AI ethics

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

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Adventures in 21st century regulation —

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

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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.”

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Deepfakes in the courtroom: US judicial panel debates new AI evidence rules

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adventures in 21st-century justice —

Panel of eight judges confronts deep-faking AI tech that may undermine legal trials.

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An illustration of a man with a very long nose holding up the scales of justice.

On Friday, a federal judicial panel convened in Washington, DC, to discuss the challenges of policing AI-generated evidence in court trials, according to a Reuters report. The US Judicial Conference’s Advisory Committee on Evidence Rules, an eight-member panel responsible for drafting evidence-related amendments to the Federal Rules of Evidence, heard from computer scientists and academics about the potential risks of AI being used to manipulate images and videos or create deepfakes that could disrupt a trial.

The meeting took place amid broader efforts by federal and state courts nationwide to address the rise of generative AI models (such as those that power OpenAI’s ChatGPT or Stability AI’s Stable Diffusion), which can be trained on large datasets with the aim of producing realistic text, images, audio, or videos.

In the published 358-page agenda for the meeting, the committee offers up this definition of a deepfake and the problems AI-generated media may pose in legal trials:

A deepfake is an inauthentic audiovisual presentation prepared by software programs using artificial intelligence. Of course, photos and videos have always been subject to forgery, but developments in AI make deepfakes much more difficult to detect. Software for creating deepfakes is already freely available online and fairly easy for anyone to use. As the software’s usability and the videos’ apparent genuineness keep improving over time, it will become harder for computer systems, much less lay jurors, to tell real from fake.

During Friday’s three-hour hearing, the panel wrestled with the question of whether existing rules, which predate the rise of generative AI, are sufficient to ensure the reliability and authenticity of evidence presented in court.

Some judges on the panel, such as US Circuit Judge Richard Sullivan and US District Judge Valerie Caproni, reportedly expressed skepticism about the urgency of the issue, noting that there have been few instances so far of judges being asked to exclude AI-generated evidence.

“I’m not sure that this is the crisis that it’s been painted as, and I’m not sure that judges don’t have the tools already to deal with this,” said Judge Sullivan, as quoted by Reuters.

Last year, Chief US Supreme Court Justice John Roberts acknowledged the potential benefits of AI for litigants and judges, while emphasizing the need for the judiciary to consider its proper uses in litigation. US District Judge Patrick Schiltz, the evidence committee’s chair, said that determining how the judiciary can best react to AI is one of Roberts’ priorities.

In Friday’s meeting, the committee considered several deepfake-related rule changes. In the agenda for the meeting, US District Judge Paul Grimm and attorney Maura Grossman proposed modifying Federal Rule 901(b)(9) (see page 5), which involves authenticating or identifying evidence. They also recommended the addition of a new rule, 901(c), which might read:

901(c): Potentially Fabricated or Altered Electronic Evidence. If a party challenging the authenticity of computer-generated or other electronic evidence demonstrates to the court that it is more likely than not either fabricated, or altered in whole or in part, the evidence is admissible only if the proponent demonstrates that its probative value outweighs its prejudicial effect on the party challenging the evidence.

The panel agreed during the meeting that this proposal to address concerns about litigants challenging evidence as deepfakes did not work as written and that it will be reworked before being reconsidered later.

Another proposal by Andrea Roth, a law professor at the University of California, Berkeley, suggested subjecting machine-generated evidence to the same reliability requirements as expert witnesses. However, Judge Schiltz cautioned that such a rule could hamper prosecutions by allowing defense lawyers to challenge any digital evidence without establishing a reason to question it.

For now, no definitive rule changes have been made, and the process continues. But we’re witnessing the first steps of how the US justice system will adapt to an entirely new class of media-generating technology.

Putting aside risks from AI-generated evidence, generative AI has led to embarrassing moments for lawyers in court over the past two years. In May 2023, US lawyer Steven Schwartz of the firm Levidow, Levidow, & Oberman apologized to a judge for using ChatGPT to help write court filings that inaccurately cited six nonexistent cases, leading to serious questions about the reliability of AI in legal research. Also, in November, a lawyer for Michael Cohen cited three fake cases that were potentially influenced by a confabulating AI assistant.

Deepfakes in the courtroom: US judicial panel debates new AI evidence rules Read More »

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Microsoft’s VASA-1 can deepfake a person with one photo and one audio track

AI, AI ethics, AI safety, Biz & IT, Deepfakes, image synthesis, machine learning, microsoft, VASA-1, video synthesis / /

pics and it didn’t happen —

YouTube videos of 6K celebrities helped train AI model to animate photos in real time.

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A sample image from Microsoft for

Enlarge / A sample image from Microsoft for “VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time.”

