logo
'A sandwich has more regulation': AI pioneer warns of dangerous lack of oversight in the advancement of artificial intelligence

'A sandwich has more regulation': AI pioneer warns of dangerous lack of oversight in the advancement of artificial intelligence

Time of India17-06-2025

Billions in, No Seatbelts On
You Might Also Like:
Godfather of AI reveals the one job robots can't steal, and it does not need a desk
Into the Fog Without a Map
When the Architect Questions the Blueprint
The Clock Is Ticking
In a revelation that's equal parts staggering and sobering, Yoshua Bengio—one of the world's foremost authorities on artificial intelligence—recently declared in a TED Talk that a sandwich is more regulated than AI.Yes, you read that right! 'A sandwich has more regulation than AI,' Bengio said, in a recent TED Talk with a comparison that's both absurd and alarmingly true. While food safety standards demand strict oversight on how a sandwich is prepared, stored, and sold, the world's most transformative technology—capable of rewriting economies, societies, and perhaps humanity itself—is operating in a near-total regulatory vacuum.Bengio, who received the Turing Award in 2018 alongside Geoffrey Hinton and Yann LeCun and is often referred to as a " Godfather of AI ," warned that hundreds of billions of dollars are being pumped into AI research each year. Yet, we still have no assurance that the intelligent machines being developed won't act against human interests.'These companies have a stated goal of building machines that will be smarter than us and can replace human labor,' Bengio noted. 'Yet, we still don't know how to make sure they won't turn against us.'His statement comes amid growing concerns from national security agencies that advanced AI systems could be weaponized. He referenced a chilling example: OpenAI 's Q1 system, which in a 2024 evaluation saw its risk status upgraded from 'low' to 'medium'—just one step below being deemed unacceptable.Bengio likened the current AI trajectory to 'blindly driving into a fog,' warning that this unregulated race toward artificial general intelligence (AGI) could result in a catastrophic loss of human control. But he offered a glimmer of hope too.'There is still a bit of time,' he said. 'My team and I are working on a technical solution… We call it Scientist AI .'Designed to model the reasoning of a selfless, non-agentive scientist, the 'Scientist AI' aims to serve as a guardrail against untrustworthy AI agents. It's a system built to predict risks rather than act—precisely the kind of neutral evaluator Bengio believes could keep rogue systems in check.Bengio's concerns carry weight not only because of his stature—he's the most-cited living scientist across all disciplines according to h-index and total citations—but also because of his personal reckoning with AI's direction.In 2023, he publicly stated he felt 'lost' over how his life's work was being used. That same year, he co-signed a Future of Life Institute open letter urging a pause on training models more powerful than GPT-4. Since then, he has emerged as one of the most prominent voices calling for AI safety legislation , international oversight, and ethical governance.In a 2025 Fortune article, Bengio criticized the AI arms race , arguing that companies are prioritizing capability over caution. He supported California's SB 1047 bill, which requires large AI model developers to conduct risk assessments—a law he believes is the 'bare minimum for effective regulation.'Despite the mounting evidence and expert warnings, real regulation remains elusive. And the absurdity of the moment—that a meat-and-bread sandwich is subject to more scrutiny than technologies that may soon outthink and outmaneuver us—underscores just how unprepared we are for what's coming.As Bengio concluded in his talk, 'We need a lot more of these scientific projects to explore solutions to the AI safety challenges—and we need to do it quickly.' Because if the godfathers of AI are now sounding the alarm, perhaps it's time we start listening—before the machines stop asking for permission.

Orange background

Try Our AI Features

Explore what Daily8 AI can do for you:

Comments

No comments yet...

