generative ai

elon-musk-sues-openai,-sam-altman-for-making-a-“fool”-out-of-him

Elon Musk sues OpenAI, Sam Altman for making a “fool” out of him

agi, AI, AI safety, Artificial Intelligence, chatbot, elon musk, existential risks, generative ai, GPT-4, GPT-4o, grok, microsoft, openai, Policy / /

“Altman’s long con” —

Elon Musk asks court to void Microsoft’s exclusive deal with OpenAI.

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Elon Musk and Sam Altman share the stage in 2015, the same year that Musk alleged that Altman's

Enlarge / Elon Musk and Sam Altman share the stage in 2015, the same year that Musk alleged that Altman’s “deception” began.

After withdrawing his lawsuit in June for unknown reasons, Elon Musk has revived a complaint accusing OpenAI and its CEO Sam Altman of fraudulently inducing Musk to contribute $44 million in seed funding by promising that OpenAI would always open-source its technology and prioritize serving the public good over profits as a permanent nonprofit.

Instead, Musk alleged that Altman and his co-conspirators—”preying on Musk’s humanitarian concern about the existential dangers posed by artificial intelligence”—always intended to “betray” these promises in pursuit of personal gains.

As OpenAI’s technology advanced toward artificial general intelligence (AGI) and strove to surpass human capabilities, “Altman set the bait and hooked Musk with sham altruism then flipped the script as the non-profit’s technology approached AGI and profits neared, mobilizing Defendants to turn OpenAI, Inc. into their personal piggy bank and OpenAI into a moneymaking bonanza, worth billions,” Musk’s complaint said.

Where Musk saw OpenAI as his chance to fund a meaningful rival to stop Google from controlling the most powerful AI, Altman and others “wished to launch a competitor to Google” and allegedly deceived Musk to do it. According to Musk:

The idea Altman sold Musk was that a non-profit, funded and backed by Musk, would attract world-class scientists, conduct leading AI research and development, and, as a meaningful counterweight to Google’s DeepMind in the race for Artificial General Intelligence (“AGI”), decentralize its technology by making it open source. Altman assured Musk that the non-profit structure guaranteed neutrality and a focus on safety and openness for the benefit of humanity, not shareholder value. But as it turns out, this was all hot-air philanthropy—the hook for Altman’s long con.

Without Musk’s involvement and funding during OpenAI’s “first five critical years,” Musk’s complaint said, “it is fair to say” that “there would have been no OpenAI.” And when Altman and others repeatedly approached Musk with plans to shift OpenAI to a for-profit model, Musk held strong to his morals, conditioning his ongoing contributions on OpenAI remaining a nonprofit and its tech largely remaining open source.

“Either go do something on your own or continue with OpenAI as a nonprofit,” Musk told Altman in 2018 when Altman tried to “recast the nonprofit as a moneymaking endeavor to bring in shareholders, sell equity, and raise capital.”

“I will no longer fund OpenAI until you have made a firm commitment to stay, or I’m just being a fool who is essentially providing free funding to a startup,” Musk said at the time. “Discussions are over.”

But discussions weren’t over. And now Musk seemingly does feel like a fool after OpenAI exclusively licensed GPT-4 and all “pre-AGI” technology to Microsoft in 2023, while putting up paywalls and “failing to publicly disclose the non-profit’s research and development, including details on GPT-4, GPT-4T, and GPT-4o’s architecture, hardware, training method, and training computation.” This excluded the public “from open usage of GPT-4 and related technology to advance Defendants and Microsoft’s own commercial interests,” Musk alleged.

Now Musk has revived his suit against OpenAI, asking the court to award maximum damages for OpenAI’s alleged fraud, contract breaches, false advertising, acts viewed as unfair to competition, and other violations.

He has also asked the court to determine a very technical question: whether OpenAI’s most recent models should be considered AGI and therefore Microsoft’s license voided. That’s the only way to ensure that a private corporation isn’t controlling OpenAI’s AGI models, which Musk repeatedly conditioned his financial contributions upon preventing.

“Musk contributed considerable money and resources to launch and sustain OpenAI, Inc., which was done on the condition that the endeavor would be and remain a non-profit devoted to openly sharing its technology with the public and avoid concentrating its power in the hands of the few,” Musk’s complaint said. “Defendants knowingly and repeatedly accepted Musk’s contributions in order to develop AGI, with no intention of honoring those conditions once AGI was in reach. Case in point: GPT-4, GPT-4T, and GPT-4o are all closed source and shrouded in secrecy, while Defendants actively work to transform the non-profit into a thoroughly commercial business.”

Musk wants Microsoft’s GPT-4 license voided

Musk also asked the court to null and void OpenAI’s exclusive license to Microsoft, or else determine “whether GPT-4, GPT-4T, GPT-4o, and other OpenAI next generation large language models constitute AGI and are thus excluded from Microsoft’s license.”

It’s clear that Musk considers these models to be AGI, and he’s alleged that Altman’s current control of OpenAI’s Board—after firing dissidents in 2023 whom Musk claimed tried to get Altman ousted for prioritizing profits over AI safety—gives Altman the power to obscure when OpenAI’s models constitute AGI.

Elon Musk sues OpenAI, Sam Altman for making a “fool” out of him Read More »

union-game-performers-strike-over-ai-voice-and-motion-capture-training

Union game performers strike over AI voice and motion-capture training

AI, gaming, generative ai, SAG-AFTRA, Tech, unions, video game strike, video game voice acting, Voice acting / /

Speaking into the large language model —

Use of motion-capture actors’ performances for AI training is a sticking point.

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Image of SAG-AFTRA logo next to a raised fist holding up a game controller, with

Enlarge / One day, using pixellated fonts and images to represent that something is a video game will not be a trope. Today is not that day.

SAG-AFTRA has called for a strike of all its members working in video games, with the union demanding that its next contract not allow “companies to abuse AI to the detriment of our members.”

