quality or attempt to craft effective prompts.

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Midjourney introduces first new image generation model in over a year

AI, generative ai, image synthesis, MidJourney, midjourney v7 / Rejus Almole / April 5, 2025

AI image generator Midjourney released its first new model in quite some time today; dubbed V7, it’s a ground-up rework that is available in alpha to users now.

There are two areas of improvement in V7: the first is better images, and the second is new tools and workflows.

Starting with the image improvements, V7 promises much higher coherence and consistency for hands, fingers, body parts, and “objects of all kinds.” It also offers much more detailed and realistic textures and materials, like skin wrinkles or the subtleties of a ceramic pot.

Those details are often among the most obvious telltale signs that an image has been AI-generated. To be clear, Midjourney isn’t claiming to have made advancements that make AI images unrecognizable to a trained eye; it’s just saying that some of the messiness we’re accustomed to has been cleaned up to a significant degree.

V7 can reproduce materials and lighting situations that V6.1 usually couldn’t. Credit: Xeophon

On the features side, the star of the show is the new “Draft Mode.” On its various communication channels with users (a blog, Discord, X, and so on), Midjourney says that “Draft mode is half the cost and renders images at 10 times the speed.”

However, the images are of lower quality than what you get in the other modes, so this is not intended to be the way you produce final images. Rather, it’s meant to be a way to iterate and explore to find the desired result before switching modes to make something ready for public consumption.

V7 comes with two modes: turbo and relax. Turbo generates final images quickly but is twice as expensive in terms of credit use, while relax mode takes its time but is half as expensive. There is currently no standard mode for V7, strangely; Midjourney says that’s coming later, as it needs some more time to be refined.

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OpenAI declares AI race “over” if training on copyrighted works isn’t fair use

agi, ai action plan, copyright infringement, copyright law, Donald Trump, generative ai, national security, openai, Policy / Paul Patrick / March 14, 2025

OpenAI is hoping that Donald Trump’s AI Action Plan, due out this July, will settle copyright debates by declaring AI training fair use—paving the way for AI companies’ unfettered access to training data that OpenAI claims is critical to defeat China in the AI race.

Currently, courts are mulling whether AI training is fair use, as rights holders say that AI models trained on creative works threaten to replace them in markets and water down humanity’s creative output overall.

OpenAI is just one AI company fighting with rights holders in several dozen lawsuits, arguing that AI transforms copyrighted works it trains on and alleging that AI outputs aren’t substitutes for original works.

So far, one landmark ruling favored rights holders, with a judge declaring AI training is not fair use, as AI outputs clearly threatened to replace Thomson-Reuters’ legal research firm Westlaw in the market, Wired reported. But OpenAI now appears to be looking to Trump to avoid a similar outcome in its lawsuits, including a major suit brought by The New York Times.

“OpenAI’s models are trained to not replicate works for consumption by the public. Instead, they learn from the works and extract patterns, linguistic structures, and contextual insights,” OpenAI claimed. “This means our AI model training aligns with the core objectives of copyright and the fair use doctrine, using existing works to create something wholly new and different without eroding the commercial value of those existing works.”

Providing “freedom-focused” recommendations on Trump’s plan during a public comment period ending Saturday, OpenAI suggested Thursday that the US should end these court fights by shifting its copyright strategy to promote the AI industry’s “freedom to learn.” Otherwise, the People’s Republic of China (PRC) will likely continue accessing copyrighted data that US companies cannot access, supposedly giving China a leg up “while gaining little in the way of protections for the original IP creators,” OpenAI argued.

OpenAI declares AI race “over” if training on copyrighted works isn’t fair use Read More »

Amazon’s subscription-based Alexa+ looks highly capable—and questionable

AI, Amazon, amazon alexa, generative ai, Tech / Rejus Almole / February 27, 2025

Alexa+ will be free for Prime members, $20/month for everyone else.

NEW YORK—After teasing it in September 2023 and reportedly suffering delays, Amazon today announced that its more capable and conversational version of Alexa will start rolling out to US Prime members for free in the next few weeks.

Those who aren’t Prime subscribers will be able to get Alexa+ for $20 a month. Amazon didn’t provide a specific release date but said availability would start with the Echo Show 8, 10, 15, and 21 smart displays.

