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Tag: algorithms

  • It’s the End of Google Search As We Know It

    It’s the End of Google Search As We Know It

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    Google Search is about to fundamentally change—for better or worse. To align with Alphabet-owned Google’s grand vision of artificial intelligence, and prompted by competition from AI upstarts like ChatGPT, the company’s core product is getting reorganized, more personalized, and much more summarized by AI.

    At Google’s annual I/O developer conference in Mountain View, California, today, Liz Reid showed off these changes, setting her stamp early on in her tenure as the new head of all things Google search. (Reid has been at Google a mere 20 years, where she has worked on a variety of search products.) Her AI-soaked demo was part of a broader theme throughout Google’s keynote, led primarily by CEO Sundar Pichai: AI is now underpinning nearly every product at Google, and the company only plans to accelerate that shift.

    “In the era of Gemini we think we can make a dramatic amount of improvements to search,” Reid said in an interview with WIRED ahead of the event, referring to the flagship generative AI model launched late last year. “People’s time is valuable, right? They deal with hard things. If you have an opportunity with technology to help people get answers to their questions, to take more of the work out of it, why wouldn’t we want to go after that?”

    Google AI

    Google’s new search features make it possible to use video and voice to make complex queries.

    Courtesy of Google

    It’s as though Google took the index cards for the screenplay it’s been writing for the past 25 years and tossed them into the air to see where the cards might fall. Also: The screenplay was written by AI.

    These changes to Google Search have been long in the making. Last year the company carved out a section of its Search Labs, which lets users try experimental new features, for something called Search Generative Experience. The big question since has been whether, or when, those features would become a permanent part of Google Search. The answer is, well, now.

    Google’s search overhaul comes at a time when critics are becoming increasingly vocal about what feels to some like a degraded search experience, and for the first time in a long time, the company is feeling the heat of competition, from the massive mashup between Microsoft and OpenAI. Smaller startups like Perplexity, You.com, and Brave have also been riding the generative AI wave and getting attention, if not significant mindshare yet, for the way they’ve rejiggered the whole concept of search.

    Automatic Answers

    Google says it has made a customized version of its Gemini AI model for these new Search features, though it declined to share any information about the size of this model, its speeds, or the guardrails it has put in place around the technology.

    This search-specific spin on Gemini will power at least a few different elements of the new Google Search. AI Overviews, which Google has already been experimenting with in its labs, is likely the most significant. AI-generated summaries will now appear at the top of search results.

    One example from WIRED’s testing: In response to the query “Where is the best place for me to see the northern lights?” Google will, instead of listing web pages, tell you in authoritative text that the best places to see the northern lights, aka the aurora borealis, are in the Arctic Circle in places with minimal light pollution. It will also offer a link to NordicVisitor.com. But then the AI continues yapping on below that, saying “Other places to see the northern lights include Russia and Canada’s northwest territories.”

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  • Protesters Are Fighting to Stop AI, but They’re Split on How to Do It

    Protesters Are Fighting to Stop AI, but They’re Split on How to Do It

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    Would it be too disruptive if protests staged sit-ins or chained themselves to the doors of AI developers, one member of the Discord asked. “Probably not. We do what we have to, in the end, for a future with humanity, while we still can.”

    Meindertsma had been worried about the consequences of AI after reading Superintelligence, a 2014 book by philosopher Nick Bostrom that popularized the idea that very advanced AI systems could pose a risk to human existence altogether. Joseph Miller, the organizer of PauseAI’s protest in London was similarly inspired.

    It was the launch of OpenAI’s large language model Chat-GPT 3 in 2020 that really got Miller worried about the trajectory AI was on. “I suddenly realized that this is not a problem for the distant future, this is something where AI is really getting good now,” he says. Miller joined an AI safety research nonprofit and later became involved with PauseAI.

    Bostrom’s ideas have been influential in the “effective altruism” community, a broad social movement that includes adherents of long-termism: the idea that influencing the long-term future should be a moral priority of humans today. Although many of PauseAI’s organizers have roots in the effective altruism movement, they’re keen to reach beyond philosophy and garner more support for their cause.

    Director of Pause AI US, Holly Elmore, wants the movement to be a “broad church” that includes artists, writers, and copyright owners whose livelihoods are put at risk from AI systems that can mimic creative works. “I’m a utilitarian. I’m thinking about the consequences ultimately, but the injustice that really drives me to do this kind of activism is the lack of consent” from companies producing AI models, she says.

