Meta

surgeon-general’s-proposed-social-media-warning-label-for-kids-could-hurt-kids

Surgeon general’s proposed social media warning label for kids could hurt kids

Surgeon general’s proposed social media warning label for kids could hurt kids

US Surgeon General Vivek Murthy wants to put a warning label on social media platforms, alerting young users of potential mental health harms.

“It is time to require a surgeon general’s warning label on social media platforms stating that social media is associated with significant mental health harms for adolescents,” Murthy wrote in a New York Times op-ed published Monday.

Murthy argued that a warning label is urgently needed because the “mental health crisis among young people is an emergency,” and adolescents overusing social media can increase risks of anxiety and depression and negatively impact body image.

Spiking mental health issues for young people began long before the surgeon general declared a youth behavioral health crisis during the pandemic, an April report from a New York nonprofit called the United Health Fund found. Between 2010 and 2022, “adolescents ages 12–17 have experienced the highest year-over-year increase in having a major depressive episode,” the report said. By 2022, 6.7 million adolescents in the US were reporting “suffering from one or more behavioral health condition.”

However, mental health experts have maintained that the science is divided, showing that kids can also benefit from social media depending on how they use it. Murthy’s warning label seems to ignore that tension, prioritizing raising awareness of potential harms even though parents potentially restricting online access due to the proposed label could end up harming some kids. The label also would seemingly fail to acknowledge known risks to young adults, whose brains continue developing after the age of 18.

To create the proposed warning label, Murthy is seeking better data from social media companies that have not always been transparent about studying or publicizing alleged harms to kids on their platforms. Last year, a Meta whistleblower, Arturo Bejar, testified to a US Senate subcommittee that Meta overlooks obvious reforms and “continues to publicly misrepresent the level and frequency of harm that users, especially children, experience” on its platforms Facebook and Instagram.

According to Murthy, the US is past the point of accepting promises from social media companies to make their platforms safer. “We need proof,” Murthy wrote.

“Companies must be required to share all of their data on health effects with independent scientists and the public—currently they do not—and allow independent safety audits,” Murthy wrote, arguing that parents need “assurance that trusted experts have investigated and ensured that these platforms are safe for our kids.”

“A surgeon general’s warning label, which requires congressional action, would regularly remind parents and adolescents that social media has not been proved safe,” Murthy wrote.

Kids need safer platforms, not a warning label

Leaving parents to police kids’ use of platforms is unacceptable, Murthy said, because their efforts are “pitted against some of the best product engineers and most well-resourced companies in the world.”

That is nearly an impossible battle for parents, Murthy argued. If platforms are allowed to ignore harms to kids while pursuing financial gains by developing features that are laser-focused on maximizing young users’ online engagement, platforms will “likely” perpetuate the cycle of problematic use that Murthy described in his op-ed, the American Psychological Association (APA) warned this year.

Downplayed in Murthy’s op-ed, however, is the fact that social media use is not universally harmful to kids and can be beneficial to some, especially children in marginalized groups. Monitoring this tension remains a focal point of the APA’s most recent guidance, which noted that in April 2024 that “society continues to wrestle with ways to maximize the benefits of these platforms while protecting youth from the potential harms associated with them.”

“Psychological science continues to reveal benefits from social media use, as well as risks and opportunities that certain content, features, and functions present to young social media users,” APA reported.

According to the APA, platforms urgently need to enact responsible safety standards that diminish risks without restricting kids’ access to beneficial social media use.

“By early 2024, few meaningful changes to social media platforms had been enacted by industry, and no federal policies had been adopted,” the APA report said. “There remains a need for social media companies to make fundamental changes to their platforms.”

The APA has recommended a range of platform reforms, including limiting infinite scroll, imposing time limits on young users, reducing kids’ push notifications, and adding protections to shield kids from malicious actors.

Bejar agreed with the APA that platforms owe it to parents to make meaningful reforms. His ideal future would see platforms gathering more granular feedback from young users to expose harms and confront them faster. He provided senators with recommendations that platforms could use to “radically improve the experience of our children on social media” without “eliminating the joy and value they otherwise get from using such services” and without “significantly” affecting profits.

Bejar’s reforms included platforms providing young users with open-ended ways to report harassment, abuse, and harmful content that allow users to explain exactly why a contact or content was unwanted—rather than platforms limiting feedback to certain categories they want to track. This could help ensure that companies that strategically limit language in reporting categories don’t obscure the harms and also provide platforms with more information to improve services, Bejar suggested.

By improving feedback mechanisms, Bejar said, platforms could more easily adjust kids’ feeds to stop recommending unwanted content. The APA’s report agreed that this was an obvious area for platform improvement, finding that “the absence of clear and transparent processes for addressing reports of harmful content makes it harder for youth to feel protected or able to get help in the face of harmful content.”

Ultimately, the APA, Bejar, and Murthy all seem to agree that it is important to bring in outside experts to help platforms come up with better solutions, especially as technology advances. The APA warned that “AI-recommended content has the potential to be especially influential and hard to resist” for some of the youngest users online (ages 10–13).

Surgeon general’s proposed social media warning label for kids could hurt kids Read More »

meta-halts-plans-to-train-ai-on-facebook,-instagram-posts-in-eu

Meta halts plans to train AI on Facebook, Instagram posts in EU

Not so fast —

Meta was going to start training AI on Facebook and Instagram posts on June 26.

