AI News Archive: July 15, 2026 — Part 13
Sourced from 500+ daily AI sources, scored by relevance.
- AI Demand Powers Forecast Hike, Profit Gains At Tech Giant ASML
AI Demand Powers Forecast Hike, Profit Gains At Tech Giant ASML Barron's
- Australia unveils AI standards to shape roll out of technology
Australia unveils AI standards to shape roll out of technology Nikkei Asia
- Australia to enact AI regulation laws
Australia to enact AI regulation laws The Straits Times
- Australian PM says to enact laws to govern AI
Australia will enact laws to regulate how artificial intelligence data centers use power and water, and to protect creative copyright, Prime Minister Anthony Albanese said Wednesday.
- Australian PM Says To Enact Laws To Govern AI
Australian PM Says To Enact Laws To Govern AI Barron's
- Here’s what Albo’s ‘Office of AI’ means for Australian tech
Australia’s new AI Office grabs the wheel on standards, data centres and creator rights—but the hard rules stay hazy.
- Australia to impose energy and water guardrails on data centers amid AI boom
Australia to impose energy and water guardrails on data centers amid AI boom The Boston Globe
- Australian PM says to enact laws to govern AI
Australia will enact laws to regulate how artificial intelligence data centers use power and water and to protect creative copyright, Prime Minister Anthony Albanese said Wednesday.
- 26 Meta employees accuse Mark Zuckerberg of using AI to target 8,000 layoffs against workers on medical, parental or family leave
26 Meta employees accuse Mark Zuckerberg of using AI to target 8,000 layoffs against workers on medical, parental or family leave Fortune
- Meta employees sue, alleging AI-driven layoff picks hit workers on medical, parental leave
Meta faces a lawsuit from twenty-six employees alleging AI selection for layoffs. These workers claim the company's systems unfairly targeted those on medical and family leave. The complaint states that AI did not account for protected leave periods. This process allegedly resulted in a disproportionate impact on women and disabled individuals. The lawsuit seeks to preserve employment status pending arbitration proceedings.
- Meta faces lawsuit from 26 employees over AI-based layoffs
Meta faces lawsuit from 26 employees over AI-based layoffs YourStory.com
- Meta used AI to target workers with medical conditions for layoffs, lawsuit claims
Meta used AI to target workers with medical conditions for layoffs, lawsuit claims
- Meta employees sue over layoffs they say were driven by discriminatory AI selection systems
Former and current Meta employees are suing the company in a California federal court over AI-driven mass layoffs. Meta allegedly used internal AI systems to generate the layoff lists when it cut 8,000 workers, disproportionately targeting employees with disabilities or on parental leave. The article Meta employees sue over layoffs they say were driven by discriminatory AI selection systems appeared first on The Decoder .
- Meta used AI to target workers with medical conditions for layoffs, lawsuit claims
Meta used AI to target workers with medical conditions for layoffs, lawsuit claims The Japan Times
- 26 Meta employees sue, alleging AI-driven layoff picks hit workers on medical and parental leave
26 Meta employees sue, alleging AI-driven layoff picks hit workers on medical and parental leave Gulf News
- Meta used AI to target workers with medical conditions for layoffs, lawsuit claims
UPDATE 2-Meta used AI to target workers with medical conditions for layoffs, lawsuit claims
- Lawsuit Says Meta's AI Targeted Workers With Medical Conditions for Layoffs
Lawsuit Says Meta's AI Targeted Workers With Medical Conditions for Layoffs PCMag Australia
- Lawsuit Says Meta's AI Targeted Workers With Medical Conditions for Layoffs
Lawsuit Says Meta's AI Targeted Workers With Medical Conditions for Layoffs PCMag UK
- Meta sued over claims AI penalized workers who took maternity leave
A group of 26 Meta employees has sued the company, claiming it used artificial intelligence systems that disproportionately targeted those on medical or family leave for layoffs
- Meta sued over claims AI selected staff with medical conditions for layoffs
Meta sued over claims AI selected staff with medical conditions for layoffs Computing UK
- Meta’s AI-based layoffs allegedly targeted workers who had taken protected leave
The company used “a constellation of internal artificial-intelligence systems” to determine who would be included in its 10% reduction in force, per a lawsuit.