Amazon is hoping Alexa+ will be a lifeline for its fledgling voice assistant business that has failed to turn a profit. Alexa has reportedly cost Amazon tens of billions of dollars over the years. Although Alexa is on 600 million purchased devices, per remarks CEO Andy Jassy made at a press conference on Wednesday, it’s primarily used for simple tasks that don’t generate much money, like checking the weather. Exacerbating the problem, generative AI chatbots are a new, shinier approach to AI assistants that have quickly outperformed what people could do with today’s Alexa.

By using the large language models (LLMs) available under the Amazon Bedrock service and technology from Anthropic, as well as Amazon Web Services, Amazon has re-architected Alexa to, per demos Ars saw today, be significantly more useful. From its demonstrated speech and ability to respond to casual language (that doesn’t include saying the “Alexa” prompt repeatedly), to its ability to perform actions, like book dinner reservations or put appointments in your digital calendar, Alexa+ looks way more capable than the original Alexa.

Alexa+ in action

For example, Amazon representatives showed Alexa+ learning what a family member likes to eat and later recalling that information to recommend appropriate recipes. In another demo, Alexa+ appeared to set a price monitor for ticket availability on Ticketmaster. Alexa+ told the user it would notify them of price drops via their Echo or Alexa.

I also saw Alexa+ identify, per the issued prompt, “that song Bradley Cooper sings. It’s, like, in a duet” and stream it off of Amazon Music via Echo devices placed around the room. The user was able to toggle audio playing from Echo devices on the left or right side of the room. He then had Alexa+ quickly play the scene from the movie A Star Is Born (that the song is from) on a Fire TV.

Notably, Alexa+ understood directions delivered in casual speak (for example: “can you just jump to the scene in the movie?”). During the demos, the Echo Show in use showed a transcription of the user and voice assistant’s conversation on-screen. At times, I saw the transcription fix mistakes. For example, when a speaker said “I’m in New York,” Alexa first heard “I’m imminent,” but by the time the speaker was done talking, the transcribed prompt was corrected.

I even saw Alexa+ use some logic. In one demo, a user requested tickets for Seattle Storm games in Seattle in March. Since there were none, Alexa+ asked if the user wanted to look for games in April. This showed Alexa+ anticipating a user’s potential response, while increasing the chances that Amazon would be compensated for helping to drive a future ticket sale.

Unlike with today’s Alexa, Alexa+ is supposed to be able to interpret shared documents. An Amazon rep appeared to show Alexa+ reading a homeowner’s association contract to determine if the user is allowed to install solar panels on their home. Although, as some have learned recently, there are inherent risks with relying on AI to provide totally accurate information about contracts, legal information, or, really anything.

Alexa+ also aims to make navigating smart homes easier. For example, on stage, Panos Panay, Amazon’s SVP of devices and services, asked Alexa+ if anyone took his dog out or brought a package to his house in the last couple of days. The AI was able to sift through Ring camera footage and relay the information (supposedly accurately) within seconds.

Subscription Alexa has a new, friendlier tone, which I’d hope you can scale back for getting more direct, succinct information (I don’t need a voice assistant telling me I have a “great idea!”). But ultimately, Alexa’s agenda remains the same: get information about you and be a part of your purchasing process.

A vast web of partnerships

Making Alexa+ wasn’t “as easy as taking an LLM and jacking it into the original Alexa,” Daniel Rausch, VP of Amazon Alexa and Fire TV, said today.

Alexa+ relies on a pile of partnerships to provide users with real-time information and the ability to complete tasks, like schedule someone from Thumbtack to come to the house to fix the sink.

The logos of some of Alexa+'s partners on display. — Some of Alexa+’s partners on display at Amazon’s Alexa+ press conference. Credit: Scharon Harding

At launch, Alexa+ will work with “tens of thousands of other devices and services from our partners,” said Rausch. He explained:

Experts are groups of systems, capabilities, APIs, and instructions that accomplish specific tasks. So they bring together all the technology it takes to deliver on a customer’s particular request. And building any single expert is actually super complicated. And having LLMs orchestrate across hundreds of them is definitely something that’s never been done.

