Artificial Intelligence

Elon Musk’s X tests letting users request Community Notes on bad posts

AI, Artificial Intelligence, chatbot, community notes, disinformation, elon musk, fact checking, grok, misinformation, online news, Policy, Twitter, X / Kris Guyer / July 19, 2024

Continuing to evolve the fact-checking service that launched as Twitter’s Birdwatch, X has announced that Community Notes can now be requested to clarify problematic posts spreading on Elon Musk’s platform.

X’s Community Notes account confirmed late Thursday that, due to “popular demand,” X had launched a pilot test on the web-based version of the platform. The test is active now and the same functionality will be “coming soon” to Android and iOS, the Community Notes account said.

Through the current web-based pilot, if you’re an eligible user, you can click on the “•••” menu on any X post on the web and request fact-checking from one of Community Notes’ top contributors, X explained. If X receives five or more requests within 24 hours of the post going live, a Community Note will be added.

Only X users with verified phone numbers will be eligible to request Community Notes, X said, and to start, users will be limited to five requests a day.

“The limit may increase if requests successfully result in helpful notes, or may decrease if requests are on posts that people don’t agree need a note,” X’s website said. “This helps prevent spam and keep note writers focused on posts that could use helpful notes.”

Once X receives five or more requests for a Community Note within a single day, top contributors with diverse views will be alerted to respond. On X, top contributors are constantly changing, as their notes are voted as either helpful or not. If at least 4 percent of their notes are rated “helpful,” X explained on its site, and the impact of their notes meets X standards, they can be eligible to receive alerts.

“A contributor’s Top Writer status can always change as their notes are rated by others,” X’s website said.

Ultimately, X considers notes helpful if they “contain accurate, high-quality information” and “help inform people’s understanding of the subject matter in posts,” X said on another part of its site. To gauge the former, X said that the platform partners with “professional reviewers” from the Associated Press and Reuters. X also continually monitors whether notes marked helpful by top writers match what general X users marked as helpful.

“We don’t expect all notes to be perceived as helpful by all people all the time,” X’s website said. “Instead, the goal is to ensure that on average notes that earn the status of Helpful are likely to be seen as helpful by a wide range of people from different points of view, and not only be seen as helpful by people from one viewpoint.”

X will also be allowing half of the top contributors to request notes during the pilot phase, which X said will help the platform evaluate “whether it is beneficial for Community Notes contributors to have both the ability to write notes and request notes.”

According to X, the criteria for requesting a note have intentionally been designed to be simple during the pilot stage, but X expects “these criteria to evolve, with the goal that requests are frequently found valuable to contributors, and not noisy.”

It’s hard to tell from the outside looking in how helpful Community Notes are to X users. The most recent Community Notes survey data that X points to is from 2022 when the platform was still called Twitter and the fact-checking service was still called Birdwatch.

That data showed that “on average,” users were “20–40 percent less likely to agree with the substance of a potentially misleading Tweet than someone who sees the Tweet alone.” And based on Twitter’s “internal data” at that time, the platform also estimated that “people on Twitter who see notes are, on average, 15–35 percent less likely to Like or Retweet a Tweet than someone who sees the Tweet alone.”

Elon Musk’s X tests letting users request Community Notes on bad posts Read More »

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 / Paul Patrick / July 10, 2024

Real consequences —

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

Ashley Belanger – Jul 10, 2024 8: 31 pm UTC

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.

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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 / Rejus Almole / July 4, 2024

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, 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 / Kris Guyer / July 2, 2024

“Outrageous” —

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

Ashley Belanger – Jul 2, 2024 7: 37 pm UTC

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 »

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 / Paul Patrick / June 21, 2024

DMA —

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

Samuel Axon – Jun 21, 2024 7: 34 pm UTC

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 »

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 / Rejus Almole / June 11, 2024

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 »

OpenAI backpedals on scandalous tactic to silence former employees

Artificial Intelligence, censorship, non-disparagement, openai, Policy, sam altman / Rejus Almole / May 24, 2024

That settles that? —

OpenAI releases employees from evil exit agreement in staff-wide memo.

Ashley Belanger – May 24, 2024 3: 32 pm UTC

Former and current OpenAI employees received a memo this week that the AI company hopes to end the most embarrassing scandal that Sam Altman has ever faced as OpenAI’s CEO.