- 26 Meta employees sue, alleging AI-driven layoff picks hit workers on medical and parental leave
26 Meta employees sue, alleging AI-driven layoff picks hit workers on medical and parental leave The Boston Globe
- 26 Meta employees sue, alleging AI-driven layoff picks hit workers on medical and parental leave
26 Meta employees sue, alleging AI-driven layoff picks hit workers on medical and parental leave Dallas News
- Meta employees sue on allegations company used AI to target workers on medical, parental leave for layoffs
A group of 26 Meta employees allege in a lawsuit that the company used AI systems and keystroke monitoring to target workers on medical or parental leave for mass layoffs.
- Meta Employees Allege Discriminatory AI-driven Layoffs
Meta Employees Allege Discriminatory AI-driven Layoffs Barron's
- Lawsuit accuses Meta of using AI to target workers for layoffs who took medical and maternity leave
Lawsuit accuses Meta of using AI to target workers for layoffs who took medical and maternity leave The Mercury News
- 26 Meta employees sue, alleging AI-driven layoff picks hit workers on medical and parental leave
26 Meta employees sue, alleging AI-driven layoff picks hit workers on medical and parental leave Austin American-Statesman
- Meta employees allege discriminatory AI-driven layoffs
Twenty-six Meta employees have filed a lawsuit accusing the tech giant of using artificial intelligence to select workers for mass layoffs, a claim strongly denied by the trillion-dollar company.
- Inside Anthropic's State-by-State Plan to Ratchet up AI Rules
Inside Anthropic's State-by-State Plan to Ratchet up AI Rules Business Insider
- What smart people are saying about IBM's AI warning and SaaSpocalypse fears
What smart people are saying about IBM's AI warning and SaaSpocalypse fears Business Insider
- IBM and other old-school tech companies feel the AI pinch
IBM and other old-school tech companies feel the AI pinch marketplace.org
- IBM Misses, IBM’s Mainframe Moat, IBM’s Many AI Problems
IBM announced preliminary results that spooked the software market generally; this is a story, however, specifically about IBM and its mainframe franchise.
- ‘We did not adapt and move quickly enough’: IBM CEO Arvind Krishna laments enterprise spending pivot as company issues profit warning
‘We did not adapt and move quickly enough’: IBM CEO Arvind Krishna laments enterprise spending pivot as company issues profit warning IT Pro
- IBM Stock: What Wall Street Is Watching Next After 25% Tumble
IBM stock ticked slightly lower Wednesday morning, following a brutal selloff on Tuesday. The post IBM Stock: What Wall Street Is Watching Next After 25% Tumble appeared first on Investor's Business Daily .
- UAE's big bet on AI
In Abu Dhabi , the largest emirate in the United Arab Emirates, AI is as much a part of daily life as reporting a pothole or making a doctor's appointment or paying a parking ticket — because AI does all that for you. Abu Dhabi, the capital of one of the world's wealthiest and most globalized business hubs, has near-universal adoption of an app that knows when you need to renew your national ID or health insurance or vehicle registration. The app's "AutoGov" feature goes a step further: It handles the paperwork and pays what's owed without being asked. Why it matters: The UAE made a massive bet on AI, spending billions on infrastructure and research, backed by long-term thinking and alignment from top leaders. Before the war with Iran, the bet was paying off massively. "People make money here and bring money here," a UAE resident told Jim VandeHei and me when we visited just before the war. The war rattled the UAE's AI ambitions and stirred fears about visiting, given the constant threat of Iranian attack. UAE leaders tell us they remain all-in on AI: They're willing to work with both the U.S. and China , and see the technology as the key to their future beyond oil. The big picture: Yousef Al Otaiba , the UAE's longtime ambassador to Washington, told me his country "recognized early that data is destiny — and our leaders didn't wait for AI to arrive before preparing for it." The UAE appointed an AI minister (said to be the world's first ) nearly a decade ago, in 2017. Two years later, it opened what's billed as the world's first graduate-level university dedicated to AI, Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) in Masdar City, Abu Dhabi. The UAE was built on oil. But leaders aggressively diversified into what The New York Times recently called "the ultimate globalized city — a Switzerland on the Persian Gulf." Dubai, the UAE's biggest city, is rollicking, wealthy and Western-friendly. It's one of the world's top business hubs, and is home to the world's tallest building and the world's busiest international airport. That