Amazon trained Alexa+ to use partner APIs so that Alexa+ can work with and accomplish tasks with third-party services. Many of Amazon’s partners don’t have a full set of external APIs, though. In these cases, Alexa+ gathers information through what Amazon called “agentic capabilities,” which is basically like having Alexa+ navigate the web on its own. Amazon also sees Alexa+ performing actions with third parties by having its LLM work with third-party LLMs. Developers can request previews of Alexa+’s three new SDKs as of today.

Interestingly, Amazon’s partners include over 200 publications, like Reuters, Forbes, Elle, and Ars Technica parent company Condé Nast. Based on Amazon’s announcement and the need for Alexa+ to provide real-time information to maximize usefulness, it’s likely that Amazon is relying on content licensing deals with these publishers and pulling in information via APIs and other tools. Training AI models on hundreds of publications would be expensive and time-consuming and would require frequent re-training. Amazon hasn’t confirmed training deals with these publications.

Commerce complications

Alexa+ looks like it could potentially use AI in ways that most people haven’t experienced before. However, there are obvious limitations.

To start, it seems that users need to be working with one of Amazon’s partners for the best experience. For example, Alexa+ can book a reservation for you at a restaurant—but not if that restaurant isn’t on OpenTable. In such cases, Alexa+ could, an Amazon representative said, provide you with the restaurant’s phone number, which it will have taken from the web. But I wonder if Alexa+ will prioritize Amazon partners when it comes to showing results and providing information.

Also, Amazon must still convince people that Alexa+ is a better way to buy and schedule things than your computer, phone, or even your (non-Fire) smart TV. Compared to the other types of gadgets vying to be the intermediary in our buying process, Alexa+ has serious disadvantages.

For one, most Alexa users access the AI from a speaker. However, the voice assistant’s advanced features look much easier to navigate and leverage fully with a screen, namely an Echo Show or Fire TV. I’d happily bet that there are many more people who want a laptop or phone than who want an Echo Show or Amazon TV. Other gadgets can also make it easier to dive deeper into tasks by enabling things like comparing products across competitors, understanding reviews, or marking critical parts of important documents.

Amazon is using a clever approach to dealing with fatigue with subscriptions and, more specifically, subscription spending. By including Alexa+ with Prime, Prime members may feel like they’re getting something extra for free, rather than suddenly paying for Alexa. For some who aren’t subscribed to Prime, Alexa+ could be the extra nudge needed to get them to pay for Prime. For most non-Prime members, though, the idea of paying $20 per month for Alexa is laughable, especially if you only use Alexa through an Echo.

And those with access to Alexa through a screen will still be challenged to change how they do things—critically—choosing to not rely on a technology and company with a checkered past around protecting customer privacy, including when it comes to Alexa and Amazon smart cameras.

If Alexa+ works like the demos I saw today (which, of course, isn’t a guarantee), Amazon will have succeeded in making AI gadgets that outperform expectations. Then, one of the biggest questions remaining will be: Who is willing to pay to have Amazon manage their schedules, smart homes, and purchases?

Scharon is a Senior Technology Reporter at Ars Technica writing news, reviews, and analysis on consumer gadgets and services. She’s been reporting on technology for over 10 years, with bylines at Tom’s Hardware, Channelnomics, and CRN UK.

Amazon’s subscription-based Alexa+ looks highly capable—and questionable Read More »

Google’s new AI generates hypotheses for researchers

AI, artifical intelligence, biomedical research, generative ai, Google / Paul Patrick / February 19, 2025

Over the past few years, Google has embarked on a quest to jam generative AI into every product and initiative possible. Google has robots summarizing search results, interacting with your apps, and analyzing the data on your phone. And sometimes, the output of generative AI systems can be surprisingly good despite lacking any real knowledge. But can they do science?

Google Research is now angling to turn AI into a scientist—well, a “co-scientist.” The company has a new multi-agent AI system based on Gemini 2.0 aimed at biomedical researchers that can supposedly point the way toward new hypotheses and areas of biomedical research. However, Google’s AI co-scientist boils down to a fancy chatbot.

A flesh-and-blood scientist using Google’s co-scientist would input their research goals, ideas, and references to past research, allowing the robot to generate possible avenues of research. The AI co-scientist contains multiple interconnected models that churn through the input data and access Internet resources to refine the output. Inside the tool, the different agents challenge each other to create a “self-improving loop,” which is similar to the new raft of reasoning AI models like Gemini Flash Thinking and OpenAI o3.