The memo finally clarified for employees that OpenAI would not enforce a non-disparagement contract that employees since at least 2019 were pressured to sign within a week of termination or else risk losing their vested equity. For an OpenAI employee, that could mean losing millions for expressing even mild criticism about OpenAI’s work.

You can read the full memo below in a post on X (formerly Twitter) from Andrew Carr, a former OpenAI employee whose LinkedIn confirms that he left the company in 2021.

“I guess that settles that,” Carr wrote on X.

OpenAI faced a major public backlash when Vox revealed the unusually restrictive language in the non-disparagement clause last week after OpenAI co-founder and chief scientist Ilya Sutskever resigned, along with his superalignment team co-leader Jan Leike.

As questions swirled regarding these resignations, the former OpenAI staffers provided little explanation for why they suddenly quit. Sutskever basically wished OpenAI well, expressing confidence “that OpenAI will build AGI that is both safe and beneficial,” while Leike only offered two words: “I resigned.”

Amid an explosion of speculation about whether OpenAI was perhaps forcing out employees or doing dangerous or reckless AI work, some wondered if OpenAI’s non-disparagement agreement was keeping employees from warning the public about what was really going on at OpenAI.

According to Vox, employees had to sign the exit agreement within a week of quitting or else potentially lose millions in vested equity that could be worth more than their salaries. The extreme terms of the agreement were “fairly uncommon in Silicon Valley,” Vox found, allowing OpenAI to effectively censor former employees by requiring that they never criticize OpenAI for the rest of their lives.

“This is on me and one of the few times I’ve been genuinely embarrassed running OpenAI,” Altman posted on X, while claiming, “I did not know this was happening and I should have.”

Vox reporter Kelsey Piper called Altman’s apology “hollow,” noting that Altman had recently signed separation letters that seemed to “complicate” his claim that he was unaware of the harsh terms. Piper reviewed hundreds of pages of leaked OpenAI documents and reported that in addition to financially pressuring employees to quickly sign exit agreements, OpenAI also threatened to block employees from selling their equity.

Even requests for an extra week to review the separation agreement, which could afford the employees more time to seek legal counsel, were seemingly denied—”as recently as this spring,” Vox found.

“We want to make sure you understand that if you don’t sign, it could impact your equity,” an OpenAI representative wrote in an email to one departing employee. “That’s true for everyone, and we’re just doing things by the book.”

OpenAI Chief Strategy Officer Jason Kwon told Vox that the company began reconsidering revising this language about a month before the controversy hit.

“We are sorry for the distress this has caused great people who have worked hard for us,” Kwon told Vox. “We have been working to fix this as quickly as possible. We will work even harder to be better.”

Altman sided with OpenAI’s biggest critics, writing on X that the non-disparagement clause “should never have been something we had in any documents or communication.”

“Vested equity is vested equity, full stop,” Altman wrote.

These long-awaited updates make clear that OpenAI will never claw back vested equity if employees leave the company and then openly criticize its work (unless both parties sign a non-disparagement agreement). Prior to this week, some former employees feared steep financial retribution for sharing true feelings about the company.

One former employee, Daniel Kokotajlo, publicly posted that he refused to sign the exit agreement, even though he had no idea how to estimate how much his vested equity was worth. He guessed it represented “about 85 percent of my family’s net worth.”

And while Kokotajlo said that he wasn’t sure if the sacrifice was worth it, he still felt it was important to defend his right to speak up about the company.

“I wanted to retain my ability to criticize the company in the future,” Kokotajlo wrote.

Even mild criticism could seemingly cost employees, like Kokotajlo, who confirmed that he was leaving the company because he was “losing confidence” that OpenAI “would behave responsibly” when developing generative AI.

In OpenAI’s defense, the company confirmed that it had never enforced the exit agreements. But now, OpenAI’s spokesperson told CNBC, OpenAI is backtracking and “making important updates” to its “departure process” to eliminate any confusion the prior language caused.

“We have not and never will take away vested equity, even when people didn’t sign the departure documents,” OpenAI’s spokesperson said. “We’ll remove non-disparagement clauses from our standard departure paperwork, and we’ll release former employees from existing non-disparagement obligations unless the non-disparagement provision was mutual.”

The memo sent to current and former employees reassured everyone at OpenAI that “regardless of whether you executed the Agreement, we write to notify you that OpenAI has not canceled, and will not cancel, any Vested Units.”