On Tuesday, Microsoft Research Asia unveiled VASA-1, an AI model that can create a synchronized animated video of a person talking or singing from a single photo and an existing audio track. In the future, it could power virtual avatars that render locally and don’t require video feeds—or allow anyone with similar tools to take a photo of a person found online and make them appear to say whatever they want.

“It paves the way for real-time engagements with lifelike avatars that emulate human conversational behaviors,” reads the abstract of the accompanying research paper titled, “VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time.” It’s the work of Sicheng Xu, Guojun Chen, Yu-Xiao Guo, Jiaolong Yang, Chong Li, Zhenyu Zang, Yizhong Zhang, Xin Tong, and Baining Guo.

The VASA framework (short for “Visual Affective Skills Animator”) uses machine learning to analyze a static image along with a speech audio clip. It is then able to generate a realistic video with precise facial expressions, head movements, and lip-syncing to the audio. It does not clone or simulate voices (like other Microsoft research) but relies on an existing audio input that could be specially recorded or spoken for a particular purpose.

Microsoft claims the model significantly outperforms previous speech animation methods in terms of realism, expressiveness, and efficiency. To our eyes, it does seem like an improvement over single-image animating models that have come before.

AI research efforts to animate a single photo of a person or character extend back at least a few years, but more recently, researchers have been working on automatically synchronizing a generated video to an audio track. In February, an AI model called EMO: Emote Portrait Alive from Alibaba’s Institute for Intelligent Computing research group made waves with a similar approach to VASA-1 that can automatically sync an animated photo to a provided audio track (they call it “Audio2Video”).

Trained on YouTube clips

Microsoft Researchers trained VASA-1 on the VoxCeleb2 dataset created in 2018 by three researchers from the University of Oxford. That dataset contains “over 1 million utterances for 6,112 celebrities,” according to the VoxCeleb2 website, extracted from videos uploaded to YouTube. VASA-1 can reportedly generate videos of 512×512 pixel resolution at up to 40 frames per second with minimal latency, which means it could potentially be used for realtime applications like video conferencing.

To show off the model, Microsoft created a VASA-1 research page featuring many sample videos of the tool in action, including people singing and speaking in sync with pre-recorded audio tracks. They show how the model can be controlled to express different moods or change its eye gaze. The examples also include some more fanciful generations, such as Mona Lisa rapping to an audio track of Anne Hathaway performing a “Paparazzi” song on Conan O’Brien.

The researchers say that, for privacy reasons, each example photo on their page was AI-generated by StyleGAN2 or DALL-E 3 (aside from the Mona Lisa). But it’s obvious that the technique could equally apply to photos of real people as well, although it’s likely that it will work better if a person appears similar to a celebrity present in the training dataset. Still, the researchers say that deepfaking real humans is not their intention.

“We are exploring visual affective skill generation for virtual, interactive charactors [sic], NOT impersonating any person in the real world. This is only a research demonstration and there’s no product or API release plan,” reads the site.

While the Microsoft researchers tout potential positive applications like enhancing educational equity, improving accessibility, and providing therapeutic companionship, the technology could also easily be misused. For example, it could allow people to fake video chats, make real people appear to say things they never actually said (especially when paired with a cloned voice track), or allow harassment from a single social media photo.

Right now, the generated video still looks imperfect in some ways, but it could be fairly convincing for some people if they did not know to expect an AI-generated animation. The researchers say they are aware of this, which is why they are not openly releasing the code that powers the model.

“We are opposed to any behavior to create misleading or harmful contents of real persons, and are interested in applying our technique for advancing forgery detection,” write the researchers. “Currently, the videos generated by this method still contain identifiable artifacts, and the numerical analysis shows that there’s still a gap to achieve the authenticity of real videos.”

VASA-1 is only a research demonstration, but Microsoft is far from the only group developing similar technology. If the recent history of generative AI is any guide, it’s potentially only a matter of time before similar technology becomes open source and freely available—and they will very likely continue to improve in realism over time.

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Billie Eilish, Pearl Jam, 200 artists say AI poses existential threat to their livelihoods

AI, AI art, AI ethics, AI music, ara, Arists Rights Alliance, Billie Eilish, Biz & IT, chatgpt, chatgtp, culture, Google, machine learning, music, music industry, music synthesis, MusicLM, openai, Pearl Jam, Riffusion, Stable Audio / /

artificial music —

Artists say AI will “set in motion a race to the bottom that will degrade the value of our work.”

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Billie Eilish attends the 2024 Vanity Fair Oscar Party hosted by Radhika Jones at the Wallis Annenberg Center for the Performing Arts on March 10, 2024 in Beverly Hills, California.

Enlarge / Billie Eilish attends the 2024 Vanity Fair Oscar Party hosted by Radhika Jones at the Wallis Annenberg Center for the Performing Arts on March 10, 2024, in Beverly Hills, California.