This is still a generative AI system like Gemini, so it doesn’t truly have any new ideas or knowledge. However, it can extrapolate from existing data to potentially make decent suggestions. At the end of the process, Google’s AI co-scientist spits out research proposals and hypotheses. The human scientist can even talk with the robot about the proposals in a chatbot interface.

Google AI co-scientist — The structure of Google’s AI co-scientist.

You can think of the AI co-scientist as a highly technical form of brainstorming. The same way you can bounce party-planning ideas off a consumer AI model, scientists will be able to conceptualize new scientific research with an AI tuned specifically for that purpose.

Testing AI science

Today’s popular AI systems have a well-known problem with accuracy. Generative AI always has something to say, even if the model doesn’t have the right training data or model weights to be helpful, and fact-checking with more AI models can’t work miracles. Leveraging its reasoning roots, the AI co-scientist conducts an internal evaluation to improve outputs, and Google says the self-evaluation ratings correlate to greater scientific accuracy.

The internal metrics are one thing, but what do real scientists think? Google had human biomedical researchers evaluate the robot’s proposals, and they reportedly rated the AI co-scientist higher than other, less specialized agentic AI systems. The experts also agreed the AI co-scientist’s outputs showed greater potential for impact and novelty compared to standard AI models.

This doesn’t mean the AI’s suggestions are all good. However, Google partnered with several universities to test some of the AI research proposals in the laboratory. For example, the AI suggested repurposing certain drugs for treating acute myeloid leukemia, and laboratory testing suggested it was a viable idea. Research at Stanford University also showed that the AI co-scientist’s ideas about treatment for liver fibrosis were worthy of further study.

This is compelling work, certainly, but calling this system a “co-scientist” is perhaps a bit grandiose. Despite the insistence from AI leaders that we’re on the verge of creating living, thinking machines, AI isn’t anywhere close to being able to do science on its own. That doesn’t mean the AI-co-scientist won’t be useful, though. Google’s new AI could help humans interpret and contextualize expansive data sets and bodies of research, even if it can’t understand or offer true insights.

Google says it wants more researchers working with this AI system in the hope it can assist with real research. Interested researchers and organizations can apply to be part of the Trusted Tester program, which provides access to the co-scientist UI as well as an API that can be integrated with existing tools.

Google’s new AI generates hypotheses for researchers Read More »

AI making up cases can get lawyers fired, scandalized law firm warns

AI, Artificial Intelligence, chatbot, chatgpt, fake AI cases, generative ai, Policy / Kris Guyer / February 19, 2025

Morgan & Morgan—which bills itself as “America’s largest injury law firm” that fights “for the people”—learned the hard way this month that even one lawyer blindly citing AI-hallucinated case law can risk sullying the reputation of an entire nationwide firm.

In a letter shared in a court filing, Morgan & Morgan’s chief transformation officer, Yath Ithayakumar, warned the firms’ more than 1,000 attorneys that citing fake AI-generated cases in court filings could be cause for disciplinary action, including “termination.”

“This is a serious issue,” Ithayakumar wrote. “The integrity of your legal work and reputation depend on it.”

Morgan & Morgan’s AI troubles were sparked in a lawsuit claiming that Walmart was involved in designing a supposedly defective hoverboard toy that allegedly caused a family’s house fire. Despite being an experienced litigator, Rudwin Ayala, the firm’s lead attorney on the case, cited eight cases in a court filing that Walmart’s lawyers could not find anywhere except on ChatGPT.

These “cited cases seemingly do not exist anywhere other than in the world of Artificial Intelligence,” Walmart’s lawyers said, urging the court to consider sanctions.

So far, the court has not ruled on possible sanctions. But Ayala was immediately dropped from the case and was replaced by his direct supervisor, T. Michael Morgan, Esq. Expressing “great embarrassment” over Ayala’s fake citations that wasted the court’s time, Morgan struck a deal with Walmart’s attorneys to pay all fees and expenses associated with replying to the errant court filing, which Morgan told the court should serve as a “cautionary tale” for both his firm and “all firms.”