The strike mirrors similar actions taken by SAG-AFTRA and the Writers Guild of America (WGA) last year, which, while also broader in scope than just AI, were similarly focused on concerns about AI-generated work product and the use of member work to train AI.

“Frankly, it’s stunning that these video game studios haven’t learned anything from the lessons of last year—that our members can and will stand up and demand fair and equitable treatment with respect to A.I., and the public supports us in that,” Duncan Crabtree-Ireland, chief negotiator for SAG-AFTRA, said in a statement.

During the strike, the more than 160,000 members of the union will not provide talent to games produced by Disney, Electronic Arts, Blizzard Activision, Take-Two, WB Games, and others. Not every game is affected. Some productions may have interim agreements with union workers, and others, like continually updated games that launched before the current negotiations starting September 2023, may be exempt.

The publishers and other companies issued statements to the media through a communications firm representing them. “We are disappointed the union has chosen to walk away when we are so close to a deal, and we remain prepared to resume negotiations,” a statement offered to The New York Times and other outlets read. The statement said the two sides had found common ground on 24 out of 25 proposals and that the game companies’ offer was responsive and “extends meaningful AI protections.”

The Washington Post says the biggest remaining issue involves on-camera performers, including motion capture performers. Crabtree-Ireland told the Post that while AI training protections were extended to voice performers, motion and stunt work was left out. “[A]ll of those performers deserve to have their right to have informed consent and fair compensation for the use of their image, their likeness or voice, their performance. It’s that simple,” Crabtree-Ireland said in June.

It will be difficult to know the impact of a game performer strike for some time, if ever, owing to the non-linear and secretive nature of game production. A game’s conception, development, casting, acting, announcement, and further development (and development pivots) happen on whatever timeline they happen upon.

SAG-AFTRA has a tool for searching game titles to see if they are struck for union work, but it is finicky, recognizing only specific production titles, code names, and ID numbers. Searches for Grande Theft Auto VI and 6 returned a “Game Over!” (i.e., struck), but Kotaku confirmed the game is technically unaffected, even though its parent publisher, Take-Two, is generally struck.

Video game performers in SAG-AFTRA last went on strike in 2016, that time regarding long-term royalties. The strike lasted 340 days, still the longest in that union’s history, and was settled with pay raises for actors while residuals and terms on vocal stress remained unaddressed. The impact of that strike was generally either hidden or largely blunted, as affected titles hired non-union replacements. Voice work, as noted by the original English voice for Bayonetta, remains a largely unprotected field.

Union game performers strike over AI voice and motion-capture training Read More »

alexa-had-“no-profit-timeline,”-cost-amazon-$25-billion-in-4-years

Alexa had “no profit timeline,” cost Amazon $25 billion in 4 years

Amazon, amazon alexa, generative ai, Tech / /
In this photo illustration, Echo Dot smart speaker with working Alexa with blue light ring seen displayed.

The Amazon business unit that focuses on Alexa-powered gadgets lost $25 billion between 2017 and 2021, The Wall Street Journal (WSJ) reported this week.

Amazon claims it has sold more than 500,000 Alexa devices, which included Echo speakers, Kindle readers, Fire TV sets and streaming devices, and Blink and Ring smart home security cameras. But since debuting, Alexa, like other voice assistants, has struggled to make money. In late 2022, Business Insider reported that Alexa was set to lose $10 billion that year.

WSJ said it got the $25 billion figure from “internal documents” and that it wasn’t able to determine the Devices business’s losses before or after the shared time period.

“No profit timeline”

WSJ’s report claims to offer insight into how Devices was able to bleed so much money for so long.

For one, it seems like the business unit was allowed some wiggle room in terms of financial success in the interest of innovation and the potential for long-term gains. Someone the WSJ described as being “a former longtime Devices executive” said that when Alexa first started, Amazon’s gadgets team “didn’t have a profit timeline” when launching products.

Amazon is known to have sold Echo speakers for cheap or at a loss in the hopes of making money off Alexa later. In 2019, then-Amazon Devices SVP Dave Limp, who exited the company last year, told WSJ: “We don’t have to make money when we sell you the device.” WSJ noted that this strategy has applied to other unspecified Amazon devices, too.

People tend to use Alexa for free services, though, like checking the weather or the time, not making big purchases.

“We worried we’ve hired 10,000 people and we’ve built a smart timer,” an anonymous person that WSJ said is a “former senior employee” said.

An Amazon spokesperson told WSJ that more than half of people with an Echo have shopped with it but wouldn’t provide more specifics. Per “former employees on the Alexa shopping team” that WSJ spoke with, however, the amount of shopping revenue tied to Alexa is insignificant.

In an emailed statement, an Amazon spokesperson told Ars Technica, in part:

Within Devices & Services, we’re focused on the value we create when customers use our services, not just when they buy our devices. Our Devices & Services organization has established numerous profitable businesses for Amazon and is well-positioned to continue doing so going forward.

Further hindering Alexa’s revenue are challenges in selling security and other services and the limitation of ad sales because they annoy Alexa users, WSJ reported.

Massive losses also didn’t seem to slow down product development. WSJ claimed the Devices business lost over $5 billion in 2018 yet still spent money developing the Astro consumer robot. That robot has yet to see general availability, while a business version is getting bricked just 10 months after release. Amazon Halo health trackers, which have also been bricked, and Luna game-streaming devices were also developed in 2019, when the hardware unit lost over $6 billion, per WSJ.

Amazon has laid off at least 19,000 workers since 2022, with the Devices division reportedly hit especially hard.

Alexa had “no profit timeline,” cost Amazon $25 billion in 4 years Read More »

court-ordered-penalties-for-15-teens-who-created-naked-ai-images-of-classmates

Court ordered penalties for 15 teens who created naked AI images of classmates

AI, ai child sex images, ai deepfakes, AI image generators, Artificial Intelligence, child sexual abuse materials, csam, face swapping, fake AI images, generative ai, nudity apps, Policy / /

Real consequences —

Teens ordered to attend classes on sex education and responsible use of AI.