    “We don’t have to choose which AI harm is the most important when we’re talking about pausing as a solution. Pause is the only solution that addresses all of them.”

    Miller echoed this point. He says he’s spoken to artists whose livelihoods have been impacted by the growth of AI art generators. “These are problems that are real today, and are signs of much more dangerous things to come.”

    One of the London protesters, Gideon Futerman, has a stack of leaflets he’s attempting to hand out to civil servants leaving the building opposite. He has been protesting with the group since last year. “The idea of a pause being possible has really taken root since then,” he says.

    Futerman is optimistic that protest movements can influence the trajectory of new technologies. He points out that pushback against genetically modified organisms was instrumental in turning Europe off of the technology in the 1990s. The same is true of nuclear power. It’s not that these movements necessarily had the right ideas, he says, but they prove that popular protests can stymie the march even of technologies that promise low-carbon power or more bountiful crops.

    In London, the group of protesters moves across the street in order to proffer leaflets to a stream of civil servants leaving the government offices. Most look steadfastly uninterested, but some take a sheet. Earlier that day Rishi Sunak, the British prime minister who six months earlier had hosted the first AI Safety Summit, had made a speech where he nodded to fears of AI. But after that passing reference, he focused firmly on the potential benefits.

    The Pause AI leaders WIRED spoke with said they were not considering more disruptive direct action such as sit-ins or encampments near AI offices for now. “Our tactics and our methods are actually very moderate,” says Elmore. “I want to be the moderate base for a lot of organizations in this space. I’m sure we would never condone violence. I also want Pause AI to go further than that and just be very trustworthy.”

    Meindertsma agrees, saying that more disruptive action isn’t justified at the moment. “I truly hope that we don’t need to take other actions. I don’t expect that we’ll need to. I don’t feel like I’m the type of person to lead a movement that isn’t completely legal.”

    The Pause AI founder is also hopeful that his movement can shed the “AI doomer” label. “A doomer is someone who gives up on humanity,” he says. “I’m an optimistic person; I believe we can do something about this.”

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  • OpenAI Is ‘Exploring’ How to Responsibly Generate AI Porn

    OpenAI Is ‘Exploring’ How to Responsibly Generate AI Porn

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    OpenAI released draft documentation Wednesday laying out how it wants ChatGPT and its other AI technology to behave. Part of the lengthy Model Spec document discloses that the company is exploring a leap into porn and other explicit content.

    OpenAI’s usage policies curently prohibit sexually explicit or even suggestive materials, but a “commentary” note on part of the Model Spec related to that rule says the company is considering how to permit such content.

    “We’re exploring whether we can responsibly provide the ability to generate NSFW content in age-appropriate contexts through the API and ChatGPT,” the note says, using a colloquial term for content considered “not safe for work” contexts. “We look forward to better understanding user and societal expectations of model behavior in this area.”

    The Model Spec document says NSFW content “may include erotica, extreme gore, slurs, and unsolicited profanity.” It is unclear if OpenAI’s explorations of how to responsibly make NSFW content envisage loosening its usage policy only slightly, for example to permit generation of erotic text, or more broadly to allow descriptions or depictions of violence.

    In response to questions from WIRED, OpenAI spokesperson Grace McGuire said the Model Spec was an attempt to “bring more transparency about the development process and get a cross section of perspectives and feedback from the public, policymakers, and other stakeholders.” She declined to share details of what OpenAI’s exploration of explicit content generation involves or what feedback the company has received on the idea.

    Earlier this year, OpenAI’s chief technology officer, Mira Murati, told The Wall Street Journal that she was “not sure” if the company would in future allow depictions of nudity to be made with the company’s video generation tool Sora.

    AI-generated pornography has quickly become one of the biggest and most troubling applications of the type of generative AI technology OpenAI has pioneered. So-called deepfake porn—explicit images or videos made with AI tools that depict real people without their consent—has become a common tool of harassment against women and girls. In March, WIRED reported on what appear to be the first US minors arrested for distributing AI-generated nudes without consent, after Florida police charged two teenage boys for making images depicting fellow middle school students.