Reuters found that lawyers improperly citing AI-hallucinated cases have scrambled litigation in at least seven cases in the past two years. Some lawyers have been sanctioned, including an early case last June fining lawyers $5,000 for citing chatbot “gibberish” in filings. And in at least one case in Texas, Reuters reported, a lawyer was fined $2,000 and required to attend a course on responsible use of generative AI in legal applications. But in another high-profile incident, Michael Cohen, Donald Trump’s former lawyer, avoided sanctions after Cohen accidentally gave his own attorney three fake case citations to help his defense in his criminal tax and campaign finance litigation.

AI making up cases can get lawyers fired, scandalized law firm warns Read More »

Reddit mods are fighting to keep AI slop off subreddits. They could use help.

AI, Features, generative ai, reddit, Social Media, Tech / Mike M. / February 17, 2025

Mods ask Reddit for tools as generative AI gets more popular and inconspicuous.

Credit: Aurich Lawson (based on a still from Getty Images)

Like it or not, generative AI is carving out its place in the world. And some Reddit users are definitely in the “don’t like it” category. While some subreddits openly welcome AI-generated images, videos, and text, others have responded to the growing trend by banning most or all posts made with the technology.

To better understand the reasoning and obstacles associated with these bans, Ars Technica spoke with moderators of subreddits that totally or partially ban generative AI. Almost all these volunteers described moderating against generative AI as a time-consuming challenge they expect to get more difficult as time goes on. And most are hoping that Reddit will release a tool to help their efforts.

It’s hard to know how much AI-generated content is actually on Reddit, and getting an estimate would be a large undertaking. Image library Freepik has analyzed the use of AI-generated content on social media but leaves Reddit out of its research because “it would take loads of time to manually comb through thousands of threads within the platform,” spokesperson Bella Valentini told me. For its part, Reddit doesn’t publicly disclose how many Reddit posts involve generative AI use.

To be clear, we’re not suggesting that Reddit has a large problem with generative AI use. By now, many subreddits seem to have agreed on their approach to AI-generated posts, and generative AI has not superseded the real, human voices that have made Reddit popular.

Still, mods largely agree that generative AI will likely get more popular on Reddit over the next few years, making generative AI modding increasingly important to both moderators and general users. Generative AI’s rising popularity has also had implications for Reddit the company, which in 2024 started licensing Reddit posts to train the large language models (LLMs) powering generative AI.

(Note: All the moderators I spoke with for this story requested that I use their Reddit usernames instead of their real names due to privacy concerns.)

No generative AI allowed

When it comes to anti-generative AI rules, numerous subreddits have zero-tolerance policies, while others permit posts that use generative AI if it’s combined with human elements or is executed very well. These rules task mods with identifying posts using generative AI and determining if they fit the criteria to be permitted on the subreddit.

Many subreddits have rules against posts made with generative AI because their mod teams or members consider such posts “low effort” or believe AI is counterintuitive to the subreddit’s mission of providing real human expertise and creations.

“At a basic level, generative AI removes the human element from the Internet; if we allowed it, then it would undermine the very point of r/AskHistorians, which is engagement with experts,” the mods of r/AskHistorians told me in a collective statement.

The subreddit’s goal is to provide historical information, and its mods think generative AI could make information shared on the subreddit less accurate. “[Generative AI] is likely to hallucinate facts, generate non-existent references, or otherwise provide misleading content,” the mods said. “Someone getting answers from an LLM can’t respond to follow-ups because they aren’t an expert. We have built a reputation as a reliable source of historical information, and the use of [generative AI], especially without oversight, puts that at risk.”

Similarly, Halaku, a mod of r/wheeloftime, told me that the subreddit’s mods banned generative AI because “we focus on genuine discussion.” Halaku believes AI content can’t facilitate “organic, genuine discussion” and “can drown out actual artwork being done by actual artists.”

The r/lego subreddit banned AI-generated art because it caused confusion in online fan communities and retail stores selling Lego products, r/lego mod Mescad said. “People would see AI-generated art that looked like Lego on [I]nstagram or [F]acebook and then go into the store to ask to buy it,” they explained. “We decided that our community’s dedication to authentic Lego products doesn’t include AI-generated art.”

Not all of Reddit is against generative AI, of course. Subreddits dedicated to the technology exist, and some general subreddits permit the use of generative AI in some or all forms.