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Court ordered penalties for 15 teens who created naked AI images of classmates

A Spanish youth court has sentenced 15 minors to one year of probation after spreading AI-generated nude images of female classmates in two WhatsApp groups.

The minors were charged with 20 counts of creating child sex abuse images and 20 counts of offenses against their victims’ moral integrity. In addition to probation, the teens will also be required to attend classes on gender and equality, as well as on the “responsible use of information and communication technologies,” a press release from the Juvenile Court of Badajoz said.

Many of the victims were too ashamed to speak up when the inappropriate fake images began spreading last year. Prior to the sentencing, a mother of one of the victims told The Guardian that girls like her daughter “were completely terrified and had tremendous anxiety attacks because they were suffering this in silence.”

The court confirmed that the teens used artificial intelligence to create images where female classmates “appear naked” by swiping photos from their social media profiles and superimposing their faces on “other naked female bodies.”

Teens using AI to sexualize and harass classmates has become an alarming global trend. Police have probed disturbing cases in both high schools and middle schools in the US, and earlier this year, the European Union proposed expanding its definition of child sex abuse to more effectively “prosecute the production and dissemination of deepfakes and AI-generated material.” Last year, US President Joe Biden issued an executive order urging lawmakers to pass more protections.

In addition to mental health impacts, victims have reported losing trust in classmates who targeted them and wanting to switch schools to avoid further contact with harassers. Others stopped posting photos online and remained fearful that the harmful AI images will resurface.

Minors targeting classmates may not realize exactly how far images can potentially spread when generating fake child sex abuse materials (CSAM); they could even end up on the dark web. An investigation by the United Kingdom-based Internet Watch Foundation (IWF) last year reported that “20,254 AI-generated images were found to have been posted to one dark web CSAM forum in a one-month period,” with more than half determined most likely to be criminal.

IWF warned that it has identified a growing market for AI-generated CSAM and concluded that “most AI CSAM found is now realistic enough to be treated as ‘real’ CSAM.” One “shocked” mother of a female classmate victimized in Spain agreed. She told The Guardian that “if I didn’t know my daughter’s body, I would have thought that image was real.”

More drastic steps to stop deepfakes

While lawmakers struggle to apply existing protections against CSAM to AI-generated images or to update laws to explicitly prosecute the offense, other more drastic solutions to prevent the harmful spread of deepfakes have been proposed.

In an op-ed for The Guardian today, journalist Lucia Osborne-Crowley advocated for laws restricting sites used to both generate and surface deepfake pornography, including regulating this harmful content when it appears on social media sites and search engines. And IWF suggested that, like jurisdictions that restrict sharing bomb-making information, lawmakers could also restrict guides instructing bad actors on how to use AI to generate CSAM.

The Malvaluna Association, which represented families of victims in Spain and broadly advocates for better sex education, told El Diario that beyond more regulations, more education is needed to stop teens motivated to use AI to attack classmates. Because the teens were ordered to attend classes, the association agreed to the sentencing measures.

“Beyond this particular trial, these facts should make us reflect on the need to educate people about equality between men and women,” the Malvaluna Association said. The group urged that today’s kids should not be learning about sex through pornography that “generates more sexism and violence.”

Teens sentenced in Spain were between the ages of 13 and 15. According to the Guardian, Spanish law prevented sentencing of minors under 14, but the youth court “can force them to take part in rehabilitation courses.”

Tech companies could also make it easier to report and remove harmful deepfakes. Ars could not immediately reach Meta for comment on efforts to combat the proliferation of AI-generated CSAM on WhatsApp, the private messaging app that was used to share fake images in Spain.

An FAQ said that “WhatsApp has zero tolerance for child sexual exploitation and abuse, and we ban users when we become aware they are sharing content that exploits or endangers children,” but it does not mention AI.

Court ordered penalties for 15 teens who created naked AI images of classmates Read More »

tool-preventing-ai-mimicry-cracked;-artists-wonder-what’s-next

Tool preventing AI mimicry cracked; artists wonder what’s next

Artificial Intelligence, artists, Features, generative ai, Glaze, image generators, Nightshade, Policy, security research, the glaze project / /
Tool preventing AI mimicry cracked; artists wonder what’s next

Aurich Lawson | Getty Images

For many artists, it’s a precarious time to post art online. AI image generators keep getting better at cheaply replicating a wider range of unique styles, and basically every popular platform is rushing to update user terms to seize permissions to scrape as much data as possible for AI training.

Defenses against AI training exist—like Glaze, a tool that adds a small amount of imperceptible-to-humans noise to images to stop image generators from copying artists’ styles. But they don’t provide a permanent solution at a time when tech companies appear determined to chase profits by building ever-more-sophisticated AI models that increasingly threaten to dilute artists’ brands and replace them in the market.

In one high-profile example just last month, the estate of Ansel Adams condemned Adobe for selling AI images stealing the famous photographer’s style, Smithsonian reported. Adobe quickly responded and removed the AI copycats. But it’s not just famous artists who risk being ripped off, and lesser-known artists may struggle to prove AI models are referencing their works. In this largely lawless world, every image uploaded risks contributing to an artist’s downfall, potentially watering down demand for their own work each time they promote new pieces online.

Unsurprisingly, artists have increasingly sought protections to diminish or dodge these AI risks. As tech companies update their products’ terms—like when Meta suddenly announced that it was training AI on a billion Facebook and Instagram user photos last December—artists frantically survey the landscape for new defenses. That’s why, counting among those offering scarce AI protections available today, The Glaze Project recently reported a dramatic surge in requests for its free tools.