On Tuesday, the Artist Rights Alliance (ARA) announced an open letter critical of AI signed by over 200 musical artists, including Pearl Jam, Nicki Minaj, Billie Eilish, Stevie Wonder, Elvis Costello, and the estate of Frank Sinatra. In the letter, the artists call on AI developers, technology companies, platforms, and digital music services to stop using AI to “infringe upon and devalue the rights of human artists.” A tweet from the ARA added that AI poses an “existential threat” to their art.

Visual artists began protesting the advent of generative AI after the rise of the first mainstream AI image generators in 2022, and considering that generative AI research has since been undertaken for other forms of creative media, we have seen that protest extend to professionals in other creative domains, such as writers, actors, filmmakers—and now musicians.

“When used irresponsibly, AI poses enormous threats to our ability to protect our privacy, our identities, our music and our livelihoods,” the open letter states. It alleges that some of the “biggest and most powerful” companies (unnamed in the letter) are using the work of artists without permission to train AI models, with the aim of replacing human artists with AI-created content.

  • A list of musical artists that signed the ARA open letter against generative AI.

  • A list of musical artists that signed the ARA open letter against generative AI.

  • A list of musical artists that signed the ARA open letter against generative AI.

  • A list of musical artists that signed the ARA open letter against generative AI.

In January, Billboard reported that AI research taking place at Google DeepMind had trained an unnamed music-generating AI on a large dataset of copyrighted music without seeking artist permission. That report may have been referring to Google’s Lyria, an AI-generation model announced in November that the company positioned as a tool for enhancing human creativity. The tech has since powered musical experiments from YouTube.

We’ve previously covered AI music generators that seemed fairly primitive throughout 2022 and 2023, such as Riffusion, Google’s MusicLM, and Stability AI’s Stable Audio. We’ve also covered open source musical voice-cloning technology that is frequently used to make musical parodies online. While we have yet to see an AI model that can generate perfect, fully composed high-quality music on demand, the quality of outputs from music synthesis models has been steadily improving over time.

In considering AI’s potential impact on music, it’s instructive to remember historical instances where tech innovations initially sparked concern among artists. For instance, the introduction of synthesizers in the 1960s and 1970s and the advent of digital sampling in the 1980s both faced scrutiny and fear from parts of the music community, but the music industry eventually adjusted.

While we’ve seen fear of the unknown related to AI going around quite a bit for the past year, it’s possible that AI tools will be integrated into the music production process like any other music production tool or technique that came before. It’s also possible that even if that kind of integration comes to pass, some artists will still get hurt along the way—and the ARA wants to speak out about it before the technology progresses further.

“Race to the bottom”

The Artists Rights Alliance is a nonprofit advocacy group that describes itself as an “alliance of working musicians, performers, and songwriters fighting for a healthy creative economy and fair treatment for all creators in the digital world.”

The signers of the ARA’s open letter say they acknowledge the potential of AI to advance human creativity when used responsibly, but they also claim that replacing artists with generative AI would “substantially dilute the royalty pool” paid out to artists, which could be “catastrophic” for many working musicians, artists, and songwriters who are trying to make ends meet.

In the letter, the artists say that unchecked AI will set in motion a race to the bottom that will degrade the value of their work and prevent them from being fairly compensated. “This assault on human creativity must be stopped,” they write. “We must protect against the predatory use of AI to steal professional artist’ voices and likenesses, violate creators’ rights, and destroy the music ecosystem.”

The emphasis on the word “human” in the letter is notable (“human artist” was used twice and “human creativity” and “human artistry” are used once, each) because it suggests the clear distinction they are drawing between the work of human artists and the output of AI systems. It implies recognition that we’ve entered a new era where not all creative output is made by people.

The letter concludes with a call to action, urging all AI developers, technology companies, platforms, and digital music services to pledge not to develop or deploy AI music-generation technology, content, or tools that undermine or replace the human artistry of songwriters and artists or deny them fair compensation for their work.

While it’s unclear whether companies will meet those demands, so far, protests from visual artists have not stopped development of ever-more advanced image-synthesis models. On Threads, frequent AI industry commentator Dare Obasanjo wrote, “Unfortunately this will be as effective as writing an open letter to stop the sun from rising tomorrow.”

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OpenAI holds back wide release of voice-cloning tech due to misuse concerns

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Voice synthesis has come a long way since 1978’s Speak & Spell toy, which once wowed people with its state-of-the-art ability to read words aloud using an electronic voice. Now, using deep-learning AI models, software can create not only realistic-sounding voices, but also convincingly imitate existing voices using small samples of audio.

Along those lines, OpenAI just announced Voice Engine, a text-to-speech AI model for creating synthetic voices based on a 15-second segment of recorded audio. It has provided audio samples of the Voice Engine in action on its website.