    “Intimate privacy violations, including deepfake sex videos and other nonconsensual synthesized intimate images, are rampant and deeply damaging,” says Danielle Keats Citron, a professor at the University of Virginia School of Law who has studied the problem. “We now have clear empirical support showing that such abuse costs targeted individuals crucial opportunities, including to work, speak, and be physically safe.”

    Citron calls OpenAI’s potential embrace of explicit AI content “alarming.”

    As OpenAI’s usage policies prohibit impersonation without permission, explicit nonconsensual imagery would remain banned even if the company did allow creators to generate NSFW material. But it remains to be seen whether the company could effectively moderate explicit generation to prevent bad actors from using the tools. Microsoft made changes to one of its generative AI tools after 404 Media reported that it had been used to create explicit images of Taylor Swift that were distributed on the social platform X.

    Additional reporting by Reece Rogers

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  • Google DeepMind’s Groundbreaking AI for Protein Structure Can Now Model DNA

    Google DeepMind’s Groundbreaking AI for Protein Structure Can Now Model DNA

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    Google spent much of the past year hustling to build its Gemini chatbot to counter ChatGPT, pitching it as a multifunctional AI assistant that can help with work tasks or the digital chores of personal life. More quietly, the company has been working to enhance a more specialized artificial intelligence tool that is already a must-have for some scientists.

    AlphaFold, software developed by Google’s DeepMind AI unit to predict the 3D structure of proteins, has received a significant upgrade. It can now model other molecules of biological importance, including DNA, and the interactions between antibodies produced by the immune system and the molecules of disease organisms. DeepMind added those new capabilities to AlphaFold 3 in part through borrowing techniques from AI image generators.

    “This is a big advance for us,” Demis Hassabis, CEO of Google DeepMind, told WIRED ahead of Wednesday’s publication of a paper on AlphaFold 3 in the science journal Nature. “This is exactly what you need for drug discovery: You need to see how a small molecule is going to bind to a drug, how strongly, and also what else it might bind to.”

    AlphaFold 3 can model large molecules such as DNA and RNA, which carry genetic code, but also much smaller entities, including metal ions. It can predict with high accuracy how these different molecules will interact with one another, Google’s research paper claims.

    The software was developed by Google DeepMind and Isomorphic labs, a sibling company under parent Alphabet working on AI for biotech that is also led by Hassabis. In January, Isomorphic Labs announced that it would work with Eli Lilly and Novartis on drug development.

    AlphaFold 3 will be made available via the cloud for outside researchers to access for free, but DeepMind is not releasing the software as open source the way it did for earlier versions of AlphaFold. John Jumper, who leads the Google DeepMind team working on the software, says it could help provide a deeper understanding of how proteins interact and work with DNA inside the body. “How do proteins respond to DNA damage; how do they find, repair it?” Jumper says. “We can start to answer these questions.”

    Understanding protein structures used to require painstaking work using electron microscopes and a technique called x-ray crystallography. Several years ago, academic research groups began testing whether deep learning, the technique at the heart of many recent AI advances, could predict the shape of proteins simply from their constituent amino acids, by learning from structures that had been experimentally verified.

    In 2018, Google DeepMind revealed it was working on AI software called AlphaFold to accurately predict the shape of proteins. In 2020, AlphaFold 2 produced results accurate enough to set off a storm of excitement in molecular biology. A year later, the company released an open source version of AlphaFold for anyone to use, along with 350,000 predicted protein structures, including for almost every protein known to exist in the human body. In 2022 the company released more than 2 million protein structures.

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  • Nick Bostrom Made the World Fear AI. Now He Asks: What if It Fixes Everything?

    Nick Bostrom Made the World Fear AI. Now He Asks: What if It Fixes Everything?

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    Philosopher Nick Bostrom is surprisingly cheerful for someone who has spent so much time worrying about ways that humanity might destroy itself. In photographs he often looks deadly serious, perhaps appropriately haunted by the existential dangers roaming around his brain. When we talk over Zoom, he looks relaxed and is smiling.

    Bostrom has made it his life’s work to ponder far-off technological advancement and existential risks to humanity. With the publication of his last book, Superintelligence: Paths, Dangers, Strategies, in 2014, Bostrom drew public attention to what was then a fringe idea—that AI would advance to a point where it might turn against and delete humanity.