Meta halts plans to train AI on Facebook, Instagram posts in EU

Meta has apparently paused plans to process mounds of user data to bring new AI experiences to Europe.

The decision comes after data regulators rebuffed the tech giant’s claims that it had “legitimate interests” in processing European Union- and European Economic Area (EEA)-based Facebook and Instagram users’ data—including personal posts and pictures—to train future AI tools.

There’s not much information available yet on Meta’s decision. But Meta’s EU regulator, the Irish Data Protection Commission (DPC), posted a statement confirming that Meta made the move after ongoing discussions with the DPC about compliance with the EU’s strict data privacy laws, including the General Data Protection Regulation (GDPR).

“The DPC welcomes the decision by Meta to pause its plans to train its large language model using public content shared by adults on Facebook and Instagram across the EU/EEA,” the DPC said. “This decision followed intensive engagement between the DPC and Meta. The DPC, in co-operation with its fellow EU data protection authorities, will continue to engage with Meta on this issue.”

The European Center for Digital Rights, known as Noyb, had filed 11 complaints across the EU and intended to file more to stop Meta from moving forward with its AI plans. The DPC initially gave Meta AI the green light to proceed but has now made a U-turn, Noyb said.

Meta’s policy still requires update

In a blog, Meta had previously teased new AI features coming to the EU, including everything from customized stickers for chats and stories to Meta AI, a “virtual assistant you can access to answer questions, generate images, and more.” Meta had argued that training on EU users’ personal data was necessary so that AI services could reflect “the diverse cultures and languages of the European communities who will use them.”

Before the pause, the company had been hoping to rely “on the legal basis of ‘legitimate interests’” to process the data, because it’s needed “to improve AI at Meta.” But Noyb and EU data regulators had argued that Meta’s legal basis did not comply with the GDPR, with the Norwegian Data Protection Authority arguing that “the most natural thing would have been to ask the users for their consent before their posts and images are used in this way.”

Rather than ask for consent, however, Meta had given EU users until June 26 to opt out. Noyb had alleged that in going this route, Meta planned to use “dark patterns” to thwart AI opt-outs in the EU and collect as much data as possible to fuel undisclosed AI technologies. Noyb urgently argued that once users’ data is in the system, “users seem to have no option of ever having it removed.”

Noyb said that the “obvious explanation” for Meta seemingly halting its plans was pushback from EU officials, but the privacy advocacy group also warned EU users that Meta’s privacy policy has not yet been fully updated to reflect the pause.

“We welcome this development but will monitor this closely,” Max Schrems, Noyb chair, said in a statement provided to Ars. “So far there is no official change of the Meta privacy policy, which would make this commitment legally binding. The cases we filed are ongoing and will need a determination.”

Ars was not immediately able to reach Meta for comment.

Meta halts plans to train AI on Facebook, Instagram posts in EU Read More »

duckduckgo-offers-“anonymous”-access-to-ai-chatbots-through-new-service

DuckDuckGo offers “anonymous” access to AI chatbots through new service

anonymous confabulations —

DDG offers LLMs from OpenAI, Anthropic, Meta, and Mistral for factually-iffy conversations.

DuckDuckGo's AI Chat promotional image.

DuckDuckGo

On Thursday, DuckDuckGo unveiled a new “AI Chat” service that allows users to converse with four mid-range large language models (LLMs) from OpenAI, Anthropic, Meta, and Mistral in an interface similar to ChatGPT while attempting to preserve privacy and anonymity. While the AI models involved can output inaccurate information readily, the site allows users to test different mid-range LLMs without having to install anything or sign up for an account.

DuckDuckGo’s AI Chat currently features access to OpenAI’s GPT-3.5 Turbo, Anthropic’s Claude 3 Haiku, and two open source models, Meta’s Llama 3 and Mistral’s Mixtral 8x7B. The service is currently free to use within daily limits. Users can access AI Chat through the DuckDuckGo search engine, direct links to the site, or by using “!ai” or “!chat” shortcuts in the search field. AI Chat can also be disabled in the site’s settings for users with accounts.

According to DuckDuckGo, chats on the service are anonymized, with metadata and IP address removed to prevent tracing back to individuals. The company states that chats are not used for AI model training, citing its privacy policy and terms of use.

“We have agreements in place with all model providers to ensure that any saved chats are completely deleted by the providers within 30 days,” says DuckDuckGo, “and that none of the chats made on our platform can be used to train or improve the models.”

An example of DuckDuckGo AI Chat with GPT-3.5 answering a silly question in an inaccurate way.

Enlarge / An example of DuckDuckGo AI Chat with GPT-3.5 answering a silly question in an inaccurate way.

Benj Edwards

However, the privacy experience is not bulletproof because, in the case of GPT-3.5 and Claude Haiku, DuckDuckGo is required to send a user’s inputs to remote servers for processing over the Internet. Given certain inputs (i.e., “Hey, GPT, my name is Bob, and I live on Main Street, and I just murdered Bill”), a user could still potentially be identified if such an extreme need arose.

While the service appears to work well for us, there’s a question about its utility. For example, while GPT-3.5 initially wowed people when it launched with ChatGPT in 2022, it also confabulated a lot—and it still does. GPT-4 was the first major LLM to get confabulations under control to a point where the bot became more reasonably useful for some tasks (though this itself is a controversial point), but that more capable model isn’t present in DuckDuckGo’s AI Chat. Also missing are similar GPT-4-level models like Claude Opus or Google’s Gemini Ultra, likely because they are far more expensive to run. DuckDuckGo says it may roll out paid plans in the future, and those may include higher daily usage limits or access to “more advanced models.”)