Designed to help prevent style mimicry and even poison AI models to discourage data scraping without an artist’s consent or compensation, The Glaze Project’s tools are now in higher demand than ever. University of Chicago professor Ben Zhao, who created the tools, told Ars that the backlog for approving a “skyrocketing” number of requests for access is “bad.” And as he recently posted on X (formerly Twitter), an “explosion in demand” in June is only likely to be sustained as AI threats continue to evolve. For the foreseeable future, that means artists searching for protections against AI will have to wait.

Even if Zhao’s team did nothing but approve requests for WebGlaze, its invite-only web-based version of Glaze, “we probably still won’t keep up,” Zhao said. He’s warned artists on X to expect delays.

Compounding artists’ struggles, at the same time as demand for Glaze is spiking, the tool has come under attack by security researchers who claimed it was not only possible but easy to bypass Glaze’s protections. For security researchers and some artists, this attack calls into question whether Glaze can truly protect artists in these embattled times. But for thousands of artists joining the Glaze queue, the long-term future looks so bleak that any promise of protections against mimicry seems worth the wait.

Attack cracking Glaze sparks debate

Millions have downloaded Glaze already, and many artists are waiting weeks or even months for access to WebGlaze, mostly submitting requests for invites on social media. The Glaze Project vets every request to verify that each user is human and ensure bad actors don’t abuse the tools, so the process can take a while.

The team is currently struggling to approve hundreds of requests submitted daily through direct messages on Instagram and Twitter in the order they are received, and artists requesting access must be patient through prolonged delays. Because these platforms’ inboxes aren’t designed to sort messages easily, any artist who follows up on a request gets bumped to the back of the line—as their message bounces to the top of the inbox and Zhao’s team, largely volunteers, continues approving requests from the bottom up.

“This is obviously a problem,” Zhao wrote on X while discouraging artists from sending any follow-ups unless they’ve already gotten an invite. “We might have to change the way we do invites and rethink the future of WebGlaze to keep it sustainable enough to support a large and growing user base.”

Glaze interest is likely also spiking due to word of mouth. Reid Southen, a freelance concept artist for major movies, is advocating for all artists to use Glaze. Reid told Ars that WebGlaze is especially “nice” because it’s “available for free for people who don’t have the GPU power to run the program on their home machine.”

Tool preventing AI mimicry cracked; artists wonder what’s next Read More »

ai-trains-on-kids’-photos-even-when-parents-use-strict-privacy-settings

AI trains on kids’ photos even when parents use strict privacy settings

AI, ai deepfakes, AI training, Artificial Intelligence, australia, child online safety, children's online privacy, generative ai, Human rights, image generators, large language models, Policy, youtube / /

“Outrageous” —

Even unlisted YouTube videos are used to train AI, watchdog warns.

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AI trains on kids’ photos even when parents use strict privacy settings

Human Rights Watch (HRW) continues to reveal how photos of real children casually posted online years ago are being used to train AI models powering image generators—even when platforms prohibit scraping and families use strict privacy settings.

Last month, HRW researcher Hye Jung Han found 170 photos of Brazilian kids that were linked in LAION-5B, a popular AI dataset built from Common Crawl snapshots of the public web. Now, she has released a second report, flagging 190 photos of children from all of Australia’s states and territories, including indigenous children who may be particularly vulnerable to harms.

These photos are linked in the dataset “without the knowledge or consent of the children or their families.” They span the entirety of childhood, making it possible for AI image generators to generate realistic deepfakes of real Australian children, Han’s report said. Perhaps even more concerning, the URLs in the dataset sometimes reveal identifying information about children, including their names and locations where photos were shot, making it easy to track down children whose images might not otherwise be discoverable online.

That puts children in danger of privacy and safety risks, Han said, and some parents thinking they’ve protected their kids’ privacy online may not realize that these risks exist.

From a single link to one photo that showed “two boys, ages 3 and 4, grinning from ear to ear as they hold paintbrushes in front of a colorful mural,” Han could trace “both children’s full names and ages, and the name of the preschool they attend in Perth, in Western Australia.” And perhaps most disturbingly, “information about these children does not appear to exist anywhere else on the Internet”—suggesting that families were particularly cautious in shielding these boys’ identities online.

Stricter privacy settings were used in another image that Han found linked in the dataset. The photo showed “a close-up of two boys making funny faces, captured from a video posted on YouTube of teenagers celebrating” during the week after their final exams, Han reported. Whoever posted that YouTube video adjusted privacy settings so that it would be “unlisted” and would not appear in searches.

Only someone with a link to the video was supposed to have access, but that didn’t stop Common Crawl from archiving the image, nor did YouTube policies prohibiting AI scraping or harvesting of identifying information.

Reached for comment, YouTube’s spokesperson, Jack Malon, told Ars that YouTube has “been clear that the unauthorized scraping of YouTube content is a violation of our Terms of Service, and we continue to take action against this type of abuse.” But Han worries that even if YouTube did join efforts to remove images of children from the dataset, the damage has been done, since AI tools have already trained on them. That’s why—even more than parents need tech companies to up their game blocking AI training—kids need regulators to intervene and stop training before it happens, Han’s report said.

Han’s report comes a month before Australia is expected to release a reformed draft of the country’s Privacy Act. Those reforms include a draft of Australia’s first child data protection law, known as the Children’s Online Privacy Code, but Han told Ars that even people involved in long-running discussions about reforms aren’t “actually sure how much the government is going to announce in August.”

“Children in Australia are waiting with bated breath to see if the government will adopt protections for them,” Han said, emphasizing in her report that “children should not have to live in fear that their photos might be stolen and weaponized against them.”

AI uniquely harms Australian kids

To hunt down the photos of Australian kids, Han “reviewed fewer than 0.0001 percent of the 5.85 billion images and captions contained in the data set.” Because her sample was so small, Han expects that her findings represent a significant undercount of how many children could be impacted by the AI scraping.