prosperity is being tested by war in the Middle East. But business leaders tell us AI investments from around the world have kept the UAE powerful amid the danger and disruption plaguing the Persian Gulf. On Tuesday night, The Wall Street Journal reported that the Trump administration is rewarding the UAE for its help with the Iran war by expanding access to coveted AI chips, capping "a yearslong push by the Gulf state to obtain American technology to diversify its economy." Reality check: This is as much opportunism as strategic vision. The UAE has an all-powerful royal family that controls government and business, allowing wholesale societal changes that couldn't be replicated in a democracy. Zoom in: His Excellency Dr. Mohamed Al Askar , director general of TAMM, as the app is called, took me behind the scenes of Abu Dhabi's " AI-native government " in two lengthy interviews. He and the emirate's Department of Government Enablement host a parade of ministers from other governments who dream of replicating TAMM. "If you look at the UAE as a whole, this is rooted in our leadership vision," said Al Askar, a leader in digital strategy and technological innovation. "This has become part of our DNA. ... This is why I believe the UAE can be a haven for any entrepreneur who wants to test and experiment with AI." How it works: TAMM is Arabic for "Consider it done." The app has a "Snap & Report" section where you can take a photo of a streetlight that doesn't work and submit it to the government. "AI will analyze that photo," the director general said. "We'll route it to the concerned entity. And the entity will fix it. And listen to this: The entity doesn't have the right to close your request until you confirm. So you as a customer have the power." If you take a photo of your food, the app will give you a letter grade for healthiness. When I asked what's next, Al Askar said: "We're actually cooking a lot of things. I wish I could share what we're cooking. But we will surprise you." What we're watching: The UAE's national AI strategy vows that by 2031, the country will have a "reputation as an AI destination ... a magnet that attracts the best talents from the globe to conduct their experiments on AI solutions in the UAE." PwC says that by 2030, AI could contribute 11% of the country's GDP, adding $320 billion to the Middle East economy. Go deeper : UAE wants to disrupt the AI superpowers.
- The Hard Part of AI Has Arrived: Why UAE Businesses Must Rethink Readiness, Trust and Resilience Now
The Hard Part of AI Has Arrived: Why UAE Businesses Must Rethink Readiness, Trust and Resilience Now Gulf News
- US grapples with rise of Chinese open-source AI
Palantir’s chief technology officer said the Chinese technology poses an economic threat to the US.
- Washington confronts China’s open-source models
American AI labs view Chinese open-source models as essentially stolen goods, built with the help of American frontier models to generate synthetic training data — a process known as distillation.
- AI is great if you're an electrician
The AI data center boom is creating an unprecedented demand for electricians and skilled trades, pushing wages higher and reshaping career paths
- DeepSeek founder Liang Wenfeng is world’s richest creator of AI models
DeepSeek founder Liang Wenfeng is world’s richest creator of AI models The Straits Times
- Report: AI struggles to replace nurses, teachers and labourers
Report: AI struggles to replace nurses, teachers and labourers YourStory.com
- 71% of smartphone users now use generative AI: CMR study
71% of smartphone users now use generative AI: CMR study YourStory.com
- Google Images turns 25 with AI image generation and a new look
Google Images turns 25 with AI image generation and a new look YourStory.com
- Google Images Marks Its 25th Birthday by Adding AI Image Generation
Google Images Marks Its 25th Birthday by Adding AI Image Generation PCMag Middle East
- Google Search will let you create AI images for free soon — here's how it works
Google Search will let you create AI images for free soon — here's how it works Tom's Guide
- Karnataka finalising data center policy to support AI and GCC growth
Government of Karnataka is finalising a comprehensive data center policy aimed at strengthening the state's digital infrastructure to support artificial intelligence (AI) workloads and the continued expansion of Global Capability Centres (GCCs). The post Karnataka finalising data center policy to support AI and GCC growth appeared first on Express Computer .
- US could set up "Standards Body" to regulate frontier AI models
According to Demis Hassabis, Co-Founder & CEO, Google DeepMind, the US is well positioned to take the first step in developing such a framework given its economic and technical standing.