It’s true that the other three models generally (and subjectively) pass GPT-3.5 in capability for coding with lower hallucinations, but they can still make things up, too. With DuckDuckGo AI Chat as it stands, the company is left with a chatbot novelty with a decent interface and the promise that your conversations with it will remain private. But what use are fully private AI conversations if they are full of errors?

Mixtral 8x7B on DuckDuckGo AI Chat when asked about the author. Everything in red boxes is sadly incorrect, but it provides an interesting fantasy scenario. It's a good example of an LLM plausibly filling gaps between concepts that are underrepresented in its training data, called confabulation. For the record, Llama 3 gives a more accurate answer.

Enlarge / Mixtral 8x7B on DuckDuckGo AI Chat when asked about the author. Everything in red boxes is sadly incorrect, but it provides an interesting fantasy scenario. It’s a good example of an LLM plausibly filling gaps between concepts that are underrepresented in its training data, called confabulation. For the record, Llama 3 gives a more accurate answer.

Benj Edwards

As DuckDuckGo itself states in its privacy policy, “By its very nature, AI Chat generates text with limited information. As such, Outputs that appear complete or accurate because of their detail or specificity may not be. For example, AI Chat cannot dynamically retrieve information and so Outputs may be outdated. You should not rely on any Output without verifying its contents using other sources, especially for professional advice (like medical, financial, or legal advice).”

So, have fun talking to bots, but tread carefully. They’ll easily “lie” to your face because they don’t understand what they are saying and are tuned to output statistically plausible information, not factual references.

DuckDuckGo offers “anonymous” access to AI chatbots through new service Read More »

“csam-generated-by-ai-is-still-csam,”-doj-says-after-rare-arrest

“CSAM generated by AI is still CSAM,” DOJ says after rare arrest

“CSAM generated by AI is still CSAM,” DOJ says after rare arrest

The US Department of Justice has started cracking down on the use of AI image generators to produce child sexual abuse materials (CSAM).

On Monday, the DOJ arrested Steven Anderegg, a 42-year-old “extremely technologically savvy” Wisconsin man who allegedly used Stable Diffusion to create “thousands of realistic images of prepubescent minors,” which were then distributed on Instagram and Telegram.

The cops were tipped off to Anderegg’s alleged activities after Instagram flagged direct messages that were sent on Anderegg’s Instagram account to a 15-year-old boy. Instagram reported the messages to the National Center for Missing and Exploited Children (NCMEC), which subsequently alerted law enforcement.

During the Instagram exchange, the DOJ found that Anderegg sent sexually explicit AI images of minors soon after the teen made his age known, alleging that “the only reasonable explanation for sending these images was to sexually entice the child.”

According to the DOJ’s indictment, Anderegg is a software engineer with “professional experience working with AI.” Because of his “special skill” in generative AI (GenAI), he was allegedly able to generate the CSAM using a version of Stable Diffusion, “along with a graphical user interface and special add-ons created by other Stable Diffusion users that specialized in producing genitalia.”

After Instagram reported Anderegg’s messages to the minor, cops seized Anderegg’s laptop and found “over 13,000 GenAI images, with hundreds—if not thousands—of these images depicting nude or semi-clothed prepubescent minors lasciviously displaying or touching their genitals” or “engaging in sexual intercourse with men.”

In his messages to the teen, Anderegg seemingly “boasted” about his skill in generating CSAM, the indictment said. The DOJ alleged that evidence from his laptop showed that Anderegg “used extremely specific and explicit prompts to create these images,” including “specific ‘negative’ prompts—that is, prompts that direct the GenAI model on what not to include in generated content—to avoid creating images that depict adults.” These go-to prompts were stored on his computer, the DOJ alleged.

Anderegg is currently in federal custody and has been charged with production, distribution, and possession of AI-generated CSAM, as well as “transferring obscene material to a minor under the age of 16,” the indictment said.

Because the DOJ suspected that Anderegg intended to use the AI-generated CSAM to groom a minor, the DOJ is arguing that there are “no conditions of release” that could prevent him from posing a “significant danger” to his community while the court mulls his case. The DOJ warned the court that it’s highly likely that any future contact with minors could go unnoticed, as Anderegg is seemingly tech-savvy enough to hide any future attempts to send minors AI-generated CSAM.

“He studied computer science and has decades of experience in software engineering,” the indictment said. “While computer monitoring may address the danger posed by less sophisticated offenders, the defendant’s background provides ample reason to conclude that he could sidestep such restrictions if he decided to. And if he did, any reoffending conduct would likely go undetected.”

If convicted of all four counts, he could face “a total statutory maximum penalty of 70 years in prison and a mandatory minimum of five years in prison,” the DOJ said. Partly because of “special skill in GenAI,” the DOJ—which described its evidence against Anderegg as “strong”—suggested that they may recommend a sentencing range “as high as life imprisonment.”

Announcing Anderegg’s arrest, Deputy Attorney General Lisa Monaco made it clear that creating AI-generated CSAM is illegal in the US.

“Technology may change, but our commitment to protecting children will not,” Monaco said. “The Justice Department will aggressively pursue those who produce and distribute child sexual abuse material—or CSAM—no matter how that material was created. Put simply, CSAM generated by AI is still CSAM, and we will hold accountable those who exploit AI to create obscene, abusive, and increasingly photorealistic images of children.”