“We’re incredibly sorry that we’re only changing this language now; it doesn’t reflect our values or the company we want to be,” OpenAI’s spokesperson said.

OpenAI backpedals on scandalous tactic to silence former employees Read More »

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 / Rejus Almole / May 23, 2024

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 »

Slack users horrified to discover messages used for AI training

AI, AI training, AI training data, Artificial Intelligence, chat app, machine learning, Policy, slack, slack ai / Kris Guyer / May 19, 2024

After launching Slack AI in February, Slack appears to be digging its heels in, defending its vague policy that by default sucks up customers’ data—including messages, content, and files—to train Slack’s global AI models.

According to Slack engineer Aaron Maurer, Slack has explained in a blog that the Salesforce-owned chat service does not train its large language models (LLMs) on customer data. But Slack’s policy may need updating “to explain more carefully how these privacy principles play with Slack AI,” Maurer wrote on Threads, partly because the policy “was originally written about the search/recommendation work we’ve been doing for years prior to Slack AI.”

Maurer was responding to a Threads post from engineer and writer Gergely Orosz, who called for companies to opt out of data sharing until the policy is clarified, not by a blog, but in the actual policy language.

“An ML engineer at Slack says they don’t use messages to train LLM models,” Orosz wrote. “My response is that the current terms allow them to do so. I’ll believe this is the policy when it’s in the policy. A blog post is not the privacy policy: every serious company knows this.”

The tension for users becomes clearer if you compare Slack’s privacy principles with how the company touts Slack AI.

Slack’s privacy principles specifically say that “Machine Learning (ML) and Artificial Intelligence (AI) are useful tools that we use in limited ways to enhance our product mission. To develop AI/ML models, our systems analyze Customer Data (e.g. messages, content, and files) submitted to Slack as well as other information (including usage information) as defined in our privacy policy and in your customer agreement.”

Meanwhile, Slack AI’s page says, “Work without worry. Your data is your data. We don’t use it to train Slack AI.”

Because of this incongruity, users called on Slack to update the privacy principles to make it clear how data is used for Slack AI or any future AI updates. According to a Salesforce spokesperson, the company has agreed an update is needed.

“Yesterday, some Slack community members asked for more clarity regarding our privacy principles,” Salesforce’s spokesperson told Ars. “We’ll be updating those principles today to better explain the relationship between customer data and generative AI in Slack.”

The spokesperson told Ars that the policy updates will clarify that Slack does not “develop LLMs or other generative models using customer data,” “use customer data to train third-party LLMs” or “build or train these models in such a way that they could learn, memorize, or be able to reproduce customer data.” The update will also clarify that “Slack AI uses off-the-shelf LLMs where the models don’t retain customer data,” ensuring that “customer data never leaves Slack’s trust boundary, and the providers of the LLM never have any access to the customer data.”

These changes, however, do not seem to address a key concern for users who never explicitly consented to sharing chats and other Slack content for use in AI training.

Users opting out of sharing chats with Slack

This controversial policy is not new. Wired warned about it in April, and TechCrunch reported that the policy has been in place since at least September 2023.

But widespread backlash began swelling last night on Hacker News, where Slack users called out the chat service for seemingly failing to notify users about the policy change, instead quietly opting them in by default. To critics, it felt like there was no benefit to opting in for anyone but Slack.

From there, the backlash spread to social media, where SlackHQ hastened to clarify Slack’s terms with explanations that did not seem to address all the criticism.

“I’m sorry Slack, you’re doing fucking WHAT with user DMs, messages, files, etc?” Corey Quinn, the chief cloud economist for a cost management company called Duckbill Group, posted on X. “I’m positive I’m not reading this correctly.”

SlackHQ responded to Quinn after the economist declared, “I hate this so much,” and confirmed that he had opted out of data sharing in his paid workspace.

“To clarify, Slack has platform-level machine-learning models for things like channel and emoji recommendations and search results,” SlackHQ posted. “And yes, customers can exclude their data from helping train those (non-generative) ML models. Customer data belongs to the customer.”

Later in the thread, SlackHQ noted, “Slack AI—which is our generative AI experience natively built in Slack—[and] is a separately purchased add-on that uses Large Language Models (LLMs) but does not train those LLMs on customer data.”