- DeepMind CEO again pushes for a frontier AI standards body
Google DeepMind CEO Demis Hassabis on Tuesday reiterated his push for an AI industry self-regulation effort, led by the US government, that is particularly focused on artificial general intelligence (AGI) and national security. But it is precisely that focus on national security that may make the results of such an effort, assuming it happens, less than palatable outside of the US. “The rapid progress we’re seeing in AI requires a new approach to testing frontier AI model capabilities that is dynamic, adaptable, and rigorous,” Hassabis wrote . “The US is well positioned, given its economic and technical standing, to take the first step in developing such a framework. It could establish a new Standards Body modelled on a federally overseen public-private partnership or self-regulatory organization, much like the Financial Industry Regulatory Authority (FINRA), with a board that includes independent leading technical experts and open-source representatives.” He noted, however, that the funding would need to be substantial, and would most likely come from industry, to allow the new body to attract world-class technical talent and obtain the necessary compute resources for large-scale testing. Hassabis said he would propose that the organization “be responsible for developing assessment protocols and working with appropriate federal agencies and the US National Labs to conduct testing in areas relevant to national security,” and that AI vendor participants would be encouraged to adopt best practices, such as publishing model cards with technical details, maintaining strong internal cybersecurity, vetting key personnel, and providing sufficient resourcing for safety and security research. This is not the first time Hassabis has expressed worries about AGI . He has already worked on a US government initiative evaluating AI safety , which involved DeepMind, Microsoft and xAI (now SpaceXAI) working with the Center for AI Standards and Innovation (CAISI), a division of the US Department of Commerce. It allowed CAISI to conduct pre-deployment evaluations and targeted research to “better assess frontier AI capabilities and advance the state of AI security.” The rest of the world may have concerns Analysts and consultants were mixed about the move, with most expressing concerns about whether an industry-focused group would prioritize the public’s best interests. “Self-regulation is not viable because it implies everyone is able to regulate themselves and will do so in line with the best interests of the public. Most tech vendors don’t have the capacity to self-regulate. They would just prefer a set of rules within which they can operate,” said Gartner VP analyst Nader Henein . “For-profit organizations are required to do what is best for their shareholders, and external regulation ensures that those organizations are never in a conflict of interest where they have to choose between what is good for their shareholders and what is good for the public.” And, said Sanchit Vir Gogia , chief analyst at Greyhound Research, given the international nature of AI models, an effort coordinated by the US government might alienate other countries. “National security is the proposal’s accelerator in Washington and its poison pill abroad: the framing that opens the only gate available at home invites foreign capitals to read the institution as an instrument of American strategy,” he pointed out. “The map is already plural,” he said. “Brussels switches on enforcement powers over general-purpose models [starting in August 2026], London runs the AI Security Institute, and Beijing licenses on its own terms. California and New York have legislated for frontier models at home. The durable route is shared technical evidence with sovereign enforcement, sealed through mutual recognition rather than deference, with India and the other major non-Western markets holding authorship rather than seats.” Gogia added that the rules enacted by even such a group may not address all of the key concerns of enterprise IT. A US government effort along the lines that Hassabis is proposing would result in testing that “sits close to intelligence and industrial policy, and those functions will not stay neatly separated. A model can pass every catastrophic-risk test and still fail the enterprise on privacy, reliability, and liability,” he noted. Walmart’s former director of cybersecurity Steven Eric Fisher , who is now an independent cybersecurity consultant, said he found the proposal “well-intentioned, but it addresses a highly polarized topic at a time when commercial interests carry unprecedented political influence, which is not always applied benevolently.” He added, “an exclusive US standard that is not globally respected or enforceable would likely fail to achieve its core purpose and would place US companies at a competitive disadvantage.” Aman Mahapatra , chief strategy officer for Tribeca Softtech, a New York City-based technology consulting firm, said that a deep dive into how FINRA operates today is illustrative of what IT leaders can expect from this effort, assuming the industry adopts that model. “When the CEOs of the five companies that would be regulated are also the primary drafters of the standards, the standards will reflect those companies’ interests. FINRA has an independent board, but the operational reality is that member firm perspectives dominate the working groups that write the actual rules,” he said. “There is no reason to expect an AI equivalent to work differently, and every reason to expect it to work worse, because AI standardization is happening faster than any industry has ever attempted to standardize itself, and speed is the enemy of independent oversight.” Carmi Levy , an independent technology analyst, was even more emphatically opposed to the Hassabis proposal. “Asking Big Tech companies to self-police is analogous to