“CSAM generated by AI is still CSAM,” DOJ says after rare arrest Read More »

robert-f-kennedy-jr.-sues-meta,-citing-chatbot’s-reply-as-evidence-of-shadowban

Robert F. Kennedy Jr. sues Meta, citing chatbot’s reply as evidence of shadowban

Screenshot from the documentary <em>Who Is Bobby Kennedy?</em>” src=”https://cdn.arstechnica.net/wp-content/uploads/2024/05/Who-Is-Bobby-Kennedy-screenshot-via-YouTube-800×422.jpg”></img><figcaption>
<p><a data-height=Enlarge / Screenshot from the documentary Who Is Bobby Kennedy?

In a lawsuit that seems determined to ignore that Section 230 exists, Robert F. Kennedy Jr. has sued Meta for allegedly shadowbanning his million-dollar documentary, Who Is Bobby Kennedy? and preventing his supporters from advocating for his presidential campaign.

According to Kennedy, Meta is colluding with the Biden administration to sway the 2024 presidential election by suppressing Kennedy’s documentary and making it harder to support Kennedy’s candidacy. This allegedly has caused “substantial donation losses,” while also violating the free speech rights of Kennedy, his supporters, and his film’s production company, AV24.

Meta had initially restricted the documentary on Facebook and Instagram but later fixed the issue after discovering that the film was mistakenly flagged by the platforms’ automated spam filters.

But Kennedy’s complaint claimed that Meta is still “brazenly censoring speech” by “continuing to throttle, de-boost, demote, and shadowban the film.” In an exhibit, Kennedy’s lawyers attached screenshots representing “hundreds” of Facebook and Instagram users whom Meta allegedly sent threats, intimidated, and sanctioned after they shared the documentary.

Some of these users remain suspended on Meta platforms, the complaint alleged. Others whose temporary suspensions have been lifted claimed that their posts are still being throttled, though, and Kennedy’s lawyers earnestly insisted that an exchange with Meta’s chatbot proves it.

Two days after the documentary’s release, Kennedy’s team apparently asked the Meta AI assistant, “When users post the link whoisbobbykennedy.com, can their followers see the post in their feeds?”

“I can tell you that the link is currently restricted by Meta,” the chatbot answered.

Chatbots, of course, are notoriously inaccurate sources of information, and Meta AI’s terms of service note this. In a section labeled “accuracy,” Meta warns that chatbot responses “may not reflect accurate, complete, or current information” and should always be verified.

Perhaps more significantly, there is little reason to think that Meta’s chatbot would have access to information about internal content moderation decisions.

Techdirt’s Mike Masnick mocked Kennedy’s reliance on the chatbot in the case. He noted that Kennedy seemed to have no evidence of the alleged shadow-banning, while there’s plenty of evidence that Meta’s spam filters accidentally remove non-violative content all the time.

Meta’s chatbot is “just a probabilistic stochastic parrot, repeating a probable sounding answer to users’ questions,” Masnick wrote. “And these idiots think it’s meaningful evidence. This is beyond embarrassing.”

Neither Meta nor Kennedy’s lawyer, Jed Rubenfeld, responded to Ars’ request to comment.

Robert F. Kennedy Jr. sues Meta, citing chatbot’s reply as evidence of shadowban Read More »

concerns-over-addicted-kids-spur-probe-into-meta-and-its-use-of-dark-patterns

Concerns over addicted kids spur probe into Meta and its use of dark patterns

Protecting the vulnerable —

EU is concerned Meta isn’t doing enough to protect children using its apps.

An iPhone screen displays the app icons for WhatsApp, Messenger, Instagram, and Facebook in a folder titled

Getty Images | Chesnot

Brussels has opened an in-depth probe into Meta over concerns it is failing to do enough to protect children from becoming addicted to social media platforms such as Instagram.

The European Commission, the EU’s executive arm, announced on Thursday it would look into whether the Silicon Valley giant’s apps were reinforcing “rabbit hole” effects, where users get drawn ever deeper into online feeds and topics.

EU investigators will also look into whether Meta, which owns Facebook and Instagram, is complying with legal obligations to provide appropriate age-verification tools to prevent children from accessing inappropriate content.

The probe is the second into the company under the EU’s Digital Services Act. The landmark legislation is designed to police content online, with sweeping new rules on the protection of minors.

It also has mechanisms to force Internet platforms to reveal how they are tackling misinformation and propaganda.

The DSA, which was approved last year, imposes new obligations on very large online platforms with more than 45 million users in the EU. If Meta is found to have broken the law, Brussels can impose fines of up to 6 percent of a company’s global annual turnover.

Repeat offenders can even face bans in the single market as an extreme measure to enforce the rules.

Thierry Breton, commissioner for internal market, said the EU was “not convinced” that Meta “has done enough to comply with the DSA obligations to mitigate the risks of negative effects to the physical and mental health of young Europeans on its platforms Facebook and Instagram.”

“We are sparing no effort to protect our children,” Breton added.

Meta said: “We want young people to have safe, age-appropriate experiences online and have spent a decade developing more than 50 tools and policies designed to protect them. This is a challenge the whole industry is facing, and we look forward to sharing details of our work with the European Commission.”

In the investigation, the commission said it would focus on whether Meta’s platforms were putting in place “appropriate and proportionate measures to ensure a high level of privacy, safety, and security for minors.” It added that it was placing special emphasis on default privacy settings for children.