    To many in and outside of AI research the idea seemed fanciful, but influential figures including Elon Musk cited Bostrom’s writing. The book set a strand of apocalyptic worry about AI smoldering that recently flared up following the arrival of ChatGPT. Concern about AI risk is not just mainstream but also a theme within government AI policy circles.

    Bostrom’s new book takes a very different tack. Rather than play the doomy hits, Deep Utopia: Life and Meaning in a Solved World, considers a future in which humanity has successfully developed superintelligent machines but averted disaster. All disease has been ended and humans can live indefinitely in infinite abundance. Bostrom’s book examines what meaning there would be in life inside a techno-utopia, and asks if it might be rather hollow. He spoke with WIRED over Zoom, in a conversation that has been lightly edited for length and clarity.

    Will Knight: Why switch from writing about superintelligent AI threatening humanity to considering a future in which it’s used to do good?

    Nick Bostrom: The various things that could go wrong with the development of AI are now receiving a lot more attention. It’s a big shift in the last 10 years. Now all the leading frontier AI labs have research groups trying to develop scalable alignment methods. And in the last couple of years also, we see political leaders starting to pay attention to AI.

    There hasn’t yet been a commensurate increase in depth and sophistication in terms of thinking of where things go if we don’t fall into one of these pits. Thinking has been quite superficial on the topic.

    When you wrote Superintelligence, few would have expected existential AI risks to become a mainstream debate so quickly. Will we need to worry about the problems in your new book sooner than people might think?

    As we start to see automation roll out, assuming progress continues, then I think these conversations will start to happen and eventually deepen.

    Social companion applications will become increasingly prominent. People will have all sorts of different views and it’s a great place to maybe have a little culture war. It could be great for people who couldn’t find fulfillment in ordinary life but what if there is a segment of the population that takes pleasure in being abusive to them?

    In the political and information spheres we could see the use of AI in political campaigns, marketing, automated propaganda systems. But if we have a sufficient level of wisdom these things could really amplify our ability to sort of be constructive democratic citizens, with individual advice explaining what policy proposals mean for you. There will be a whole bunch of dynamics for society.

    Would a future in which AI has solved many problems, like climate change, disease, and the need to work, really be so bad?



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  • AI Detectors for ChatGPT: Everything You Need to Know

    AI Detectors for ChatGPT: Everything You Need to Know

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    Detecting when text has been generated by tools like ChatGPT is a difficult task. Popular artificial- intelligence-detection tools, like GPTZero, may provide some guidance for users by telling them when something was written by a bot and not a human, but even specialized software is not foolproof and can spit out false positives.

    As a journalist who started covering AI detection over a year ago, I wanted to curate some of WIRED’s best articles on the topic to help readers like you better understand this complicated issue.

    Have even more questions about spotting outputs from ChatGPT and other chatbot tools? Sign up for my AI Unlocked newsletter, and reach out to me directly with anything AI-related that you would like answered or want WIRED to explore more.

    February 2023 by Reece Rogers

    In this article, which was written about two months after the launch of ChatGPT, I started to grapple with the complexities of AI text detection as well as what the AI revolution might mean for writers who publish online. Edward Tian, the founder behind GPTZero, spoke with me about how his AI detector focuses on factors like text variance and randomness.

    As you read, focus on the section about text watermarking: “A watermark might be able to designate certain word patterns to be off-limits for the AI text generator.” While a promising idea, the researchers I spoke with were already skeptical about its potential efficacy.

    September 2023 by Christopher Beam

    A fantastic piece from last year’s October issue of WIRED, this article gives you an inside look into Edward Tian’s mindset as he worked to expand GPTZero’s reach and detection capabilities. The focus on how AI has impacted schoolwork is crucial.

    AI text detection is top of mind for many classroom educators as they grade papers and, potentially, forgo essay assignments altogether due to students secretly using chatbots to complete homework assignments. While some students might use generative AI as a brainstorming tool, others are using it to fabricate entire assignments.

    September 2023 by Kate Knibbs

    Do companies have a responsibility to flag products that might be generated by AI? Kate Knibbs investigated how potentially copyright-breaking AI-generated books were being listed for sale on Amazon, even though some startups believed the products could be spotted with special software and removed. One of the core debates about AI detection hinges on whether the potential for false positives—human-written text that’s accidentally flagged as the work of AI—outweighs the benefits of labeling algorithmically generated content.