Once a voice is cloned, a user can input text into the Voice Engine and get an AI-generated voice result. But OpenAI is not ready to widely release its technology yet. The company initially planned to launch a pilot program for developers to sign up for the Voice Engine API earlier this month. But after more consideration about ethical implications, the company decided to scale back its ambitions for now.

“In line with our approach to AI safety and our voluntary commitments, we are choosing to preview but not widely release this technology at this time,” the company writes. “We hope this preview of Voice Engine both underscores its potential and also motivates the need to bolster societal resilience against the challenges brought by ever more convincing generative models.”

Voice cloning tech in general is not particularly new—we’ve covered several AI voice synthesis models since 2022, and the tech is active in the open source community with packages like OpenVoice and XTTSv2. But the idea that OpenAI is inching toward letting anyone use their particular brand of voice tech is notable. And in some ways, the company’s reticence to release it fully might be the bigger story.

OpenAI says that benefits of its voice technology include providing reading assistance through natural-sounding voices, enabling global reach for creators by translating content while preserving native accents, supporting non-verbal individuals with personalized speech options, and assisting patients in recovering their own voice after speech-impairing conditions.

But it also means that anyone with 15 seconds of someone’s recorded voice could effectively clone it, and that has obvious implications for potential misuse. Even if OpenAI never widely releases its Voice Engine, the ability to clone voices has already caused trouble in society through phone scams where someone imitates a loved one’s voice and election campaign robocalls featuring cloned voices from politicians like Joe Biden.

Also, researchers and reporters have shown that voice-cloning technology can be used to break into bank accounts that use voice authentication (such as Chase’s Voice ID), which prompted Sen. Sherrod Brown (D-Ohio), the chairman of the US Senate Committee on Banking, Housing, and Urban Affairs, to send a letter to the CEOs of several major banks in May 2023 to inquire about the security measures banks are taking to counteract AI-powered risks.

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World’s first global AI resolution unanimously adopted by United Nations

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We hold these seeds to be self-evident —

Nonbinding agreement seeks to protect personal data and safeguard human rights.

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The United Nations building in New York.

Enlarge / The United Nations building in New York.

On Thursday, the United Nations General Assembly unanimously consented to adopt what some call the first global resolution on AI, reports Reuters. The resolution aims to foster the protection of personal data, enhance privacy policies, ensure close monitoring of AI for potential risks, and uphold human rights. It emerged from a proposal by the United States and received backing from China and 121 other countries.

Being a nonbinding agreement and thus effectively toothless, the resolution seems broadly popular in the AI industry. On X, Microsoft Vice Chair and President Brad Smith wrote, “We fully support the @UN’s adoption of the comprehensive AI resolution. The consensus reached today marks a critical step towards establishing international guardrails for the ethical and sustainable development of AI, ensuring this technology serves the needs of everyone.”

The resolution, titled “Seizing the opportunities of safe, secure and trustworthy artificial intelligence systems for sustainable development,” resulted from three months of negotiation, and the stakeholders involved seem pleased at the level of international cooperation. “We’re sailing in choppy waters with the fast-changing technology, which means that it’s more important than ever to steer by the light of our values,” one senior US administration official told Reuters, highlighting the significance of this “first-ever truly global consensus document on AI.”

In the UN, adoption by consensus means that all members agree to adopt the resolution without a vote. “Consensus is reached when all Member States agree on a text, but it does not mean that they all agree on every element of a draft document,” writes the UN in a FAQ found online. “They can agree to adopt a draft resolution without a vote, but still have reservations about certain parts of the text.”

The initiative joins a series of efforts by governments worldwide to influence the trajectory of AI development following the launch of ChatGPT and GPT-4, and the enormous hype raised by certain members of the tech industry in a public worldwide campaign waged last year. Critics fear that AI may undermine democratic processes, amplify fraudulent activities, or contribute to significant job displacement, among other issues. The resolution seeks to address the dangers associated with the irresponsible or malicious application of AI systems, which the UN says could jeopardize human rights and fundamental freedoms.

Resistance from nations such as Russia and China was anticipated, and US officials acknowledged the presence of “lots of heated conversations” during the negotiation process, according to Reuters. However, they also emphasized successful engagement with these countries and others typically at odds with the US on various issues, agreeing on a draft resolution that sought to maintain a delicate balance between promoting development and safeguarding human rights.

The new UN agreement may be the first “global” agreement, in the sense of having the participation of every UN country, but it wasn’t the first multi-state international AI agreement. That honor seems to fall to the Bletchley Declaration signed in November by the 28 nations attending the UK’s first AI Summit.

Also in November, the US, Britain, and other nations unveiled an agreement focusing on the creation of AI systems that are “secure by design” to protect against misuse by rogue actors. Europe is slowly moving forward with provisional agreements to regulate AI and is close to implementing the world’s first comprehensive AI regulations. Meanwhile, the US government still lacks consensus on legislative action related to AI regulation, with the Biden administration advocating for measures to mitigate AI risks while enhancing national security.