“It’s astonishing that out of a random sample size of about 5,000 photos, I immediately fell into 190 photos of Australian children,” Han told Ars. “You would expect that there would be more photos of cats than there are personal photos of children,” since LAION-5B is a “reflection of the entire Internet.”

LAION is working with HRW to remove links to all the images flagged, but cleaning up the dataset does not seem to be a fast process. Han told Ars that based on her most recent exchange with the German nonprofit, LAION had not yet removed links to photos of Brazilian kids that she reported a month ago.

LAION declined Ars’ request for comment.

In June, LAION’s spokesperson, Nathan Tyler, told Ars that, “as a nonprofit, volunteer organization,” LAION is committed to doing its part to help with the “larger and very concerning issue” of misuse of children’s data online. But removing links from the LAION-5B dataset does not remove the images online, Tyler noted, where they can still be referenced and used in other AI datasets, particularly those relying on Common Crawl. And Han pointed out that removing the links from the dataset doesn’t change AI models that have already trained on them.

“Current AI models cannot forget data they were trained on, even if the data was later removed from the training data set,” Han’s report said.

Kids whose images are used to train AI models are exposed to a variety of harms, Han reported, including a risk that image generators could more convincingly create harmful or explicit deepfakes. In Australia last month, “about 50 girls from Melbourne reported that photos from their social media profiles were taken and manipulated using AI to create sexually explicit deepfakes of them, which were then circulated online,” Han reported.

For First Nations children—”including those identified in captions as being from the Anangu, Arrernte, Pitjantjatjara, Pintupi, Tiwi, and Warlpiri peoples”—the inclusion of links to photos threatens unique harms. Because culturally, First Nations peoples “restrict the reproduction of photos of deceased people during periods of mourning,” Han said the AI training could perpetuate harms by making it harder to control when images are reproduced.

Once an AI model trains on the images, there are other obvious privacy risks, including a concern that AI models are “notorious for leaking private information,” Han said. Guardrails added to image generators do not always prevent these leaks, with some tools “repeatedly broken,” Han reported.

LAION recommends that, if troubled by the privacy risks, parents remove images of kids online as the most effective way to prevent abuse. But Han told Ars that’s “not just unrealistic, but frankly, outrageous.”

“The answer is not to call for children and parents to remove wonderful photos of kids online,” Han said. “The call should be [for] some sort of legal protections for these photos, so that kids don’t have to always wonder if their selfie is going to be abused.”

AI trains on kids’ photos even when parents use strict privacy settings Read More »

music-industry-giants-allege-mass-copyright-violation-by-ai-firms

Music industry giants allege mass copyright violation by AI firms

AI, AI lawsuit, audio synthesis, Biz & IT, generative ai, Google, machine learning, Michael Jackson, microsoft, music synthesis, openai, Policy, Reuters, sony music, Suno, Udio, Univeral Music Group, voice synthesis, Warner Records / /

No one wants to be defeated —

Suno and Udio could face damages of up to $150,000 per song allegedly infringed.

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Michael Jackson in concert, 1986. Sony Music owns a large portion of publishing rights to Jackson's music.

Enlarge / Michael Jackson in concert, 1986. Sony Music owns a large portion of publishing rights to Jackson’s music.

Universal Music Group, Sony Music, and Warner Records have sued AI music-synthesis companies Udio and Suno for allegedly committing mass copyright infringement by using recordings owned by the labels to train music-generating AI models, reports Reuters. Udio and Suno can generate novel song recordings based on text-based descriptions of music (i.e., “a dubstep song about Linus Torvalds”).

The lawsuits, filed in federal courts in New York and Massachusetts, claim that the AI companies’ use of copyrighted material to train their systems could lead to AI-generated music that directly competes with and potentially devalues the work of human artists.

Like other generative AI models, both Udio and Suno (which we covered separately in April) rely on a broad selection of existing human-created artworks that teach a neural network the relationship between words in a written prompt and styles of music. The record labels correctly note that these companies have been deliberately vague about the sources of their training data.

Until generative AI models hit the mainstream in 2022, it was common practice in machine learning to scrape and use copyrighted information without seeking permission to do so. But now that the applications of those technologies have become commercial products themselves, rightsholders have come knocking to collect. In the case of Udio and Suno, the record labels are seeking statutory damages of up to $150,000 per song used in training.

In the lawsuit, the record labels cite specific examples of AI-generated content that allegedly re-creates elements of well-known songs, including The Temptations’ “My Girl,” Mariah Carey’s “All I Want for Christmas Is You,” and James Brown’s “I Got You (I Feel Good).” It also claims the music-synthesis models can produce vocals resembling those of famous artists, such as Michael Jackson and Bruce Springsteen.

Reuters claims it’s the first instance of lawsuits specifically targeting music-generating AI, but music companies and artists alike have been gearing up to deal with challenges the technology may pose for some time.

In May, Sony Music sent warning letters to over 700 AI companies (including OpenAI, Microsoft, Google, Suno, and Udio) and music-streaming services that prohibited any AI researchers from using its music to train AI models. In April, over 200 musical artists signed an open letter that called on AI companies to stop using AI to “devalue the rights of human artists.” And last November, Universal Music filed a copyright infringement lawsuit against Anthropic for allegedly including artists’ lyrics in its Claude LLM training data.

Similar to The New York Times’ lawsuit against OpenAI over the use of training data, the outcome of the record labels’ new suit could have deep implications for the future development of generative AI in creative fields, including requiring companies to license all musical training data used in creating music-synthesis models.

Compulsory licenses for AI training data could make AI model development economically impractical for small startups like Udio and Suno—and judging by the aforementioned open letter, many musical artists may applaud that potential outcome. But such a development would not preclude major labels from eventually developing their own AI music generators themselves, allowing only large corporations with deep pockets to control generative music tools for the foreseeable future.