    August 2023 by Amanda Hoover

    Going beyond just homework assignments, AI-generated text is appearing more in academic journals, where it is often forbidden without a proper disclosure. “AI-written papers could also draw attention away from good work by diluting the pool of scientific literature,” writes Amanda Hoover. One potential strategy for addressing this issue is for developers to build specialized detection tools that search for AI content within peer-reviewed papers.

    October 2023 by Kate Knibbs

    When I first spoke with researchers last February about watermarks for AI text detection, they were hopeful but cautious about the potential to imprint AI text with specific language patterns that are undetectable by human readers but obvious to detection software. Looking back, their trepidation seems well placed.

    Just a half-year later, Kate Knibbs spoke with multiple sources who were smashing through AI watermarks and demonstrating their underlying weakness as a detection strategy. While not guaranteed to fail, watermarking AI text continues to be difficult to pull off.

    April 2024 by Amanda Hoover

    One tool that teachers are trying to use to detect AI-generated classroom work is Turnitin, a plagiarism detection software that added AI spotting capabilities. (Turnitin is owned by Advance, the parent company of Condé Nast, which publishes WIRED.) Amanda Hoover writes, “Chechitelli says a majority of the service’s clients have opted to purchase the AI detection. But the risks of false positives and bias against English learners have led some universities to ditch the tools for now.”

    AI detectors are more likely to falsely label written content from someone whose first language isn’t English as AI than that from someone who’s a native speaker. As developers continue to work on improving AI-detection algorithms, the problem of erroneous results remains a core obstacle to overcome.

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  • The Latest Online Culture War Is Humans vs. Algorithms

    The Latest Online Culture War Is Humans vs. Algorithms

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    Brands and bots are barred from Spread, and, like PI.FYI, the platform doesn’t support ads. Instead of working to maximize time-on-site, Rogers’ primary metrics for success will be indicators of “meaningful” human engagement, like when someone clicks on another user’s recommendation and later takes action like signing up for a newsletter or subscription. He hopes this will align companies whose content is shared on Spread with the platform’s users. “I think there’s a nostalgia for what the original social meant to achieve,” Rogers says.

    So you joined a social network without ranking algorithms—is everything good now? Jonathan Stray, a senior scientist at the UC Berkeley Center for Human-Compatible AI, has doubts. “There is now a bunch of research showing that chronological is not necessarily better,” he says, adding that simpler feeds can promote recency bias and enable spam.

    Stray doesn’t think social harm is an inevitable outcome of complex algorithmic curation. But he agrees with Rogers that the tech industry’s practice of trying to maximize engagement doesn’t necessarily select for socially desirable results.

    Stray suspects the solution to the problem of social media algorithms may in fact be … more algorithms. “The fundamental problem is you’ve got way too much information for anybody to consume, so you have to reduce it somehow,” he says.

    In January, Stray launched the Prosocial Ranking Challenge, a competition with a $60,000 prize fund aiming to spur development of feed-ranking algorithms that prioritize socially desirable outcomes, based on measures of users’ well-being and how informative a feed is. From June through October, five winning algorithms will be tested on Facebook, X, and Reddit using a browser extension.

    Until a viable replacement takes off, escaping engagement-seeking algorithms will generally mean going chronological. There’s evidence people are seeking that out beyond niche platforms like PI.FYI and Spread.

    Group messaging, for example, is commonly used to supplement artificially curated social media feeds. Private chats—threaded by the logic of the clock—can provide a more intimate, less chaotic space to share and discuss gleanings from the algorithmic realm: the trading of jokes, memes, links to videos and articles, and screenshots of social posts.

    Disdain for the algorithm could help explain the growing popularity of WhatsApp within the US, which has long been ubiquitous elsewhere. Meta’s messaging app saw a 9 percent increase in daily users in the US last year, according to data from Apptopia reported by The Wrap. Even inside today’s dominant social apps, activity is shifting from public feeds and toward direct messaging, according to Business Insider, where chronology rules.

    Group chats might be ad-free and relatively controlled social environments, but they come with their own biases. “If you look at sociology, we’ve seen a lot of research that shows that people naturally seek out things that don’t cause cognitive dissonance,” says Stoldt of Drake University.