Slack users horrified to discover messages used for AI training Read More »

Netflix doc accused of using AI to manipulate true crime story

AI, AI images, AI-generated images, Artificial Intelligence, Jennifer pan, netflix, Policy, raw tv, True Crime, true crime documentary, what Jennifer did / Kris Guyer / April 20, 2024

Everything is not as it seems —

Producer remained vague about whether AI was used to edit photos.

Ashley Belanger – Apr 19, 2024 7: 03 pm UTC

A cropped image showing Raw TV's poster for the Netflix documentary <em>What Jennifer Did</em>, which features a long front tooth that leads critics to believe it was AI-generated.” src=”https://cdn.arstechnica.net/wp-content/uploads/2024/04/What-Jennifer-Did-Netflix-poster-cropped-800×450.jpg”></img><figcaption>
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An executive producer of the Netflix hit What Jennifer Did has responded to accusations that the true crime documentary used AI images when depicting Jennifer Pan, a woman currently imprisoned in Canada for orchestrating a murder-for-hire scheme targeting her parents.

What Jennifer Did shot to the top spot in Netflix’s global top 10 when it debuted in early April, attracting swarms of true crime fans who wanted to know more about why Pan paid hitmen $10,000 to murder her parents. But quickly the documentary became a source of controversy, as fans started noticing glaring flaws in images used in the movie, from weirdly mismatched earrings to her nose appearing to lack nostrils, the Daily Mail reported, in a post showing a plethora of examples of images from the film.

Futurism was among the first to point out that these flawed images (around the 28-minute mark of the documentary) “have all the hallmarks of an AI-generated photo, down to mangled hands and fingers, misshapen facial features, morphed objects in the background, and a far-too-long front tooth.” The image with the long front tooth was even used in Netflix’s poster for the movie.

Because the movie’s credits do not mention any uses of AI, critics called out the documentary filmmakers for potentially embellishing a movie that’s supposed to be based on real-life events.

But Jeremy Grimaldi—who is also the crime reporter who wrote a book on the case and provided the documentary with research and police footage—told the Toronto Star that the images were not AI-generated.

Grimaldi confirmed that all images of Pan used in the movie were real photos. He said that some of the images were edited, though, not to blur the lines between truth and fiction, but to protect the identity of the source of the images.

“Any filmmaker will use different tools, like Photoshop, in films,” Grimaldi told The Star. “The photos of Jennifer are real photos of her. The foreground is exactly her. The background has been anonymized to protect the source.”

While Grimaldi’s comments provide some assurance that the photos are edited versions of real photos of Pan, they are also vague enough to obscure whether AI was among the “different tools” used to edit the photos.

One photographer, Joe Foley, wrote in a post for Creative Bloq that he thought “documentary makers may have attempted to enhance old low-resolution images using AI-powered upscaling or photo restoration software to try to make them look clearer on a TV screen.”

“The problem is that even the best AI software can only take a poor-quality image so far, and such programs tend to over sharpen certain lines, resulting in strange artifacts,” Foley said.

Foley suggested that Netflix should have “at the very least” clarified that images had been altered “to avoid this kind of backlash,” noting that “any kind of manipulation of photos in a documentary is controversial because the whole point is to present things as they were.”

Hollywood’s increasing use of AI has indeed been controversial, with screenwriters’ unions opposing AI tools as “plagiarism machines” and artists stirring recent backlash over the “experimental” use of AI art in a horror film. Even using AI for a movie poster, as Civil War did, is enough to generate controversy, the Hollywood Reporter reported.

Neither Raw TV, the production company behind What Jennifer Did, nor Netflix responded to Ars’ request for comment.

Netflix doc accused of using AI to manipulate true crime story Read More »

US lawmaker proposes a public database of all AI training material

AI, Artificial Intelligence, copyright law, generative ai, generative ai disclosure act, openai, Policy, Stability AI, US Copyright Office / Paul Patrick / April 11, 2024

Who’s got the receipts? —

Proposed law would require more transparency from AI companies.

Ashley Belanger – Apr 11, 2024 8: 09 pm UTC

Amid a flurry of lawsuits over AI models’ training data, US Representative Adam Schiff (D-Calif.) has introduced a bill that would require AI companies to disclose exactly which copyrighted works are included in datasets training AI systems.

The Generative AI Disclosure Act “would require a notice to be submitted to the Register of Copyrights prior to the release of a new generative AI system with regard to all copyrighted works used in building or altering the training dataset for that system,” Schiff said in a press release.