allowing foxes to guard the henhouse. It hasn’t worked to date, and it won’t work going forward. Expecting these organizations to somehow change their ways at this point in time represents the height of naïve thinking,” Levy said. “The framework proposed by Demis Hassabis is a self-serving roadmap for an industry bent on racing to the AI horizon regardless of the harms caused along the way. It is impossible to quantify the dangers to broader society should frameworks allowing self-regulation become the norm.” Some love the proposal An almost completely opposite stance came from Yuri Goryunov , CIO of consulting firm Acceligence, who applauded the proposed move. “This is one of the rare setups where industry self-regulation has a real shot, and enterprise IT should be enthusiastically rooting for it,” he said. “It fails when harms are externalized, such as in social media content moderation. Or when the overseer outsources judgment to the overseen, such as the FAA’s delegation to Boeing before the 737 MAX. It works when everyone in the industry shares the catastrophic downside.” He suggested, however, that the best precedent here isn’t FINRA, it’s INPO, the Institute of Nuclear Power Operations, which the nuclear industry created within months of the 1979 Three Mile Island partial reactor meltdown “on the logic that an accident anywhere is an accident everywhere. INPO peer-reviews every US plant, its evaluations move insurance premiums, and it sits on top of the NRC’s statutory floor. That is a public-private stack very close to what Hassabis is describing. Frontier AI has the same structure: one lab’s catastrophic failure brings regulation down on all of them.” For enterprise CIOs and other IT executives, Goryunov said, that model has the potential for being a big win. “ Today, every enterprise duplicates the same AI diligence of red-teaming, eval suites, governance committees and each does so with less information than any certifying body would have,” Goryunov said. “A credible standards regime does for AI what UL did for electrical equipment and SOC2 did for cloud: it converts an unknowable risk into a procurable product and gives boards a defensible standard of care. That’s not red tape. That’s peace of mind with an audit trail.” However, Mahapatra said, “the countervailing view is that the alternative to industry-led standards is probably not thoughtful legislation. It is probably no standards, or state-by-state fragmentation, or the current pattern of ex-post enforcement actions where regulators surface concerns years after harm has already occurred.” Thus, he noted, “Hassabis is making the reasonable argument that imperfect fast standards are better than perfect slow ones, and there is genuine merit to that view for topics like agent identity, evaluation methodology, and interoperability, which are exactly the areas OpenClaw is also targeting .”
- DeepMind CEO again pushes for a frontier AI standards body
Google DeepMind CEO Demis Hassabis on Tuesday reiterated his push for an AI industry self-regulation effort, led by the US government, that is particularly focused on artificial general intelligence (AGI) and national security. But it is precisely that focus on national security that may make the results of such an effort, assuming it happens, less than palatable outside of the US. “The rapid progress we’re seeing in AI requires a new approach to testing frontier AI model capabilities that is dynamic, adaptable, and rigorous,” Hassabis wrote . “The US is well positioned, given its economic and technical standing, to take the first step in developing such a framework. It could establish a new Standards Body modelled on a federally overseen public-private partnership or self-regulatory organization, much like the Financial Industry Regulatory Authority (FINRA), with a board that includes independent leading technical experts and open-source representatives.” He noted, however, that the funding would need to be substantial, and would most likely come from industry, to allow the new body to attract world-class technical talent and obtain the necessary compute resources for large-scale testing. Hassabis said he would propose that the organization “be responsible for developing assessment protocols and working with appropriate federal agencies and the US National Labs to conduct testing in areas relevant to national security,” and that AI vendor participants would be encouraged to adopt best practices, such as publishing model cards with technical details, maintaining strong internal cybersecurity, vetting key personnel, and providing sufficient resourcing for safety and security research. This is not the first time Hassabis has expressed worries about AGI . He has already worked on a US government initiative evaluating AI safety , which involved DeepMind, Microsoft and xAI (now SpaceXAI) working with the Center for AI Standards and Innovation (CAISI), a division of the US Department of Commerce. It allowed CAISI to conduct pre-deployment evaluations and targeted research to “better assess frontier AI capabilities and advance the state of AI security.” The rest of the world may have concerns Analysts and consultants were mixed about the move, with most expressing concerns about whether an industry-focused group would prioritize the public’s best interests. “Self-regulation is not viable because it implies everyone is able to regulate themselves and will do so in line with the best interests of the public. Most tech vendors don’t have the capacity to self-regulate. They would just prefer a set of rules within which they can operate,” said Gartner VP analyst Nader Henein . “For-profit organizations are required to do what is best for their shareholders, and external regulation ensures that those organizations are never in a conflict of interest where they have to choose between what is good for their shareholders and what is good for the public.” And, said Sanchit