Music industry giants allege mass copyright violation by AI firms Read More »

apple-intelligence-and-other-features-won’t-launch-in-the-eu-this-year

Apple Intelligence and other features won’t launch in the EU this year

AI, Apple, apple intelligence, Artificial Intelligence, dma, EU, European Commission, European Union, gaming, generative ai, ios 18, macos sequoia, privacy, Tech / /

DMA —

iPhone Mirroring and SharePlay screen sharing will also skip the EU for now.

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A photo of a hand holding an iPhone running the Image Playground experience in iOS 18

Enlarge / Features like Image Playground won’t arrive in Europe at the same time as other regions.

Apple

Three major features in iOS 18 and macOS Sequoia will not be available to European users this fall, Apple says. They include iPhone screen mirroring on the Mac, SharePlay screen sharing, and the entire Apple Intelligence suite of generative AI features.

In a statement sent to Financial Times, The Verge, and others, Apple says this decision is related to the European Union’s Digital Markets Act (DMA). Here’s the full statement, which was attributed to Apple spokesperson Fred Sainz:

Two weeks ago, Apple unveiled hundreds of new features that we are excited to bring to our users around the world. We are highly motivated to make these technologies accessible to all users. However, due to the regulatory uncertainties brought about by the Digital Markets Act (DMA), we do not believe that we will be able to roll out three of these features — iPhone Mirroring, SharePlay Screen Sharing enhancements, and Apple Intelligence — to our EU users this year.

Specifically, we are concerned that the interoperability requirements of the DMA could force us to compromise the integrity of our products in ways that risk user privacy and data security. We are committed to collaborating with the European Commission in an attempt to find a solution that would enable us to deliver these features to our EU customers without compromising their safety.

It is unclear from Apple’s statement precisely which aspects of the DMA may have led to this decision. It could be that Apple is concerned that it would be required to give competitors like Microsoft or Google access to user data collected for Apple Intelligence features and beyond, but we’re not sure.

This is not the first recent and major divergence between functionality and features for Apple devices in the EU versus other regions. Because of EU regulations, Apple opened up iOS to third-party app stores in Europe, but not in other regions. However, critics argued its compliance with that requirement was lukewarm at best, as it came with a set of restrictions and changes to how app developers could monetize their apps on the platform should they use those other storefronts.

While Apple says in the statement it’s open to finding a solution, no timeline is given. All we know is that the features won’t be available on devices in the EU this year. They’re expected to launch in other regions in the fall.

Apple Intelligence and other features won’t launch in the EU this year Read More »

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Adobe to update vague AI terms after users threaten to cancel subscriptions

adobe, Adobe Firefly, AI training, firefly ai, generative ai, Illustrator, InDesign, Photoshop, Policy / /
Adobe to update vague AI terms after users threaten to cancel subscriptions

Adobe has promised to update its terms of service to make it “abundantly clear” that the company will “never” train generative AI on creators’ content after days of customer backlash, with some saying they would cancel Adobe subscriptions over its vague terms.

Users got upset last week when an Adobe pop-up informed them of updates to terms of use that seemed to give Adobe broad permissions to access user content, take ownership of that content, or train AI on that content. The pop-up forced users to agree to these terms to access Adobe apps, disrupting access to creatives’ projects unless they immediately accepted them.

For any users unwilling to accept, canceling annual plans could trigger fees amounting to 50 percent of their remaining subscription cost. Adobe justifies collecting these fees because a “yearly subscription comes with a significant discount.”

On X (formerly Twitter), YouTuber Sasha Yanshin wrote that he canceled his Adobe license “after many years as a customer,” arguing that “no creator in their right mind can accept” Adobe’s terms that seemed to seize a “worldwide royalty-free license to reproduce, display, distribute” or “do whatever they want with any content” produced using their software.

“This is beyond insane,” Yanshin wrote on X. “You pay a huge monthly subscription, and they want to own your content and your entire business as well. Going to have to learn some new tools.”

Adobe’s design leader Scott Belsky replied, telling Yanshin that Adobe had clarified the update in a blog post and noting that Adobe’s terms for licensing content are typical for every cloud content company. But he acknowledged that those terms were written about 11 years ago and that the language could be plainer, writing that “modern terms of service in the current climate of customer concerns should evolve to address modern day concerns directly.”

Yanshin has so far not been encouraged by any of Adobe’s attempts to clarify its terms, writing that he gives “precisely zero f*cks about Adobe’s clarifications or blog posts.”

“You forced people to sign new Terms,” Yanshin told Belsky on X. “Legally, they are the only thing that matters.”

Another user in the thread using an anonymous X account also pushed back, writing, “Point to where it says in the terms that you won’t use our content for LLM or AI training? And state unequivocally that you do not have the right to use our work beyond storing it. That would go a long way.”

“Stay tuned,” Belsky wrote on X. “Unfortunately, it takes a process to update a TOS,” but “we are working on incorporating these clarifications.”

Belsky co-authored the blog this week announcing that Adobe’s terms would be updated by June 18 after a week of fielding feedback from users.

“We’ve never trained generative AI on customer content, taken ownership of a customer’s work, or allowed access to customer content beyond legal requirements,” Adobe’s blog said. “Nor were we considering any of those practices as part of the recent Terms of Use update. That said, we agree that evolving our Terms of Use to reflect our commitments to our community is the right thing to do.”

Adobe to update vague AI terms after users threaten to cancel subscriptions Read More »

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AI trained on photos from kids’ entire childhood without their consent

AI, ai dataset, ai deepfakes, Artificial Intelligence, children's online privacy, generative ai, LAION, LAION-5b, online child safety, openai, Policy / /
AI trained on photos from kids’ entire childhood without their consent

Photos of Brazilian kids—sometimes spanning their entire childhood—have been used without their consent to power AI tools, including popular image generators like Stable Diffusion, Human Rights Watch (HRW) warned on Monday.

This act poses urgent privacy risks to kids and seems to increase risks of non-consensual AI-generated images bearing their likenesses, HRW’s report said.