Last month, the EU opened the first probe into Meta under the DSA over worries the social media giant is not properly curbing disinformation from Russia and other countries.

Brussels is especially concerned whether the social media company’s platforms are properly moderating content from Russian sources that may try to destabilize upcoming elections across Europe.

Meta defended its moderating practices and said it had appropriate systems in place to stop the spread of disinformation on its platforms.

© 2024 The Financial Times Ltd. All rights reserved. Not to be redistributed, copied, or modified in any way.

Concerns over addicted kids spur probe into Meta and its use of dark patterns Read More »

professor-sues-meta-to-allow-release-of-feed-killing-tool-for-facebook

Professor sues Meta to allow release of feed-killing tool for Facebook

Professor sues Meta to allow release of feed-killing tool for Facebook

themotioncloud/Getty Images

Ethan Zuckerman wants to release a tool that would allow Facebook users to control what appears in their newsfeeds. His privacy-friendly browser extension, Unfollow Everything 2.0, is designed to essentially give users a switch to turn the newsfeed on and off whenever they want, providing a way to eliminate or curate the feed.

Ethan Zuckerman, a professor at University of Massachusetts Amherst, is suing Meta to release a tool allowing Facebook users to

Ethan Zuckerman, a professor at University of Massachusetts Amherst, is suing Meta to release a tool allowing Facebook users to “unfollow everything.” (Photo by Lorrie LeJeune)

The tool is nearly ready to be released, Zuckerman told Ars, but the University of Massachusetts Amherst associate professor is afraid that Facebook owner Meta might threaten legal action if he goes ahead. And his fears appear well-founded. In 2021, Meta sent a cease-and-desist letter to the creator of the original Unfollow Everything, Louis Barclay, leading that developer to shut down his tool after thousands of Facebook users had eagerly downloaded it.

Zuckerman is suing Meta, asking a US district court in California to invalidate Meta’s past arguments against developers like Barclay and rule that Meta would have no grounds to sue if he released his tool.

Zuckerman insists that he’s “suing Facebook to make it better.” In picking this unusual legal fight with Meta, the professor—seemingly for the first time ever—is attempting to tip Section 230’s shield away from Big Tech and instead protect third-party developers from giant social media platforms.

To do this, Zuckerman is asking the court to consider a novel Section 230 argument relating to an overlooked provision of the law that Zuckerman believes protects the development of third-party tools that allow users to curate their newsfeeds to avoid objectionable content. His complaint cited case law and argued:

Section 230(c)(2)(B) immunizes from legal liability “a provider of software or enabling tools that filter, screen, allow, or disallow content that the provider or user considers obscene, lewd, lascivious, filthy, excessively violent, harassing, or otherwise objectionable.” Through this provision, Congress intended to promote the development of filtering tools that enable users to curate their online experiences and avoid content they would rather not see.

Unfollow Everything 2.0 falls in this “safe harbor,” Zuckerman argues, partly because “the purpose of the tool is to allow users who find the newsfeed objectionable, or who find the specific sequencing of posts within their newsfeed objectionable, to effectively turn off the feed.”

Ramya Krishnan, a senior staff attorney at the Knight Institute who helped draft Zuckerman’s complaint, told Ars that some Facebook users are concerned that the newsfeed “prioritizes inflammatory and sensational speech,” and they “may not want to see that kind of content.” By turning off the feed, Facebook users could choose to use the platform the way it was originally designed, avoiding being served objectionable content by blanking the newsfeed and manually navigating to only the content they want to see.

“Users don’t have to accept Facebook as it’s given to them,” Krishnan said in a press release provided to Ars. “The same statute that immunizes Meta from liability for the speech of its users gives users the right to decide what they see on the platform.”

Zuckerman, who considers himself “old to the Internet,” uses Facebook daily and even reconnected with and began dating his now-wife on the platform. He has a “soft spot” in his heart for Facebook and still finds the platform useful to keep in touch with friends and family.

But while he’s “never been in the ‘burn it all down’ camp,” he has watched social media evolve to give users less control over their feeds and believes “that the dominance of a small number of social media companies tends to create the illusion that the business model adopted by them is inevitable,” his complaint said.

Professor sues Meta to allow release of feed-killing tool for Facebook Read More »

critics-question-tech-heavy-lineup-of-new-homeland-security-ai-safety-board

Critics question tech-heavy lineup of new Homeland Security AI safety board

Adventures in 21st century regulation —

CEO-heavy board to tackle elusive AI safety concept and apply it to US infrastructure.

A modified photo of a 1956 scientist carefully bottling

On Friday, the US Department of Homeland Security announced the formation of an Artificial Intelligence Safety and Security Board that consists of 22 members pulled from the tech industry, government, academia, and civil rights organizations. But given the nebulous nature of the term “AI,” which can apply to a broad spectrum of computer technology, it’s unclear if this group will even be able to agree on what exactly they are safeguarding us from.

President Biden directed DHS Secretary Alejandro Mayorkas to establish the board, which will meet for the first time in early May and subsequently on a quarterly basis.

The fundamental assumption posed by the board’s existence, and reflected in Biden’s AI executive order from October, is that AI is an inherently risky technology and that American citizens and businesses need to be protected from its misuse. Along those lines, the goal of the group is to help guard against foreign adversaries using AI to disrupt US infrastructure; develop recommendations to ensure the safe adoption of AI tech into transportation, energy, and Internet services; foster cross-sector collaboration between government and businesses; and create a forum where AI leaders to share information on AI security risks with the DHS.