Vir Gogia , chief analyst at Greyhound Research, given the international nature of AI models, an effort coordinated by the US government might alienate other countries. “National security is the proposal’s accelerator in Washington and its poison pill abroad: the framing that opens the only gate available at home invites foreign capitals to read the institution as an instrument of American strategy,” he pointed out. “The map is already plural,” he said. “Brussels switches on enforcement powers over general-purpose models [starting in August 2026], London runs the AI Security Institute, and Beijing licenses on its own terms. California and New York have legislated for frontier models at home. The durable route is shared technical evidence with sovereign enforcement, sealed through mutual recognition rather than deference, with India and the other major non-Western markets holding authorship rather than seats.” Gogia added that the rules enacted by even such a group may not address all of the key concerns of enterprise IT. A US government effort along the lines that Hassabis is proposing would result in testing that “sits close to intelligence and industrial policy, and those functions will not stay neatly separated. A model can pass every catastrophic-risk test and still fail the enterprise on privacy, reliability, and liability,” he noted. Walmart’s former director of cybersecurity Steven Eric Fisher , who is now an independent cybersecurity consultant, said he found the proposal “well-intentioned, but it addresses a highly polarized topic at a time when commercial interests carry unprecedented political influence, which is not always applied benevolently.” He added, “an exclusive US standard that is not globally respected or enforceable would likely fail to achieve its core purpose and would place US companies at a competitive disadvantage.” Aman Mahapatra , chief strategy officer for Tribeca Softtech, a New York City-based technology consulting firm, said that a deep dive into how FINRA operates today is illustrative of what IT leaders can expect from this effort, assuming the industry adopts that model. “When the CEOs of the five companies that would be regulated are also the primary drafters of the standards, the standards will reflect those companies’ interests. FINRA has an independent board, but the operational reality is that member firm perspectives dominate the working groups that write the actual rules,” he said. “There is no reason to expect an AI equivalent to work differently, and every reason to expect it to work worse, because AI standardization is happening faster than any industry has ever attempted to standardize itself, and speed is the enemy of independent oversight.” Carmi Levy , an independent technology analyst, was even more emphatically opposed to the Hassabis proposal. “Asking Big Tech companies to self-police is analogous to allowing foxes to guard the henhouse. It hasn’t worked to date, and it won’t work going forward. Expecting these organizations to somehow change their ways at this point in time represents the height of naïve thinking,” Levy said. “The framework proposed by Demis Hassabis is a self-serving roadmap for an industry bent on racing to the AI horizon regardless of the harms caused along the way. It is impossible to quantify the dangers to broader society should frameworks allowing self-regulation become the norm.” Some love the proposal An almost completely opposite stance came from Yuri Goryunov , CIO of consulting firm Acceligence, who applauded the proposed move. “This is one of the rare setups where industry self-regulation has a real shot, and enterprise IT should be enthusiastically rooting for it,” he said. “It fails when harms are externalized, such as in social media content moderation. Or when the overseer outsources judgment to the overseen, such as the FAA’s delegation to Boeing before the 737 MAX. It works when everyone in the industry shares the catastrophic downside.” He suggested, however, that the best precedent here isn’t FINRA, it’s INPO, the Institute of Nuclear Power Operations, which the nuclear industry created within months of the 1979 Three Mile Island partial reactor meltdown “on the logic that an accident anywhere is an accident everywhere. INPO peer-reviews every US plant, its evaluations move insurance premiums, and it sits on top of the NRC’s statutory floor. That is a public-private stack very close to what Hassabis is describing. Frontier AI has the same structure: one lab’s catastrophic failure brings regulation down on all of them.” For enterprise CIOs and other IT executives, Goryunov said, that model has the potential for being a big win. “ Today, every enterprise duplicates the same AI diligence of red-teaming, eval suites, governance committees and each does so with less information than any certifying body would have,” Goryunov said. “A credible standards regime does for AI what UL did for electrical equipment and SOC2 did for cloud: it converts an unknowable risk into a procurable product and gives boards a defensible standard of care. That’s not red tape. That’s peace of mind with an audit trail.” However, Mahapatra said, “the countervailing view is that the alternative to industry-led standards is probably not thoughtful legislation. It is probably no standards, or state-by-state fragmentation, or the current pattern of ex-post enforcement actions where regulators surface concerns years after harm has already occurred.” Thus, he noted, “Hassabis is making the reasonable argument that imperfect fast standards are better than perfect slow ones, and there is genuine merit to that view for topics like agent identity, evaluation methodology, and interoperability, which are exactly the areas OpenClaw is also targeting .” This article originally appeared on CIO.com.
- Hassabis’ AI Standards Idea Gets Support—What’s Next?
Hassabis’ AI Standards Idea Gets Support—What’s Next? The Information