An HRW researcher, Hye Jung Han, helped expose the problem. She analyzed “less than 0.0001 percent” of LAION-5B, a dataset built from Common Crawl snapshots of the public web. The dataset does not contain the actual photos but includes image-text pairs derived from 5.85 billion images and captions posted online since 2008.

Among those images linked in the dataset, Han found 170 photos of children from at least 10 Brazilian states. These were mostly family photos uploaded to personal and parenting blogs most Internet surfers wouldn’t easily stumble upon, “as well as stills from YouTube videos with small view counts, seemingly uploaded to be shared with family and friends,” Wired reported.

LAION, the German nonprofit that created the dataset, has worked with HRW to remove the links to the children’s images in the dataset.

That may not completely resolve the problem, though. HRW’s report warned that the removed links are “likely to be a significant undercount of the total amount of children’s personal data that exists in LAION-5B.” Han told Wired that she fears that the dataset may still be referencing personal photos of kids “from all over the world.”

Removing the links also does not remove the images from the public web, where they can still be referenced and used in other AI datasets, particularly those relying on Common Crawl, LAION’s spokesperson, Nate Tyler, told Ars.

“This is a larger and very concerning issue, and as a nonprofit, volunteer organization, we will do our part to help,” Tyler told Ars.

Han told Ars that “Common Crawl should stop scraping children’s personal data, given the privacy risks involved and the potential for new forms of misuse.”

According to HRW’s analysis, many of the Brazilian children’s identities were “easily traceable,” due to children’s names and locations being included in image captions that were processed when building the LAION dataset.

And at a time when middle and high school-aged students are at greater risk of being targeted by bullies or bad actors turning “innocuous photos” into explicit imagery, it’s possible that AI tools may be better equipped to generate AI clones of kids whose images are referenced in AI datasets, HRW suggested.

“The photos reviewed span the entirety of childhood,” HRW’s report said. “They capture intimate moments of babies being born into the gloved hands of doctors, young children blowing out candles on their birthday cake or dancing in their underwear at home, students giving a presentation at school, and teenagers posing for photos at their high school’s carnival.”

There is less risk that the Brazilian kids’ photos are currently powering AI tools since “all publicly available versions of LAION-5B were taken down” in December, Tyler told Ars. That decision came out of an “abundance of caution” after a Stanford University report “found links in the dataset pointing to illegal content on the public web,” Tyler said, including 3,226 suspected instances of child sexual abuse material.

Han told Ars that “the version of the dataset that we examined pre-dates LAION’s temporary removal of its dataset in December 2023.” The dataset will not be available again until LAION determines that all flagged illegal content has been removed.

“LAION is currently working with the Internet Watch Foundation, the Canadian Centre for Child Protection, Stanford, and Human Rights Watch to remove all known references to illegal content from LAION-5B,” Tyler told Ars. “We are grateful for their support and hope to republish a revised LAION-5B soon.”

In Brazil, “at least 85 girls” have reported classmates harassing them by using AI tools to “create sexually explicit deepfakes of the girls based on photos taken from their social media profiles,” HRW reported. Once these explicit deepfakes are posted online, they can inflict “lasting harm,” HRW warned, potentially remaining online for their entire lives.

“Children should not have to live in fear that their photos might be stolen and weaponized against them,” Han said. “The government should urgently adopt policies to protect children’s data from AI-fueled misuse.”

Ars could not immediately reach Stable Diffusion maker Stability AI for comment.

AI trained on photos from kids’ entire childhood without their consent Read More »

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Can a technology called RAG keep AI models from making stuff up?

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Can a technology called RAG keep AI models from making stuff up?

Aurich Lawson | Getty Images

We’ve been living through the generative AI boom for nearly a year and a half now, following the late 2022 release of OpenAI’s ChatGPT. But despite transformative effects on companies’ share prices, generative AI tools powered by large language models (LLMs) still have major drawbacks that have kept them from being as useful as many would like them to be. Retrieval augmented generation, or RAG, aims to fix some of those drawbacks.

Perhaps the most prominent drawback of LLMs is their tendency toward confabulation (also called “hallucination”), which is a statistical gap-filling phenomenon AI language models produce when they are tasked with reproducing knowledge that wasn’t present in the training data. They generate plausible-sounding text that can veer toward accuracy when the training data is solid but otherwise may just be completely made up.

Relying on confabulating AI models gets people and companies in trouble, as we’ve covered in the past. In 2023, we saw two instances of lawyers citing legal cases, confabulated by AI, that didn’t exist. We’ve covered claims against OpenAI in which ChatGPT confabulated and accused innocent people of doing terrible things. In February, we wrote about Air Canada’s customer service chatbot inventing a refund policy, and in March, a New York City chatbot was caught confabulating city regulations.

So if generative AI aims to be the technology that propels humanity into the future, someone needs to iron out the confabulation kinks along the way. That’s where RAG comes in. Its proponents hope the technique will help turn generative AI technology into reliable assistants that can supercharge productivity without requiring a human to double-check or second-guess the answers.

“RAG is a way of improving LLM performance, in essence by blending the LLM process with a web search or other document look-up process” to help LLMs stick to the facts, according to Noah Giansiracusa, associate professor of mathematics at Bentley University.

Let’s take a closer look at how it works and what its limitations are.

A framework for enhancing AI accuracy

Although RAG is now seen as a technique to help fix issues with generative AI, it actually predates ChatGPT. Researchers coined the term in a 2020 academic paper by researchers at Facebook AI Research (FAIR, now Meta AI Research), University College London, and New York University.

As we’ve mentioned, LLMs struggle with facts. Google’s entry into the generative AI race, Bard, made an embarrassing error on its first public demonstration back in February 2023 about the James Webb Space Telescope. The error wiped around $100 billion off the value of parent company Alphabet. LLMs produce the most statistically likely response based on their training data and don’t understand anything they output, meaning they can present false information that seems accurate if you don’t have expert knowledge on a subject.