It’s worth noting that the ill-defined nature of the term “Artificial Intelligence” does the new board no favors regarding scope and focus. AI can mean many different things: It can power a chatbot, fly an airplane, control the ghosts in Pac-Man, regulate the temperature of a nuclear reactor, or play a great game of chess. It can be all those things and more, and since many of those applications of AI work very differently, there’s no guarantee any two people on the board will be thinking about the same type of AI.

This confusion is reflected in the quotes provided by the DHS press release from new board members, some of whom are already talking about different types of AI. While OpenAI, Microsoft, and Anthropic are monetizing generative AI systems like ChatGPT based on large language models (LLMs), Ed Bastian, the CEO of Delta Air Lines, refers to entirely different classes of machine learning when he says, “By driving innovative tools like crew resourcing and turbulence prediction, AI is already making significant contributions to the reliability of our nation’s air travel system.”

So, defining the scope of what AI exactly means—and which applications of AI are new or dangerous—might be one of the key challenges for the new board.

A roundtable of Big Tech CEOs attracts criticism

For the inaugural meeting of the AI Safety and Security Board, the DHS selected a tech industry-heavy group, populated with CEOs of four major AI vendors (Sam Altman of OpenAI, Satya Nadella of Microsoft, Sundar Pichai of Alphabet, and Dario Amodei of Anthopic), CEO Jensen Huang of top AI chipmaker Nvidia, and representatives from other major tech companies like IBM, Adobe, Amazon, Cisco, and AMD. There are also reps from big aerospace and aviation: Northrop Grumman and Delta Air Lines.

Upon reading the announcement, some critics took issue with the board composition. On LinkedIn, founder of The Distributed AI Research Institute (DAIR) Timnit Gebru especially criticized OpenAI’s presence on the board and wrote, “I’ve now seen the full list and it is hilarious. Foxes guarding the hen house is an understatement.”

Critics question tech-heavy lineup of new Homeland Security AI safety board Read More »

customers-say-meta’s-ad-buying-ai-blows-through-budgets-in-a-matter-of-hours

Customers say Meta’s ad-buying AI blows through budgets in a matter of hours

Spending money is just so hard … can’t a computer do it for me? —

Based on your point of view, the AI either doesn’t work or works too well.

AI is here to terminate your bank account.

Enlarge / AI is here to terminate your bank account.

Carolco Pictures

Give the AI access to your credit card, they said. It’ll be fine, they said. Users of Meta’s ad platform who followed that advice have been getting burned by an AI-powered ad purchasing system, according to The Verge. The idea was to use a Meta-developed AI to automatically set up ads and spend your ad budget, saving you the hassle of making decisions about your ad campaign. Apparently, the AI funnels money to Meta a little too well: Customers say it burns, though, what should be daily ad budgets in a matter of hours, and costs are inflated as much as 10-fold.

The AI-powered software in question is the “Advantage+ Shopping Campaign.” The system is supposed to automate a lot of ad setup for you, mixing and matching various creative elements and audience targets. The power of AI-powered advertising (Google has a similar product) is that the ad platform can get instant feedback on its generated ads via click-through rates. You give it a few guard rails, and it can try hundreds or thousands of combinations to find the most clickable ad at a speed and efficiency no human could match. That’s the theory, anyway.

The Verge spoke to “several marketers and businesses” with similar stories of being hit by an AI-powered spending spree once they let Meta’s system take over a campaign. The description of one account says the AI “had blown through roughly 75 percent of the daily ad budgets for both clients in under a couple of hours” and that “the ads’ CPMs, or cost per impressions, were roughly 10 times higher than normal.” Meanwhile, the revenue earned from those AI-powered ads was “nearly zero.” The report says, “Small businesses have seen their ad dollars get wiped out and wasted as a result, and some have said the bouts of overspending are driving them from Meta’s platforms.”

Meta’s Advantage+ sales pitch promises to “Use machine learning to identify and aim for your highest value customers across all of Meta’s family of apps and services, with minimal input.” The service can “Automatically test up to 150 creative combinations and deliver the highest performing ads.” Meta promises that “on average, companies have seen a 17 percent reduction in cost per action [an action is typically a purchase, registration, or sign-up] and a 32 percent increase in return on ad spend.”

In response to the complaints, a Meta spokesperson told The Verge the company had fixed “a few technical issues” and that “Our ads system is working as expected for the vast majority of advertisers. We recently fixed a few technical issues and are researching a small amount of additional reports from advertisers to ensure the best possible results for businesses using our apps.” The Verge got that statement a few weeks ago, though, and advertisers are still having issues. The report describes the service as “unpredictable” and says what “other marketers thought was a one-time glitch by Advantage Plus ended up becoming a recurring incident for weeks.”

To make matters worse, layoffs in Meta’s customer service department mean it’s been difficult to get someone at Meta to deal with the AI’s spending sprees. Some accounts report receiving refunds after complaining, but it can take several tries to get someone at customer service to deal with you and upward of a month to receive a refund. Some customers quoted in the report have decided to return to pre-AI, non-automated way of setting up a Meta ad campaign, which can take “an extra 10 to 20 minutes.”

Customers say Meta’s ad-buying AI blows through budgets in a matter of hours Read More »

apple-releases-eight-small-ai-language-models-aimed-at-on-device-use

Apple releases eight small AI language models aimed at on-device use

Inside the Apple core —

OpenELM mirrors efforts by Microsoft to make useful small AI language models that run locally.