Related Articles

AI shift: India's IT majors embrace integration over invention, upskill workforce as global market booms
AI shift: India's IT majors embrace integration over invention, upskill workforce as global market booms

Time of India

time29 minutes ago

  • Time of India

AI shift: India's IT majors embrace integration over invention, upskill workforce as global market booms

AI image Indian IT giants are reorienting their business models around artificial intelligence, shedding traditional digital transformation narratives in favour of AI-native strategies focused on high-margin applications and integration — not foundational AI research. A review of FY25 annual reports of Tata Consultancy Services (TCS), Infosys , Wipro and Tech Mahindra reveals a clear pattern: India's top tech firms are positioning themselves as leading AI integrators, rather than developers of core generative AI models, according to PTI. This pivot comes amid rising global demand for enterprise AI solutions, projected to help push the worldwide AI market to an estimated $1.3 trillion within the next decade. TCS's annual report is themed 'The Perpetually Adaptive Enterprise,' built around an 'AI-First approach.' Infosys's strategy is more direct, under the theme 'AI Your Enterprise,' while Wipro underscores its enabler role with 'Helping Clients Build AI-Powered Future-Ready Businesses.' Tech Mahindra's report similarly highlights 'AI Delivered Right.' 'Let us think of AI as a gifted child prodigy born and brought up in a library,' said Anand G Mahindra, chairman of Mahindra Group. by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like Run Your Business Like a Pro - Top Trending Accounting Software (Check Now) Accounting ERP Click Here Undo 'It has access to all the knowledge in the world. It absorbs everything—information, fact, fiction, truth, untruth, every pattern of human behaviour. Used well, it can create extraordinary value, particularly for businesses like TechM,' he said in the company's annual update, PTI quoted. Workforce upskilling has become a key focus area. TCS reported that over 1 lakh of its employees have acquired higher-order AI/ML and GenAI skills. Infosys said over 2.7 lakh of its workforce is now 'AI-aware.' Wipro and Tech Mahindra are witnessing similar reskilling trends as they transition into AI-first firms. Infosys chairman Nandan Nilekani stressed the urgency of adapting legacy systems for AI compatibility. 'Enterprises must now create a data architecture so that all the firm's data is consumable by AI in a holistic manner,' he said. Nilekani also pushed for enterprises to build 'AI foundries and factories' to fuel innovation and scale. Rather than building their own large language models (LLMs) to rival OpenAI or Google, Indian firms are strengthening partnerships with hyperscalers like Microsoft, Google and AWS, as well as chipmakers such as Nvidia. They are establishing innovation hubs—such as TCS's AI Labs and Infosys's AI Foundry—to help clients experiment with and deploy AI in controlled environments. TCS chairman N Chandrasekaran called generative AI 'a civilisational shift' and said the company will create a 'large pool' of AI agents to work alongside humans in what he termed a 'human-AI' delivery model. Wipro, meanwhile, is realigning its Global Business Lines to sharpen its focus on AI-powered, consulting-led client solutions. 'This realignment will allow us to serve our clients better, enabling us to deliver tailored, high-impact transformation,' said Wipro CEO Srini Pallia. While foundational model development remains the domain of global tech giants, Indian IT leaders are betting that their ability to embed AI into the core of enterprise operations — from finance to manufacturing to customer engagement — will create the most durable long-term value. Stay informed with the latest business news, updates on bank holidays and public holidays . AI Masterclass for Students. Upskill Young Ones Today!– Join Now

Google's AI charge: How Sergey Brin is taking on the might of OpenAI
Google's AI charge: How Sergey Brin is taking on the might of OpenAI