“When it comes to bans, I would rather focus on hate speech, Nazi salutes, and things that actually harm the subreddits,” said 3rdusernameiveused, who moderates r/consoom and r/TeamBuilder25, which don’t ban generative AI. “AI art does not do that… If I was going to ban [something] for ‘moral’ reasons, it probably won’t be AI art.”

“Overwhelmingly low-effort slop”

Some generative AI bans are reflective of concerns that people are not being properly compensated for the content they create, which is then fed into LLM training.

Mod Mathgeek007 told me that r/DeadlockTheGame bans generative AI because its members consider it “a form of uncredited theft,” adding:

You aren’t allowed to sell/advertise the workers of others, and AI in a sense is using patterns derived from the work of others to create mockeries. I’d personally have less of an issue with it if the artists involved were credited and compensated—and there are some niche AI tools that do this.

Other moderators simply think generative AI reduces the quality of a subreddit’s content.

“It often just doesn’t look good… the art can often look subpar,” Mathgeek007 said.

Similarly, r/videos bans most AI-generated content because, according to its announcement, the videos are “annoying” and “just bad video” 99 percent of the time. In an online interview, r/videos mod Abrownn told me:

It’s overwhelmingly low-effort slop thrown together simply for views/ad revenue. The creators rarely care enough to put real effort into post-generation [or] editing of the content [and] rarely have coherent narratives [in] the videos, etc. It seems like they just throw the generated content into a video, export it, and call it a day.

An r/fakemon mod told me, “I can’t think of anything more low-effort in terms of art creation than just typing words and having it generated for you.”

Some moderators say generative AI helps people spam unwanted content on a subreddit, including posts that are irrelevant to the subreddit and posts that attack users.

“[Generative AI] content is almost entirely posted for purely self promotional/monetary reasons, and we as mods on Reddit are constantly dealing with abusive users just spamming their content without regard for the rules,” Abrownn said.

A moderator of the r/wallpaper subreddit, which permits generative AI, disagrees. The mod told me that generative AI “provides new routes for novel content” in the subreddit and questioned concerns about generative AI stealing from human artists or offering lower-quality work, saying those problems aren’t unique to generative AI:

Even in our community, we observe human-generated content that is subjectively low quality (poor camera/[P]hotoshopping skills, low-resolution source material, intentional “shitposting”). It can be argued that AI-generated content amplifies this behavior, but our experience (which we haven’t quantified) is that the rate of such behavior (whether human-generated or AI-generated content) has not changed much within our own community.

But we’re not a very active community—[about] 13 posts per day … so it very well could be a “frog in boiling water” situation.

Generative AI “wastes our time”

Many mods are confident in their ability to effectively identify posts that use generative AI. A bigger problem is how much time it takes to identify these posts and remove them.

The r/AskHistorians mods, for example, noted that all bans on the subreddit (including bans unrelated to AI) have “an appeals process,” and “making these assessments and reviewing AI appeals means we’re spending a considerable amount of time on something we didn’t have to worry about a few years ago.”

They added:

Frankly, the biggest challenge with [generative AI] usage is that it wastes our time. The time spent evaluating responses for AI use, responding to AI evangelists who try to flood our subreddit with inaccurate slop and then argue with us in modmail, [direct messages that message a subreddits’ mod team], and discussing edge cases could better be spent on other subreddit projects, like our podcast, newsletter, and AMAs, … providing feedback to users, or moderating input from users who intend to positively contribute to the community.

Several other mods I spoke with agree. Mathgeek007, for example, named “fighting AI bros” as a common obstacle. And for r/wheeloftime moderator Halaku, the biggest challenge in moderating against generative AI is “a generational one.”

“Some of the current generation don’t have a problem with it being AI because content is content, and [they think] we’re being elitist by arguing otherwise, and they want to argue about it,” they said.

A couple of mods noted that it’s less time-consuming to moderate subreddits that ban generative AI than it is to moderate those that allow posts using generative AI, depending on the context.

“On subreddits where we allowed AI, I often take a bit longer time to actually go into each post where I feel like… it’s been AI-generated to actually look at it and make a decision,” explained N3DSdude, a mod of several subreddits with rules against generative AI, including r/DeadlockTheGame.