An illustration of a robot hand tossing an apple to a human hand.

Getty Images

In the world of AI, what might be called “small language models” have been growing in popularity recently because they can be run on a local device instead of requiring data center-grade computers in the cloud. On Wednesday, Apple introduced a set of tiny source-available AI language models called OpenELM that are small enough to run directly on a smartphone. They’re mostly proof-of-concept research models for now, but they could form the basis of future on-device AI offerings from Apple.

Apple’s new AI models, collectively named OpenELM for “Open-source Efficient Language Models,” are currently available on the Hugging Face under an Apple Sample Code License. Since there are some restrictions in the license, it may not fit the commonly accepted definition of “open source,” but the source code for OpenELM is available.

On Tuesday, we covered Microsoft’s Phi-3 models, which aim to achieve something similar: a useful level of language understanding and processing performance in small AI models that can run locally. Phi-3-mini features 3.8 billion parameters, but some of Apple’s OpenELM models are much smaller, ranging from 270 million to 3 billion parameters in eight distinct models.

In comparison, the largest model yet released in Meta’s Llama 3 family includes 70 billion parameters (with a 400 billion version on the way), and OpenAI’s GPT-3 from 2020 shipped with 175 billion parameters. Parameter count serves as a rough measure of AI model capability and complexity, but recent research has focused on making smaller AI language models as capable as larger ones were a few years ago.

The eight OpenELM models come in two flavors: four as “pretrained” (basically a raw, next-token version of the model) and four as instruction-tuned (fine-tuned for instruction following, which is more ideal for developing AI assistants and chatbots):

OpenELM features a 2048-token maximum context window. The models were trained on the publicly available datasets RefinedWeb, a version of PILE with duplications removed, a subset of RedPajama, and a subset of Dolma v1.6, which Apple says totals around 1.8 trillion tokens of data. Tokens are fragmented representations of data used by AI language models for processing.

Apple says its approach with OpenELM includes a “layer-wise scaling strategy” that reportedly allocates parameters more efficiently across each layer, saving not only computational resources but also improving the model’s performance while being trained on fewer tokens. According to Apple’s released white paper, this strategy has enabled OpenELM to achieve a 2.36 percent improvement in accuracy over Allen AI’s OLMo 1B (another small language model) while requiring half as many pre-training tokens.

An table comparing OpenELM with other small AI language models in a similar class, taken from the OpenELM research paper by Apple.

Enlarge / An table comparing OpenELM with other small AI language models in a similar class, taken from the OpenELM research paper by Apple.

Apple

Apple also released the code for CoreNet, a library it used to train OpenELM—and it also included reproducible training recipes that allow the weights (neural network files) to be replicated, which is unusual for a major tech company so far. As Apple says in its OpenELM paper abstract, transparency is a key goal for the company: “The reproducibility and transparency of large language models are crucial for advancing open research, ensuring the trustworthiness of results, and enabling investigations into data and model biases, as well as potential risks.”

By releasing the source code, model weights, and training materials, Apple says it aims to “empower and enrich the open research community.” However, it also cautions that since the models were trained on publicly sourced datasets, “there exists the possibility of these models producing outputs that are inaccurate, harmful, biased, or objectionable in response to user prompts.”

While Apple has not yet integrated this new wave of AI language model capabilities into its consumer devices, the upcoming iOS 18 update (expected to be revealed in June at WWDC) is rumored to include new AI features that utilize on-device processing to ensure user privacy—though the company may potentially hire Google or OpenAI to handle more complex, off-device AI processing to give Siri a long-overdue boost.

Apple releases eight small AI language models aimed at on-device use Read More »

meta-debuts-horizon-os,-with-asus,-lenovo,-and-microsoft-on-board

Meta debuts Horizon OS, with Asus, Lenovo, and Microsoft on board

Face Operating Systems —

Rivalry with Apple now mirrors the Android/iOS competition more than ever.

The Meta Quest Pro at a Best Buy demo station in October 2022.

Enlarge / The Meta Quest Pro at a Best Buy demo station in October 2022.

Meta will open up the operating system that runs on its Quest mixed reality headsets to other technology companies, it announced today.

What was previously simply called Quest software will be called Horizon OS, and the goal will be to move beyond the general-use Quest devices to more purpose-specific devices, according to an Instagram video from Meta CEO Mark Zuckerberg.

There will be headsets focused purely on watching TV and movies on virtual screens, with the emphasis on high-end OLED displays. There will also be headsets that are designed to be as light as possible at the expense of performance for productivity and exercise uses. And there will be gaming-oriented ones.

The announcement named three partners to start. Asus will produce a gaming headset under its Republic of Gamers (ROG) brand, Lenovo will make general purpose headsets with an emphasize on “productivity, learning, and entertainment,” and Xbox and Meta will team up to deliver a special edition of the Meta Quest that will come bundled with an Xbox controller and Xbox Cloud Gaming and Game Pass.

Users running Horizon OS devices from different manufacturers will be able to stay connected in the operating system’s social layer of “identities, avatars, social graphs, and friend groups” and will be able to enjoy shared virtual spaces together across devices.

The announcement comes after Meta became an early leader in the relatively small but interesting consumer mixed reality space but with diminishing returns on new devices as the market saturates.