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OpenAI CEO Altman wasn’t fired because of scary new tech, just internal politics

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Adventures in optics —

As Altman cements power, OpenAI announces three new board members—and a returning one.

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OpenAI CEO Sam Altman speaks during the OpenAI DevDay event on November 6, 2023, in San Francisco.

Enlarge / OpenAI CEO Sam Altman speaks during the OpenAI DevDay event on November 6, 2023, in San Francisco.

On Friday afternoon Pacific Time, OpenAI announced the appointment of three new members to the company’s board of directors and released the results of an independent review of the events surrounding CEO Sam Altman’s surprise firing last November. The current board expressed its confidence in the leadership of Altman and President Greg Brockman, and Altman is rejoining the board.

The newly appointed board members are Dr. Sue Desmond-Hellmann, former CEO of the Bill and Melinda Gates Foundation; Nicole Seligman, former EVP and global general counsel of Sony; and Fidji Simo, CEO and chair of Instacart. These additions notably bring three women to the board after OpenAI met criticism about its restructured board composition last year. In addition, Sam Altman has rejoined the board.

The independent review, conducted by law firm WilmerHale, investigated the circumstances that led to Altman’s abrupt removal from the board and his termination as CEO on November 17, 2023. Despite rumors to the contrary, the board did not fire Altman because they got a peek at scary new AI technology and flinched. “WilmerHale… found that the prior Board’s decision did not arise out of concerns regarding product safety or security, the pace of development, OpenAI’s finances, or its statements to investors, customers, or business partners.”

Instead, the review determined that the prior board’s actions stemmed from a breakdown in trust between the board and Altman.

After reportedly interviewing dozens of people and reviewing over 30,000 documents, WilmerHale found that while the prior board acted within its purview, Altman’s termination was unwarranted. “WilmerHale found that the prior Board acted within its broad discretion to terminate Mr. Altman,” OpenAI wrote, “but also found that his conduct did not mandate removal.”

Additionally, the law firm found that the decision to fire Altman was made in undue haste: “The prior Board implemented its decision on an abridged timeframe, without advance notice to key stakeholders and without a full inquiry or an opportunity for Mr. Altman to address the prior Board’s concerns.”

Altman’s surprise firing occurred after he attempted to remove Helen Toner from OpenAI’s board due to disagreements over her criticism of OpenAI’s approach to AI safety and hype. Some board members saw his actions as deceptive and manipulative. After Altman returned to OpenAI, Toner resigned from the OpenAI board on November 29.

In a statement posted on X, Altman wrote, “i learned a lot from this experience. one think [sic] i’ll say now: when i believed a former board member was harming openai through some of their actions, i should have handled that situation with more grace and care. i apologize for this, and i wish i had done it differently.”

A tweet from Sam Altman posted on March 8, 2024.

Enlarge / A tweet from Sam Altman posted on March 8, 2024.

Following the review’s findings, the Special Committee of the OpenAI Board recommended endorsing the November 21 decision to rehire Altman and Brockman. The board also announced several enhancements to its governance structure, including new corporate governance guidelines, a strengthened Conflict of Interest Policy, a whistleblower hotline, and additional board committees focused on advancing OpenAI’s mission.

After OpenAI’s announcements on Friday, resigned OpenAI board members Toner and Tasha McCauley released a joint statement on X. “Accountability is important in any company, but it is paramount when building a technology as potentially world-changing as AGI,” they wrote. “We hope the new board does its job in governing OpenAI and holding it accountable to the mission. As we told the investigators, deception, manipulation, and resistance to thorough oversight should be unacceptable.”

OpenAI CEO Altman wasn’t fired because of scary new tech, just internal politics Read More »

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US gov’t announces arrest of former Google engineer for alleged AI trade secret theft

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Don’t trade the secrets dept. —

Linwei Ding faces four counts of trade secret theft, each with a potential 10-year prison term.

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A Google sign stands in front of the building on the sidelines of the opening of the new Google Cloud data center in Hesse, Hanau, opened in October 2023.

Enlarge / A Google sign stands in front of the building on the sidelines of the opening of the new Google Cloud data center in Hesse, Hanau, opened in October 2023.

On Wednesday, authorities arrested former Google software engineer Linwei Ding in Newark, California, on charges of stealing AI trade secrets from the company. The US Department of Justice alleges that Ding, a Chinese national, committed the theft while secretly working with two China-based companies.

According to the indictment, Ding, who was hired by Google in 2019 and had access to confidential information about the company’s data centers, began uploading hundreds of files into a personal Google Cloud account two years ago.

The trade secrets Ding allegedly copied contained “detailed information about the architecture and functionality of GPU and TPU chips and systems, the software that allows the chips to communicate and execute tasks, and the software that orchestrates thousands of chips into a supercomputer capable of executing at the cutting edge of machine learning and AI technology,” according to the indictment.