The bill is retroactive and would apply to all AI systems available today, as well as to all AI systems to come. It would take effect 180 days after it’s enacted, requiring anyone who creates or alters a training set not only to list works referenced by the dataset, but also to provide a URL to the dataset within 30 days before the AI system is released to the public. That URL would presumably give creators a way to double-check if their materials have been used and seek any credit or compensation available before the AI tools are in use.

All notices would be kept in a publicly available online database.

Schiff described the act as championing “innovation while safeguarding the rights and contributions of creators, ensuring they are aware when their work contributes to AI training datasets.”

“This is about respecting creativity in the age of AI and marrying technological progress with fairness,” Schiff said.

Currently, creators who don’t have access to training datasets rely on AI models’ outputs to figure out if their copyrighted works may have been included in training various AI systems. The New York Times, for example, prompted ChatGPT to spit out excerpts of its articles, relying on a tactic to identify training data by asking ChatGPT to produce lines from specific articles, which OpenAI has curiously described as “hacking.”

Under Schiff’s law, The New York Times would need to consult the database to ID all articles used to train ChatGPT or any other AI system.

Any AI maker who violates the act would risk a “civil penalty in an amount not less than $5,000,” the proposed bill said.

At a hearing on artificial intelligence and intellectual property, Rep. Darrell Issa (R-Calif.)—who chairs the House Judiciary Subcommittee on Courts, Intellectual Property, and the Internet—told Schiff that his subcommittee would consider the “thoughtful” bill.

Schiff told the subcommittee that the bill is “only a first step” toward “ensuring that at a minimum” creators are “aware of when their work contributes to AI training datasets,” saying that he would “welcome the opportunity to work with members of the subcommittee” on advancing the bill.

“The rapid development of generative AI technologies has outpaced existing copyright laws, which has led to widespread use of creative content to train generative AI models without consent or compensation,” Schiff warned at the hearing.

In Schiff’s press release, Meredith Stiehm, president of the Writers Guild of America West, joined leaders from other creative groups celebrating the bill as an “important first step” for rightsholders.

“Greater transparency and guardrails around AI are necessary to protect writers and other creators” and address “the unprecedented and unauthorized use of copyrighted materials to train generative AI systems,” Stiehm said.

Until the thorniest AI copyright questions are settled, Ken Doroshow, a chief legal officer for the Recording Industry Association of America, suggested that Schiff’s bill filled an important gap by introducing “comprehensive and transparent recordkeeping” that would provide “one of the most fundamental building blocks of effective enforcement of creators’ rights.”

A senior adviser for the Human Artistry Campaign, Moiya McTier, went further, celebrating the bill as stopping AI companies from “exploiting” artists and creators.

“AI companies should stop hiding the ball when they copy creative works into AI systems and embrace clear rules of the road for recordkeeping that create a level and transparent playing field for the development and licensing of genuinely innovative applications and tools,” McTier said.

AI copyright guidance coming soon

While courts weigh copyright questions raised by artists, book authors, and newspapers, the US Copyright Office announced in March that it would be issuing guidance later this year, but the office does not seem to be prioritizing questions on AI training.

Instead, the Copyright Office will focus first on issuing guidance on deepfakes and AI outputs. This spring, the office will release a report “analyzing the impact of AI on copyright” of “digital replicas, or the use of AI to digitally replicate individuals’ appearances, voices, or other aspects of their identities.” Over the summer, another report will focus on “the copyrightability of works incorporating AI-generated material.”

Regarding “the topic of training AI models on copyrighted works as well as any licensing considerations and liability issues,” the Copyright Office did not provide a timeline for releasing guidance, only confirming that their “goal is to finalize the entire report by the end of the fiscal year.”

Once guidance is available, it could sway court opinions, although courts do not necessarily have to apply Copyright Office guidance when weighing cases.

The Copyright Office’s aspirational timeline does seem to be ahead of when at least some courts can be expected to decide on some of the biggest copyright questions for some creators. The class-action lawsuit raised by book authors against OpenAI, for example, is not expected to be resolved until February 2025, and the New York Times’ lawsuit is likely on a similar timeline. However, artists suing Stability AI face a hearing on that AI company’s motion to dismiss this May.