Mint

time36 minutes ago

  • Mint

Google's AI charge: How Sergey Brin is taking on the might of OpenAI

New Delhi/Mountain View, California: In Mountain View, California, right next to Google's three million square-feet Googleplex headquarters, is a satellite office. While, from the outside, there's nothing seemingly special about it, the building currently houses an elite team of specialist engineers who have been tasked with only one thing: build the best foundational artificial intelligence (AI) model in the world. At the centre of its biggest room sits a man who many in Silicon Valley refer to as a living legend—Sergey Brin, Google's co-founder. Brin retired in December 2019 but returned to the company last year to lead a light brigade of over 300 engineers, all of whom are charging at OpenAI's GPT models, Google's primary rival in a high stakes battle. OpenAI's GPT models are disrupting the way people search, posing an existential threat to Alphabet Inc., Google's parent company. Brin is spearheading the development of Gemini, Google's suite of foundational AI models. Gemini's success, or failure, would impact two major areas within Alphabet—Search, and the nascent space of video generation. For one, Search currently accounts for 56% of Alphabet's annual revenue of $350 billion. Search is also a matter of personal pride for Brin and Larry Page, Google's second founder. Giving up its market dominance in Search means letting go of the duo's legacy—their entire life's work. Alongside Search, Brin was also concerned about Sora, OpenAI's video generation model. Last year, Google briefly showcased Veo, its video-generating foundational model. However, the market found Veo to be an effort from Google to catch-up with OpenAI. 'This prompted Brin's efforts to create Google Flow this year and launch the AI subscription plans—all a part of his efforts to show that Google, in fact, is still the behemoth as far as Big Tech is concerned," said a senior executive working on the integration of AI in Google's cloud offerings. He didn't want to be identified. At I/O 2025, an annual developer conference held in May this year, Google launched Flow, a video generation and editing platform that lets users create films with dialogue and background music, without needing any camera, audio and editing setup at all. A second executive, who also didn't want to be identified, said that much of Google's AI showcase at the conference was driven by what Brin's team has been up to. 'The core task that Brin is leading right now is to prove that Google is not following OpenAI's lead in AI—it is ready to lead innovation for others to follow. Last year, announcements that Google made were all either work in progress, or an iteration of what OpenAI had already showcased. This year, we've largely undone that," the executive, who works with Google's worldwide developer relations teams, said. A legacy at risk Much of Google's success, thus far, lies in the 'PageRank' algorithm that made Search the global behemoth that it is today. While the algorithm's patent is owned by Stanford University—Brin's alma mater—he, along with Page, were the ones who invented it. After failing to sell its algorithm to then-market leader Yahoo twice between 1998 and 2002, Google went on to lead the market globally. In 2021, Yahoo was sold to investment fund Apollo Global Management at $4.88 billion. Alphabet, in 2024, generated $350 billion in annual revenue. Page, to be sure, is no longer involved with Google's everyday operations, even though he retains a board seat. Instead, Page is focusing on a new AI venture, Dynatomics, which seeks to use generative AI to automate design-led manufacturing of products. In June 2017, a Stanford University research paper titled 'Attention is all you need', gave birth to the technology behind the transformer model, the fundamental architecture that underpins 'foundational' models. These models, trained on massive troves of data, today crossing trillions, aim to understand, think, calculate and feel like humans. This paper, and the study behind it, was funded by Google. But Google essentially squandered a technology that it believes it should rightfully lead. In November 2022, OpenAI—still not well-known back then—introduced ChatGPT, taking the world by storm and causing futurists to predict the doom of human jobs the way we know it today. Others predicted the nascent technology to have spurred into action an 'AI revolution', a seismic shift in the socio-economic balance akin to the industrial revolution of the 18th century. Alongside OpenAI's shortcut to global stardom, other big tech firms started cashing in on the AI overload. Microsoft was the first to pounce on the opportunity, investing nearly $14 billion in OpenAI and striking various forms of exclusive partnerships. Meta went the open-source way, appearing as a surprise early mover with its Llama family of foundational AI models. By December 2024, Amazon had announced its own family of 'Nova' foundational AI models, even though among Big Tech firms, its direct exposure to AI's algorithmic excellence was the least (Amazon earns its core revenue from e-commerce and cloud services). Apart from Google, only Apple has so far come off worse. The latter's implementation of AI is yet to see any response of enthusiasm from its customers—and analysts remain sceptical about its ability to keep up with the Big Tech fellows. Too big, too slow Analysts state that much of Google's sluggish start in generative AI is attributable to the company's way of functioning. Jayanth N. Kolla, cofounder and partner at consultancy firm Convergence Catalyst, said that at one point, there were concerns internally within senior Google staff that the company was becoming like IBM. 'Too big for its own good, too complacent, and too slow to move on anything," he said. In 2023, Google shared an internal note following the hype and surge of ChatGPT and OpenAI, asking all its employees to use its internal generative AI platform as much as possible. 'The idea was to maximize the usage hours and mine as much data as possible to bring it up to a certain scale," said a third executive who is with Google's software engineering teams. 