Shortly after the alleged theft began, Ding was offered the position of chief technology officer at an early-stage technology company in China that touted its use of AI technology. The company offered him a monthly salary of about $14,800, plus an annual bonus and company stock. Ding reportedly traveled to China, participated in investor meetings, and sought to raise capital for the company.

Investigators reviewed surveillance camera footage that showed another employee scanning Ding’s name badge at the entrance of the building where Ding worked at Google, making him look like he was working from his office when he was actually traveling.

Ding also founded and served as the chief executive of a separate China-based startup company that aspired to train “large AI models powered by supercomputing chips,” according to the indictment. Prosecutors say Ding did not disclose either affiliation to Google, which described him as a junior employee. He resigned from Google on December 26 of last year.

The FBI served a search warrant at Ding’s home in January, seizing his electronic devices and later executing an additional warrant for the contents of his personal accounts. Authorities found more than 500 unique files of confidential information that Ding allegedly stole from Google. The indictment says that Ding copied the files into the Apple Notes application on his Google-issued Apple MacBook, then converted the Apple Notes into PDF files and uploaded them to an external account to evade detection.

“We have strict safeguards to prevent the theft of our confidential commercial information and trade secrets,” Google spokesperson José Castañeda told Ars Technica. “After an investigation, we found that this employee stole numerous documents, and we quickly referred the case to law enforcement. We are grateful to the FBI for helping protect our information and will continue cooperating with them closely.”

Attorney General Merrick Garland announced the case against the 38-year-old at an American Bar Association conference in San Francisco. Ding faces four counts of federal trade secret theft, each carrying a potential sentence of up to 10 years in prison.

US gov’t announces arrest of former Google engineer for alleged AI trade secret theft Read More »

some-teachers-are-now-using-chatgpt-to-grade-papers

Some teachers are now using ChatGPT to grade papers

AI, AI ethics, AI in education, axios, Biz & IT, chatgpt, chatgtp, confabulation, education, hallucination, Houghton Mifflin Harcout, machine learning, openai, Writable / /

robots in disguise —

New AI tools aim to help with grading, lesson plans—but may have serious drawbacks.

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An elementary-school-aged child touching a robot hand.

In a notable shift toward sanctioned use of AI in schools, some educators in grades 3–12 are now using a ChatGPT-powered grading tool called Writable, reports Axios. The tool, acquired last summer by Houghton Mifflin Harcourt, is designed to streamline the grading process, potentially offering time-saving benefits for teachers. But is it a good idea to outsource critical feedback to a machine?

Writable lets teachers submit student essays for analysis by ChatGPT, which then provides commentary and observations on the work. The AI-generated feedback goes to teacher review before being passed on to students so that a human remains in the loop.

“Make feedback more actionable with AI suggestions delivered to teachers as the writing happens,” Writable promises on its AI website. “Target specific areas for improvement with powerful, rubric-aligned comments, and save grading time with AI-generated draft scores.” The service also provides AI-written writing-prompt suggestions: “Input any topic and instantly receive unique prompts that engage students and are tailored to your classroom needs.”

Writable can reportedly help a teacher develop a curriculum, although we have not tried the functionality ourselves. “Once in Writable you can also use AI to create curriculum units based on any novel, generate essays, multi-section assignments, multiple-choice questions, and more, all with included answer keys,” the site claims.

The reliance on AI for grading will likely have drawbacks. Automated grading might encourage some educators to take shortcuts, diminishing the value of personalized feedback. Over time, the augmentation from AI may allow teachers to be less familiar with the material they are teaching. The use of cloud-based AI tools may have privacy implications for teachers and students. Also, ChatGPT isn’t a perfect analyst. It can get things wrong and potentially confabulate (make up) false information, possibly misinterpret a student’s work, or provide erroneous information in lesson plans.

Yet, as Axios reports, proponents assert that AI grading tools like Writable may free up valuable time for teachers, enabling them to focus on more creative and impactful teaching activities. The company selling Writable promotes it as a way to empower educators, supposedly offering them the flexibility to allocate more time to direct student interaction and personalized teaching. Of course, without an in-depth critical review, all claims should be taken with a huge grain of salt.

Amid these discussions, there’s a divide among parents regarding the use of AI in evaluating students’ academic performance. A recent poll of parents revealed mixed opinions, with nearly half of the respondents open to the idea of AI-assisted grading.

As the generative AI craze permeates every space, it’s no surprise that Writable isn’t the only AI-powered grading tool on the market. Others include Crowdmark, Gradescope, and EssayGrader. McGraw Hill is reportedly developing similar technology aimed at enhancing teacher assessment and feedback.