US lawmaker proposes a public database of all AI training material Read More »

Fake AI law firms are sending fake DMCA threats to generate fake SEO gains

AI, ai generation, Artificial Intelligence, backlinks, Biz & IT, DMCA, DMCA abuse, Generative Adversarial networks, generative ai, SEO, Tech / Kris Guyer / April 4, 2024

Dewey Fakum & Howe, LLP —

How one journalist found himself targeted by generative AI over a keyfob photo.

Kevin Purdy – Updated Apr 4, 2024 6: 50 pm UTC

Face composed of many pixellated squares, joining together — Enlarge / A person made of many parts, similar to the attorney who handles both severe criminal law and copyright takedowns for an Arizona law firm.

Getty Images

If you run a personal or hobby website, getting a copyright notice from a law firm about an image on your site can trigger some fast-acting panic. As someone who has paid to settle a news service-licensing issue before, I can empathize with anybody who wants to make this kind of thing go away.

Which is why a new kind of angle-on-an-angle scheme can seem both obvious to spot and likely effective. Ernie Smith, the prolific, ever-curious writer behind the newsletter Tedium, received a “DMCA Copyright Infringement Notice” in late March from “Commonwealth Legal,” representing the “Intellectual Property division” of Tech4Gods.

The issue was with a photo of a keyfob from legitimate photo service Unsplash used in service of a post about a strange Uber ride Smith once took. As Smith detailed in a Mastodon thread, the purported firm needed him to “add a credit to our client immediately” through a link to Tech4Gods, and said it should be “addressed in the next five business days.” Removing the image “does not conclude the matter,” and should Smith not have taken action, the putative firm would have to “activate” its case, relying on DMCA 512(c) (which, in many readings, actually does grant relief should a website owner, unaware of infringing material, “act expeditiously to remove” said material). The email unhelpfully points to the main page of the Internet Archive so that Smith might review “past usage records.”

A slice of the website for Commonwealth Legal Services, with every word of that phrase, including “for,” called into question.

Commonwealth Legal Services

There are quite a few issues with Commonwealth Legal’s request, as detailed by Smith and 404 Media. Chief among them is that Commonwealth Legal, a firm theoretically based in Arizona (which is not a commonwealth), almost certainly does not exist. Despite the 2018 copyright displayed on the site, the firm’s website domain was seemingly registered on March 1, 2024, with a Canadian IP location. The address on the firm’s site leads to a location that, to say the least, does not match the “fourth floor” indicated on the website.

While the law firm’s website is stuffed full of stock images, so are many websites for professional services. The real tell is the site’s list of attorneys, most of which, as 404 Media puts it, have “vacant, thousand-yard stares” common to AI-generated faces. AI detection firm Reality Defender told 404 Media that his service spotted AI generation in every attorneys’ image, “most likely by a Generative Adversarial Network (GAN) model.”

Then there are the attorneys’ bios, which offer surface-level competence underpinned by bizarre setups. Five of the 12 supposedly come from acclaimed law schools at Harvard, Yale, Stanford, and University of Chicago. The other seven seem to have graduated from the top five results you might get for “Arizona Law School.” Sarah Walker has a practice based on “Copyright Violation and Judicial Criminal Proceedings,” a quite uncommon pairing. Sometimes she is “upholding the rights of artists,” but she can also “handle high-stakes criminal cases.” Walker, it seems, couldn’t pick just one track at Yale Law School.

Why would someone go to the trouble of making a law firm out of NameCheap, stock art, and AI images (and seemingly copy) to send quasi-legal demands to site owners? Backlinks, that’s why. Backlinks are links from a site that Google (or others, but almost always Google) holds in high esteem to a site trying to rank up. Whether spammed, traded, generated, or demanded through a fake firm, backlinks power the search engine optimization (SEO) gray, to very dark gray, market. For all their touted algorithmic (and now AI) prowess, search engines have always had a hard time gauging backlink quality and context, so some site owners still buy backlinks.

The owner of Tech4Gods told 404 Media’s Jason Koebler that he did buy backlinks for his gadget review site (with “AI writing assistants”). He disclaimed owning the disputed image or any images and made vague suggestions that a disgruntled former contractor may be trying to poison his ranking with spam links.

Asked by Ars if he had heard back from “Commonwealth Legal” now that five business days were up, Ernie Smith tells Ars: “No, alas.”

This post was updated at 4: 50 p.m. Eastern to include Ernie Smith’s response.

Fake AI law firms are sending fake DMCA threats to generate fake SEO gains Read More »