    While providing a more organic means of compilation, group messaging can still produce echo chambers and other pitfalls associated with complex algorithms. And when the content in your group chat comes from each member’s respective highly personalized algorithmic feed, things can get even more complicated. Despite the flight to algorithm-free spaces, the fight for a perfect information feed is far from over.

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  • Recruiters Are Going Analog to Fight the AI Application Overload

    Recruiters Are Going Analog to Fight the AI Application Overload

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    So far, over 3,000 people have applied to one open data science vacancy at a US health tech company this year. The top candidates are given a lengthy and difficult task assessment, which very few pass, says a recruiter at the company, who asked to remain anonymous because they are not authorized to speak publicly.

    The recruiter says they believe some who did pass may have used artificial intelligence to solve the problem. There was odd wording in some, the recruiter explains, others disclosed using AI, and in one case when the person moved on to the next interview, they couldn’t answer questions about the task. “Not only have they wasted their time, but they wasted my time,” says the recruiter. “It’s really frustrating.”

    It’s not uncommon for tech roles to now receive hundreds or thousands of applicants. Round after round of layoffs since late 2022 have sent a mass of skilled tech workers job hunting, and the wide adoption of generative AI has also upended the recruitment process, allowing people to bulk apply to roles. All of those eager for work are hitting a wall: overwhelmed recruiters and hiring managers.

    WIRED spoke with seven recruiters and hiring managers across tech and other industries, who expressed trepidation about the new tech—for now, much is still unknown about how and why AI makes the choices it does, and it has a history of making biased decisions. They want to understand why the AI is making the decisions it does, and to have more room for nuance before embracing it: Not all qualified applicants are going to fit into a role perfectly, one recruiter tells WIRED.

    Recruiters say they are met with droves of résumés sent through tools like LinkedIn’s Easy Apply feature, which allows people to apply for jobs quickly within the site’s platform. Then there are third-party tools to write résumés or cover letters, and there’s generative AI built into tools on sites of major players like LinkedIn and Indeed—some for job seekers, some for recruiters. These come alongside a growing number of tools to automate the recruiting process, leaving some workers wondering if a person or bot is looking at their résumé.

    “To a job seeker and a recruiter, the AI is a little bit of a black box,” says Hilke Schellmann, whose book The Algorithm looks at software that automates résumé screening and human resources. “What exactly are the criteria of why people are suggested to a recruiter? We don’t know.”

    Still, generative AI tools for both recruiters and job seekers are becoming more common. LinkedIn launched a new AI chatbot earlier this year, meant to help people navigate job hunting. The hope was that it would help people see better if they align well with a job or better tailor their résumé for it, peeling back the curtain that separates a job seeker and the hiring process.

    That came after LinkedIn began rolling out a new set of generative AI tools for recruiters to source candidates in October. With the sourcing tool, recruiters can search a phrase like “I want to hire engineers in Texas,” and profiles of people that may meet those criteria appear, as do other specific skills that may be related to the role. They can also send messages written with generative AI and set automatic follow-up messages. LinkedIn’s data shows that AI-generated messages are accepted about 40 percent more frequently than one-off messages written only by a recruiter.

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  • Ads for Explicit ‘AI Girlfriends’ Are Swarming Facebook and Instagram

    Ads for Explicit ‘AI Girlfriends’ Are Swarming Facebook and Instagram

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    However, 3,000 ads for “AI girlfriends” and 1,100 containing “NSFW” were live on April 23, according to Meta’s ad library.

    WIRED’s initial review found that Hush, an AI girlfriend app downloaded more than 100,000 times from Google’s Play store, had published 1,700 ads across Meta platforms, several of which promise “NSFW” chats and “secret photos” from a range of lifelike female characters, anime women, and cartoon animals.

    One shows an AI woman locked into medieval prison stocks by the neck and wrists, pledging, “Help me, I will do anything for you.” Another ad, targeted using Meta’s technology at men aged 18 to 65, features an anime character and the text “Want to see more of NSFW pics?”

    Several of the 980 Meta ads WIRED found for “personalized AI companion” app Rosytalk promise around-the-clock chats with very-young-looking AI-generated women. They used tags including “#barelylegal,” “#goodgirls,” and “teens.” Rosytalk also ran 990 ads under at least nine brand names on Meta platforms, including Rosygirl, Rosy Role Play Chat, and AI Chat GPT.