Some teachers are now using ChatGPT to grade papers Read More »

ai-generated-articles-prompt-wikipedia-to-downgrade-cnet’s-reliability-rating

AI-generated articles prompt Wikipedia to downgrade CNET’s reliability rating

AI, AI articles, AI ethics, AI journalism, AI publishing, AI safety, Biz & IT, chatgpt, chatgtp, CNET, journalism, large language models, machine learning, tech publications, wikipedia / /

The hidden costs of AI —

Futurism report highlights the reputational cost of publishing AI-generated content.

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The CNET logo on a smartphone screen.

Wikipedia has downgraded tech website CNET’s reliability rating following extensive discussions among its editors regarding the impact of AI-generated content on the site’s trustworthiness, as noted in a detailed report from Futurism. The decision reflects concerns over the reliability of articles found on the tech news outlet after it began publishing AI-generated stories in 2022.

Around November 2022, CNET began publishing articles written by an AI model under the byline “CNET Money Staff.” In January 2023, Futurism brought widespread attention to the issue and discovered that the articles were full of plagiarism and mistakes. (Around that time, we covered plans to do similar automated publishing at BuzzFeed.) After the revelation, CNET management paused the experiment, but the reputational damage had already been done.

Wikipedia maintains a page called “Reliable sources/Perennial sources” that includes a chart featuring news publications and their reliability ratings as viewed from Wikipedia’s perspective. Shortly after the CNET news broke in January 2023, Wikipedia editors began a discussion thread on the Reliable Sources project page about the publication.

“CNET, usually regarded as an ordinary tech RS [reliable source], has started experimentally running AI-generated articles, which are riddled with errors,” wrote a Wikipedia editor named David Gerard. “So far the experiment is not going down well, as it shouldn’t. I haven’t found any yet, but any of these articles that make it into a Wikipedia article need to be removed.”

After other editors agreed in the discussion, they began the process of downgrading CNET’s reliability rating.

As of this writing, Wikipedia’s Perennial Sources list currently features three entries for CNET broken into three time periods: (1) before October 2020, when Wikipedia considered CNET a “generally reliable” source; (2) between October 2020 and October 2022, where Wikipedia notes that the site was acquired by Red Ventures in October 2020, “leading to a deterioration in editorial standards” and saying there is no consensus about reliability; and (3) between November 2022 and present, where Wikipedia currently considers CNET “generally unreliable” after the site began using an AI tool “to rapidly generate articles riddled with factual inaccuracies and affiliate links.”

A screenshot of a chart featuring CNET's reliability ratings, as found on Wikipedia's

Enlarge / A screenshot of a chart featuring CNET’s reliability ratings, as found on Wikipedia’s “Perennial Sources” page.

Futurism reports that the issue with CNET’s AI-generated content also sparked a broader debate within the Wikipedia community about the reliability of sources owned by Red Ventures, such as Bankrate and CreditCards.com. Those sites published AI-generated content around the same period of time as CNET. The editors also criticized Red Ventures for not being forthcoming about where and how AI was being implemented, further eroding trust in the company’s publications. This lack of transparency was a key factor in the decision to downgrade CNET’s reliability rating.

In response to the downgrade and the controversies surrounding AI-generated content, CNET issued a statement that claims that the site maintains high editorial standards.

“CNET is the world’s largest provider of unbiased tech-focused news and advice,” a CNET spokesperson said in a statement to Futurism. “We have been trusted for nearly 30 years because of our rigorous editorial and product review standards. It is important to clarify that CNET is not actively using AI to create new content. While we have no specific plans to restart, any future initiatives would follow our public AI policy.”

This article was updated on March 1, 2024 at 9: 30am to reflect fixes in the date ranges for CNET on the Perennial Sources page.

AI-generated articles prompt Wikipedia to downgrade CNET’s reliability rating Read More »

tyler-perry-puts-$800-million-studio-expansion-on-hold-because-of-openai’s-sora

Tyler Perry puts $800 million studio expansion on hold because of OpenAI’s Sora

AI, AI and jobs, AI ethics, AI safety, Biz & IT, generative ai, machine learning, openai, Sora, Tyler Perry, video synthesis / /

The Synthetic Screen —

Perry: Mind-blowing AI video-generation tools “will touch every corner of our industry.”

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Tyler Perry in 2022.

Enlarge / Tyler Perry in 2022.

In an interview with The Hollywood Reporter published Thursday, filmmaker Tyler Perry spoke about his concerns related to the impact of AI video synthesis on entertainment industry jobs. In particular, he revealed that he has suspended a planned $800 million expansion of his production studio after seeing what OpenAI’s recently announced AI video generator Sora can do.

“I have been watching AI very closely,” Perry said in the interview. “I was in the middle of, and have been planning for the last four years… an $800 million expansion at the studio, which would’ve increased the backlot a tremendous size—we were adding 12 more soundstages. All of that is currently and indefinitely on hold because of Sora and what I’m seeing. I had gotten word over the last year or so that this was coming, but I had no idea until I saw recently the demonstrations of what it’s able to do. It’s shocking to me.”