MyarinTime, a moderator for r/lewdgames, which allows generative AI images, highlighted the challenges of identifying human-prompted generative AI content versus AI-generated content prompted by a bot:

When the AI bomb started, most of those bots started using AI content to work around our filters. Most of those bots started showing some random AI render, so it looks like you’re actually talking about a game when you’re not. There’s no way to know when those posts are legit games unless [you check] them one by one. I honestly believe it would be easier if we kick any post with [AI-]generated image… instead of checking if a button was pressed by a human or not.

Mods expect things to get worse

Most mods told me it’s pretty easy for them to detect posts made with generative AI, pointing to the distinct tone and favored phrases of AI-generated text. A few said that AI-generated video is harder to spot but still detectable. But as generative AI gets more advanced, moderators are expecting their work to get harder.

In a joint statement, r/dune mods Blue_Three and Herbalhippie said, “AI used to have a problem making hands—i.e., too many fingers, etc.—but as time goes on, this is less and less of an issue.”

R/videos’ Abrownn also wonders how easy it will be to detect AI-generated Reddit content “as AI tools advance and content becomes more lifelike.”

Mathgeek007 added:

AI is becoming tougher to spot and is being propagated at a larger rate. When AI style becomes normalized, it becomes tougher to fight. I expect generative AI to get significantly worse—until it becomes indistinguishable from ordinary art.

Moderators currently use various methods to fight generative AI, but they’re not perfect. r/AskHistorians mods, for example, use “AI detectors, which are unreliable, problematic, and sometimes require paid subscriptions, as well as our own ability to detect AI through experience and expertise,” while N3DSdude pointed to tools like Quid and GPTZero.

To manage current and future work around blocking generative AI, most of the mods I spoke with said they’d like Reddit to release a proprietary tool to help them.

“I’ve yet to see a reliable tool that can detect AI-generated video content,” Aabrown said. “Even if we did have such a tool, we’d be putting hundreds of hours of content through the tool daily, which would get rather expensive rather quickly. And we’re unpaid volunteer moderators, so we will be outgunned shortly when it comes to detecting this type of content at scale. We can only hope that Reddit will offer us a tool at some point in the near future that can help deal with this issue.”

A Reddit spokesperson told me that the company is evaluating what such a tool could look like. But Reddit doesn’t have a rule banning generative AI overall, and the spokesperson said the company doesn’t want to release a tool that would hinder expression or creativity.

For now, Reddit seems content to rely on moderators to remove AI-generated content when appropriate. Reddit’s spokesperson added:

Our moderation approach helps ensure that content on Reddit is curated by real humans. Moderators are quick to remove content that doesn’t follow community rules, including harmful or irrelevant AI-generated content—we don’t see this changing in the near future.

Making a generative AI Reddit tool wouldn’t be easy

Reddit is handling the evolving concerns around generative AI as it has handled other content issues, including by leveraging AI and machine learning tools. Reddit’s spokesperson said that this includes testing tools that can identify AI-generated media, such as images of politicians.

But making a proprietary tool that allows moderators to detect AI-generated posts won’t be easy, if it happens at all. The current tools for detecting generative AI are limited in their capabilities, and as generative AI advances, Reddit would need to provide tools that are more advanced than the AI-detecting tools that are currently available.

That would require a good deal of technical resources and would also likely present notable economic challenges for the social media platform, which only became profitable last year. And as noted by r/videos moderator Abrownn, tools for detecting AI-generated video still have a long way to go, making a Reddit-specific system especially challenging to create.

But even with a hypothetical Reddit tool, moderators would still have their work cut out for them. And because Reddit’s popularity is largely due to its content from real humans, that work is important.

Since Reddit’s inception, that has meant relying on moderators, which Reddit has said it intends to keep doing. As r/dune mods Blue_Three and herbalhippie put it, it’s in Reddit’s “best interest that much/most content remains organic in nature.” After all, Reddit’s profitability has a lot to do with how much AI companies are willing to pay to access Reddit data. That value would likely decline if Reddit posts became largely AI-generated themselves.

But providing the technology to ensure that generative AI isn’t abused on Reddit would be a large challege. For now, volunteer laborers will continue to bear the brunt of generative AI moderation.

Advance Publications, which owns Ars Technica parent Condé Nast, is the largest shareholder of Reddit.

Reddit mods are fighting to keep AI slop off subreddits. They could use help. Read More »