Further, Apple recently entered the fray with its Vision Pro headset. The Vision Pro is not really a direct competitor to Meta’s Quest devices today—it’s far more expensive and loaded with higher-end tech—but it may only be the opening volley in a long competition between the companies.

Meta’s decision to make Horizon OS a more open platform for partner OEMs in the face of Apple’s usual focus on owning and integrating as much of the software, hardware, and services in its device as it can mirrors the smartphone market. There, Google’s Android (on which Horizon OS is based) runs on a variety of devices from a wide range of companies, while Apple’s iOS runs only on Apple’s own iPhones.

Meta also says it is working on a new spatial app framework to make it easier for developers with experience on mobile to start making mixed reality apps for Horizon OS and that it will start “removing the barriers between the Meta Horizon Store and App Lab, which lets any developer who meets basic technical and content requirements release software on the platform.”

Pricing, specs, and release dates have not been announced for any of the new devices. Zuckerberg admitted it’s “probably going to take a couple of years” for this ecosystem of hardware devices to roll out.

Meta debuts Horizon OS, with Asus, Lenovo, and Microsoft on board Read More »

llms-keep-leaping-with-llama-3,-meta’s-newest-open-weights-ai-model

LLMs keep leaping with Llama 3, Meta’s newest open-weights AI model

computer-powered word generator —

Zuckerberg says new AI model “was still learning” when Meta stopped training.

A group of pink llamas on a pixelated background.

On Thursday, Meta unveiled early versions of its Llama 3 open-weights AI model that can be used to power text composition, code generation, or chatbots. It also announced that its Meta AI Assistant is now available on a website and is going to be integrated into its major social media apps, intensifying the company’s efforts to position its products against other AI assistants like OpenAI’s ChatGPT, Microsoft’s Copilot, and Google’s Gemini.

Like its predecessor, Llama 2, Llama 3 is notable for being a freely available, open-weights large language model (LLM) provided by a major AI company. Llama 3 technically does not quality as “open source” because that term has a specific meaning in software (as we have mentioned in other coverage), and the industry has not yet settled on terminology for AI model releases that ship either code or weights with restrictions (you can read Llama 3’s license here) or that ship without providing training data. We typically call these releases “open weights” instead.

At the moment, Llama 3 is available in two parameter sizes: 8 billion (8B) and 70 billion (70B), both of which are available as free downloads through Meta’s website with a sign-up. Llama 3 comes in two versions: pre-trained (basically the raw, next-token-prediction model) and instruction-tuned (fine-tuned to follow user instructions). Each has a 8,192 token context limit.

A screenshot of the Meta AI Assistant website on April 18, 2024.

Enlarge / A screenshot of the Meta AI Assistant website on April 18, 2024.

Benj Edwards

Meta trained both models on two custom-built, 24,000-GPU clusters. In a podcast interview with Dwarkesh Patel, Meta CEO Mark Zuckerberg said that the company trained the 70B model with around 15 trillion tokens of data. Throughout the process, the model never reached “saturation” (that is, it never hit a wall in terms of capability increases). Eventually, Meta pulled the plug and moved on to training other models.

“I guess our prediction going in was that it was going to asymptote more, but even by the end it was still leaning. We probably could have fed it more tokens, and it would have gotten somewhat better,” Zuckerberg said on the podcast.

Meta also announced that it is currently training a 400B parameter version of Llama 3, which some experts like Nvidia’s Jim Fan think may perform in the same league as GPT-4 Turbo, Claude 3 Opus, and Gemini Ultra on benchmarks like MMLU, GPQA, HumanEval, and MATH.

Speaking of benchmarks, we have devoted many words in the past to explaining how frustratingly imprecise benchmarks can be when applied to large language models due to issues like training contamination (that is, including benchmark test questions in the training dataset), cherry-picking on the part of vendors, and an inability to capture AI’s general usefulness in an interactive session with chat-tuned models.

But, as expected, Meta provided some benchmarks for Llama 3 that list results from MMLU (undergraduate level knowledge), GSM-8K (grade-school math), HumanEval (coding), GPQA (graduate-level questions), and MATH (math word problems). These show the 8B model performing well compared to open-weights models like Google’s Gemma 7B and Mistral 7B Instruct, and the 70B model also held its own against Gemini Pro 1.5 and Claude 3 Sonnet.

A chart of instruction-tuned Llama 3 8B and 70B benchmarks provided by Meta.

Enlarge / A chart of instruction-tuned Llama 3 8B and 70B benchmarks provided by Meta.

Meta says that the Llama 3 model has been enhanced with capabilities to understand coding (like Llama 2) and, for the first time, has been trained with both images and text—though it currently outputs only text. According to Reuters, Meta Chief Product Officer Chris Cox noted in an interview that more complex processing abilities (like executing multi-step plans) are expected in future updates to Llama 3, which will also support multimodal outputs—that is, both text and images.

Meta plans to host the Llama 3 models on a range of cloud platforms, making them accessible through AWS, Databricks, Google Cloud, and other major providers.

Also on Thursday, Meta announced that Llama 3 will become the new basis of the Meta AI virtual assistant, which the company first announced in September. The assistant will appear prominently in search features for Facebook, Instagram, WhatsApp, Messenger, and the aforementioned dedicated website that features a design similar to ChatGPT, including the ability to generate images in the same interface. The company also announced a partnership with Google to integrate real-time search results into the Meta AI assistant, adding to an existing partnership with Microsoft’s Bing.

LLMs keep leaping with Llama 3, Meta’s newest open-weights AI model Read More »