'Bard and PaLM (the precursors to Gemini), however, underperformed, which spurred Brin to start taking increasing interest in Google's AI progress," the executive added. Brin, who turns 52 this August, isn't being strictly shy about his role. At I/O 2025, he made a surprise appearance at a fireside chat with DeepMind chief and Nobel laureate Demis Hassabis. DeepMind, an AI research laboratory, is a subsidiary of Alphabet. Speaking about why he came out of retirement, Brin said, 'As a computer scientist, it's a very unique time in history. Honestly, anyone who's a computer scientist should not be retired right now, and be working on AI." He added that he intends to make Gemini 'the world's first AGI, before 2030." AGI stands for artificial general intelligence, which is loosely defined as an algorithm that mimics the functioning of the human brain, capable of structuring randomized thought, emotion and empathy—qualities that machines lack. Google showcased more than 16 new products and launches at I/O 2025. The list includes its foundational model's new reasoning capabilities; a 3D video conferencing platform called Google Beam; an always-on version of Gemini Live; a production variant of Project Astra, a multi-modal, all-purpose AI assistant, and Android XR, a new platform for wearable devices. The headlines, however, were made by Search introducing a new 'AI mode', showcasing for the first time a chat-based interface that changes the way Google's search engine has worked since being incorporated in 1998. Beating OpenAI Insiders Mint spoke to said that over the past 12 months, Brin has a single-minded focus—beating OpenAI. A fourth executive working on product management at Google said that the transformer model 'should be rightfully our area of expertise and leadership." Since 2024, Brin has also been showing up personally at I/O—entering product demos without a prior warning to check on audience feedback. Executives and analysts believe that Brin's urgency lies in Google's own history. In turn, the executive's return has had a major role in shifting the company's focus—and channeling its focus. 'Sergey has been back since 2023. He's been at work every day focused on AI and Gemini. Another key player is Peter Danenberg who is the godfather of Gemini. In general, the existential threat from Microsoft and Open AI galvanized the entirety of Google to focus on AI," said Ray 'R' Wang, chief executive of US-based tech consulting firm Constellation Research. Busy Pichai Brin is bringing unfazed focus to Gemini, Search and Veo, as Sundar Pichai, the CEO of Google and Alphabet, has multiple areas to focus on—lawsuits, global businesses, government relations, cloud, Android and more, the first executive cited above said. 'In the long run, Google foresees its ability to use video generation as a platform to rope in advertisers worldwide, and eventually, establish market dominance in this field," he added. Pichai, for the longest term, has been viewed as a conservative leader, steering Google's ship with 'one eye on the rear-view mirror," said an analyst who didn't want to be identified. 'For Brin, that's too safe a stance at a time when Silicon Valley is going to war with each other over AI dominance. Plus, Pichai has too much to deal with. Brin's view is that AI today needs undivided attention and he's clearly right, as Google's spate of product launches and share price movement shows," the analyst added. In the past year, the company's shares are down over 6%, compared to Microsoft's rise of nearly 10%. While there is no indication that Pichai, who will complete 10 years as the CEO of Google this August (he took over as Alphabet's chief in December 2019), is on his way out, the leadership directives seem to be clearly divided. Google did not respond to Mint's request for a comment on Brin's recent involvements. Narrowing gap? Brin's work may be showing early results. At a pre-keynote session with journalists during the developer conference, chief executive Pichai said that the Gemini developer platform currently had over seven million developers using its code to create AI applications. This is significant because as of this year, OpenAI's official statistics pegs its outreach at around three million developers. Earlier this year, at an antitrust lawsuit in a US court, Google conceded that while its developer count is higher than OpenAI's, the latter is still outpacing Google in its monthly active users count. As per filings, OpenAI's ChatGPT platform had over 600 million monthly active users, to Gemini's 350 million. Gemini's numbers, though, are a huge improvement—a year ago, ChatGPT had 400 million monthly active users, in comparison to Gemini's 9 million. Some analysts do believe that the tide is turning. 'Google is clearly in the lead for AI right now. However, search and ads and mass personalization is about to become more targeted, more actionable, and more intelligent. AI native companies will disrupt existing companies, because intelligence (in business systems) is doubling every seven months—and these AI native companies deliver on exponential efficiency," Constellation's Wang said. Phil Fersht, chief executive of New York-based tech analysis firm HFS Research, said that Google is 'sitting in an unbelievable position to win the enterprise AI war—if it can get its business model right." 'Net-net, the firm needs to be prepared to cannibalize half of its legacy search business and insert Gemini onto as many enterprises and individual users as possible. It has the resources, talent, and user base to take on OpenAI, Microsoft and Anthropic," he said. Speed wins GenAI startups such as OpenAI, Anthropic and Perplexity are known to move fast. They deploy features super quick, reach out to developers and serve a broad variety of AI use cases. Google, in contrast, is viewed to be slower, like Kolla of Convergence Catalyst hinted. Pichai, speaking with journalists a day ahead of I/O 2025, underlined a new way of working—with speed. 'Typically, we don't make announcements leading up to our big day at I/O each year, but this time it's different. Right now, we're launching products in very frequent intervals, and making technological progress at a rapid pace like never before," he said. Then, at a post-event chat, Pichai reiterated that Google is now making AI announcements to the world 'within an hour or two" of the DeepMind team showcasing the latest advancements in Gemini. 'In the end, agility and appeal to developers will play the biggest role," said Kashyap Kompella, founder of tech consultancy and research firm RPA2AI Research. 'There's no denying that its rivals are moving fast, and there are clear indications within the industry that Google's AI products are not the first choice for developers and end-users," he added. The hope is that Brin's startup-style approach, coupled with Google's inherent strength garnered over almost three decades, could be the company's trump card, says Thomas Reuner, principal analyst at UK-based tech consultancy firm PAC. 'Brin might help shore up Google's advertising business in the short term, but its biggest strategic assets are threefold: the vast data assets from the search business, data integration at scale and the unique IP of DeepMind," he said. 'Given the market noise around generative and agentic AI, these assets don't always make the headlines but provide the moat that so many startups are lacking," he added. Sitting in that satellite office in Mountain View, Brin may be hoping that this moat could firmly establish Gemini, akin to his PageRank moment 29 years ago.