OpenAI, the company behind ChatGPT, revealed a preview of Sora’s capabilities last week. Sora is a text-to-video synthesis model, and it uses a neural network—previously trained on video examples—that can take written descriptions of a scene and turn them into high-definition video clips up to 60 seconds long. Sora caused shock in the tech world because it appeared to surpass other AI video generators in capability dramatically. It seems that a similar shock also rippled into adjacent professional fields. “Being told that it can do all of these things is one thing, but actually seeing the capabilities, it was mind-blowing,” Perry said in the interview.

Tyler Perry Studios, which the actor and producer acquired in 2015, is a 330-acre lot located in Atlanta and is one of the largest film production facilities in the United States. Perry, who is perhaps best known for his series of Madea films, says that technology like Sora worries him because it could make the need for building sets or traveling to locations obsolete. He cites examples of virtual shooting in the snow of Colorado or on the Moon just by using a text prompt. “This AI can generate it like nothing.” The technology may represent a radical reduction in costs necessary to create a film, and that will likely put entertainment industry jobs in jeopardy.

“It makes me worry so much about all of the people in the business,” he told The Hollywood Reporter. “Because as I was looking at it, I immediately started thinking of everyone in the industry who would be affected by this, including actors and grip and electric and transportation and sound and editors, and looking at this, I’m thinking this will touch every corner of our industry.”

You can read the full interview at The Hollywood Reporter, which did an excellent job of covering Perry’s thoughts on a technology that may end up fundamentally disrupting Hollywood. To his mind, AI tech poses an existential risk to the entertainment industry that it can’t ignore: “There’s got to be some sort of regulations in order to protect us. If not, I just don’t see how we survive.”

Perry also looks beyond Hollywood and says that it’s not just filmmaking that needs to be on alert, and he calls for government action to help retain human employment in the age of AI. “If you look at it across the world, how it’s changing so quickly, I’m hoping that there’s a whole government approach to help everyone be able to sustain.”

Tyler Perry puts $800 million studio expansion on hold because of OpenAI’s Sora Read More »

us-says-ai-models-can’t-hold-patents

US says AI models can’t hold patents

AI, AI ethics, Biz & IT, copyright, machine learning, patents, US Patent and Trademark Office, USPTO / /

Robot inventors dismayed —

Inventors must be human, but there’s still a condition where AI can officially help.

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An illustrated concept of a digital brain, crossed out.

On Tuesday, the United States Patent and Trademark Office (USPTO) published guidance on inventorship for AI-assisted inventions, clarifying that while AI systems can play a role in the creative process, only natural persons (human beings) who make significant contributions to the conception of an invention can be named as inventors. It also rules out using AI models to churn out patent ideas without significant human input.

The USPTO says this position is supported by “the statutes, court decisions, and numerous policy considerations,” including the Executive Order on AI issued by President Biden. We’ve previously covered attempts, which have been repeatedly rejected by US courts, by Dr. Stephen Thaler to have an AI program called “DABUS” named as the inventor on a US patent (a process begun in 2019).

This guidance follows themes previously set by the US Copyright Office (and agreed upon by a judge) that an AI model cannot own a copyright for a piece of media and that substantial human contributions are required for copyright protection.

Even though an AI model itself cannot be named an inventor or joint inventor on a patent, using AI assistance to create an invention does not necessarily disqualify a human from holding a patent, as the USPTO explains:

“While AI systems and other non-natural persons cannot be listed as inventors on patent applications or patents, the use of an AI system by a natural person(s) does not preclude a natural person(s) from qualifying as an inventor (or joint inventors) if the natural person(s) significantly contributed to the claimed invention.”

However, the USPTO says that significant human input is required for an invention to be patentable: “Maintaining ‘intellectual domination’ over an AI system does not, on its own, make a person an inventor of any inventions created through the use of the AI system.” So a person simply overseeing an AI system isn’t suddenly an inventor. The person must make a significant contribution to the conception of the invention.

If someone does use an AI model to help create patents, the guidance describes how the application process would work. First, patent applications for AI-assisted inventions must name “the natural person(s) who significantly contributed to the invention as the inventor,” and additionally, applications must not list “any entity that is not a natural person as an inventor or joint inventor, even if an AI system may have been instrumental in the creation of the claimed invention.”

Reading between the lines, it seems the contributions made by AI systems are akin to contributions made by other tools that assist in the invention process. The document does not explicitly say that the use of AI is required to be disclosed during the application process.

Even with the published guidance, the USPTO is seeking public comment on the newly released guidelines and issues related to AI inventorship on its website.

US says AI models can’t hold patents Read More »