LLMs also lack up-to-date knowledge and the ability to identify gaps in their knowledge. “When a human tries to answer a question, they can rely on their memory and come up with a response on the fly, or they could do something like Google it or peruse Wikipedia and then try to piece an answer together from what they find there—still filtering that info through their internal knowledge of the matter,” said Giansiracusa.

But LLMs aren’t humans, of course. Their training data can age quickly, particularly in more time-sensitive queries. In addition, the LLM often can’t distinguish specific sources of its knowledge, as all its training data is blended together into a kind of soup.

In theory, RAG should make keeping AI models up to date far cheaper and easier. “The beauty of RAG is that when new information becomes available, rather than having to retrain the model, all that’s needed is to augment the model’s external knowledge base with the updated information,” said Peterson. “This reduces LLM development time and cost while enhancing the model’s scalability.”

Can a technology called RAG keep AI models from making stuff up? Read More »

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Sky voice actor says nobody ever compared her to ScarJo before OpenAI drama

AI, Artificial Intelligence, bette Midler, chatbot, chatgpt, generative ai, her movie, openai, Policy, right to publicity, scarlett johansson, sky voice, tom waits, voice misappropriation / /
Scarlett Johansson attends the Golden Heart Awards in 2023.

Enlarge / Scarlett Johansson attends the Golden Heart Awards in 2023.

OpenAI is sticking to its story that it never intended to copy Scarlett Johansson’s voice when seeking an actor for ChatGPT’s “Sky” voice mode.

The company provided The Washington Post with documents and recordings clearly meant to support OpenAI CEO Sam Altman’s defense against Johansson’s claims that Sky was made to sound “eerily similar” to her critically acclaimed voice acting performance in the sci-fi film Her.

Johansson has alleged that OpenAI hired a soundalike to steal her likeness and confirmed that she declined to provide the Sky voice. Experts have said that Johansson has a strong case should she decide to sue OpenAI for violating her right to publicity, which gives the actress exclusive rights to the commercial use of her likeness.

In OpenAI’s defense, The Post reported that the company’s voice casting call flier did not seek a “clone of actress Scarlett Johansson,” and initial voice test recordings of the unnamed actress hired to voice Sky showed that her “natural voice sounds identical to the AI-generated Sky voice.” Because of this, OpenAI has argued that “Sky’s voice is not an imitation of Scarlett Johansson.”

What’s more, an agent for the unnamed Sky actress who was cast—both granted anonymity to protect her client’s safety—confirmed to The Post that her client said she was never directed to imitate either Johansson or her character in Her. She simply used her own voice and got the gig.

The agent also provided a statement from her client that claimed that she had never been compared to Johansson before the backlash started.

This all “feels personal,” the voice actress said, “being that it’s just my natural voice and I’ve never been compared to her by the people who do know me closely.”

However, OpenAI apparently reached out to Johansson after casting the Sky voice actress. During outreach last September and again this month, OpenAI seemed to want to substitute the Sky voice actress’s voice with Johansson’s voice—which is ironically what happened when Johansson got cast to replace the original actress hired to voice her character in Her.

Altman has clarified that timeline in a statement provided to Ars that emphasized that the company “never intended” Sky to sound like Johansson. Instead, OpenAI tried to snag Johansson to voice the part after realizing—seemingly just as Her director Spike Jonze did—that the voice could potentially resonate with more people if Johansson did it.

“We are sorry to Ms. Johansson that we didn’t communicate better,” Altman’s statement said.

Johansson has not yet made any public indications that she intends to sue OpenAI over this supposed miscommunication. But if she did, legal experts told The Post and Reuters that her case would be strong because of legal precedent set in high-profile lawsuits raised by singers Bette Midler and Tom Waits blocking companies from misappropriating their voices.

Why Johansson could win if she sued OpenAI

In 1988, Bette Midler sued Ford Motor Company for hiring a soundalike to perform Midler’s song “Do You Want to Dance?” in a commercial intended to appeal to “young yuppies” by referencing popular songs from their college days. Midler had declined to do the commercial and accused Ford of exploiting her voice to endorse its product without her consent.

This groundbreaking case proved that a distinctive voice like Midler’s cannot be deliberately imitated to sell a product. It did not matter that the singer used in the commercial had used her natural singing voice, because “a number of people” told Midler that the performance “sounded exactly” like her.

Midler’s case set a powerful precedent preventing companies from appropriating parts of performers’ identities—essentially stopping anyone from stealing a well-known voice that otherwise could not be bought.

“A voice is as distinctive and personal as a face,” the court ruled, concluding that “when a distinctive voice of a professional singer is widely known and is deliberately imitated in order to sell a product, the sellers have appropriated what is not theirs.”

Like in Midler’s case, Johansson could argue that plenty of people think that the Sky voice sounds like her and that OpenAI’s product might be more popular if it had a Her-like voice mode. Comics on popular late-night shows joked about the similarity, including Johansson’s husband, Saturday Night Live comedian Colin Jost. And other people close to Johansson agreed that Sky sounded like her, Johansson has said.

Johansson’s case differs from Midler’s case seemingly primarily because of the casting timeline that OpenAI is working hard to defend.

OpenAI seems to think that because Johansson was offered the gig after the Sky voice actor was cast that she has no case to claim that they hired the other actor after she declined.

The timeline may not matter as much as OpenAI may think, though. In the 1990s, Tom Waits cited Midler’s case when he won a $2.6 million lawsuit after Frito-Lay hired a Waits impersonator to perform a song that “echoed the rhyming word play” of a Waits song in a Doritos commercial. Waits won his suit even though Frito-Lay never attempted to hire the singer before casting the soundalike.

Sky voice actor says nobody ever compared her to ScarJo before OpenAI drama Read More »