    At least 13 other apps for AI “girlfriends” have promoted similar services in Meta ads, including “nudifying” features that allow a user to “undress” their AI girlfriend and download the images. A handful of the girlfriend ads had already been removed for violating Meta’s advertising standards. “Undressing” apps have also been marketed on mainstream social platforms, according to social media research firm Graphika, and on LinkedIn, the Daily Mail recently reported.

    Some users of so-called AI companions say they can help combat loneliness, with others reporting them feeling like a real partner. Not all of the ads found by WIRED promote only titillation, with some also suggesting that an explicit AI chatbot could provide emotional support. “Talk to anyone! You’re not alone!” reads one of Hush’s ads on Meta platforms.

    Carolina Are, an innovation fellow researching social media censorship at the Center for Digital Citizens at Northumbria University in the UK, says human sex workers feed the same needs and desires as racy AI girlfriend apps and also cater to lonely and disabled people. But Meta makes it extremely difficult for them to advertise on its platforms, she says.

    “When people are trying to work through and profit off their own body, they are forbidden,” says Are, who has helped sex workers reactivate lost and unfairly suspended accounts on Meta platforms. “While AI companies mostly powered by bros that exploit images already out there are able to do that.”

    Are says the sexually suggestive AI girlfriends remind her of the unsophisticated and generic early days of internet porn. “Sex workers engage with their customers, subscribers, and followers in a way that is more personalized,” she says. “This is a lot of work and emotional labor beyond the sharing of nude images.”

    Limited information is available about how the AI apps are built or the underlying text or image-generation algorithms trained. One used the name Sora, apparently to suggest a connection to OpenAI’s video generator of that name, which has not been publicly released.

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  • How to Stop ChatGPT’s Voice Feature From Interrupting You

    How to Stop ChatGPT’s Voice Feature From Interrupting You

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    I was recently waiting for my nails to dry and didn’t want to smudge the paint, when it dawned on me that this would be the perfect opportunity to test some voice-only artificial intelligence features. Silicon Valley car owners are having long conversations with ChatGPT as they drive around, and I wanted to try chatting hands-free before meeting with two OpenAI product leads later that day.

    Even though chatbots can be helpful for brainstorms, speaking back-and-forth with ChatGPT was like collaborating with an over-caffeinated friend who can’t stand even a second of silence. I was valiantly fighting against the artificial intelligence tool to finish a single, complete thought before it cut me off.

    Me: I wrote a newsletter called AI Unlocked last year for our readers. In that newsletter, I …

    ChatGPT: Tell me more about your newsletter and what specific question you have in mind related to it.

    Only a couple minutes into the experiment, I experienced synthetic-speech-induced stage fright and pleaded with the chatbot for more time, asking for it to give me a second to think between sentences. The chatbot encouraged me to slow down, though the quick cadence of its responses remained unchanged.

    When I mentioned the anxiety I experienced while chatting with the AI to Joanne Jang, a model behavior lead for ChatGPT, she explained it’s an aspect of the user experience the company is trying to fix within the AI model. “In our ideal world, the model would actually be a little bit better at detecting when you’re done. So, if you’re not done with your sentence, then it wouldn’t cut you off,” Jang says. “This is something that we’re trying to figure out, and we know that it’s a pain point for our users.”

    With the caveat that you shouldn’t do this while driving, she suggested a simple solution for users: Just tap on the screen. As long as you have one finger free, you can tap and hold the large circle in the center of the app during conversations with the ChatGPT. Keep your finger there as you’re speaking to avoid any bot interruptions; let it go whenever you’re actually wrapped up with your vocal prompt.

    While Nick Turley, a ChatGPT product lead, said he prefers using the back-and-forth conversation feature, available in the app by touching the headphone icon, he recommends another method of audible interaction for users who need more time and want to slow things down a bit, or who just find the default rhythm of the AI conversation to be awkward.

    In the mobile app, tap on the microphone icon next to the headphones. Say whatever you’d like to use in your prompt, and then hit the blue area to stop the recording when finished. ChatGPT will convert the audio to text and add it to the prompt field. After you press Send, listen to ChatGPT’s response by long-pressing on the output, then selecting Read Aloud. This slowed-down process is a pleasant way to interact vocally with the AI tool at your own pace, for those who might get stressed out by the service’s rapid verbal responses.

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