Productivity puzzle: Solow's paradox has come to haunt AI adoption
Productivity puzzle: Solow's paradox has come to haunt AI adoption

Mint

time2 hours ago

  • Mint

Productivity puzzle: Solow's paradox has come to haunt AI adoption

AI enthusiasts, beware: predictions that the technology will suddenly boost productivity eerily echo those that had followed the introduction of computers to the workplace. Back then, we were told that the miraculous new machines would automate vast swathes of white-collar work, leading to a lean, digital-driven economy. Fast forward 60 years, and it's more of the same. Shortly after the debut of ChatGPT in 2022, researchers at the Massachusetts Institute of Technology claimed employees would be 40% more productive than their AI-less counterparts. These claims may prove to be no more durable than the pollyannish predictions of the Mad Men era. A rigorous study published by the National Bureau of Economic Research in May found only a 3% boost in time saved, while other studies have shown that reliance on AI for high-level cognitive work leads to less motivated, impaired employees. We are witnessing the makings of another 'productivity paradox,' the term coined to describe how productivity unexpectedly stagnated and, in some cases, declined during the first four decades of the information age. The bright side is that the lessons learned then might help us navigate our expectations in the present day. The invention of transistors, integrated circuits, memory chips and microprocessors fuelled exponential improvements in information technology from the 1960s onward, with computers reliably doubling in power roughly every two years with almost no increase in cost. It quickly became an article of faith that computers would lead to widespread automation (and structural unemployment). A single person armed with the device could handle work that previously required hundreds of employees. Over the next three decades, the service sector decisively embraced computers. Yet, the promised gains did not materialize. In fact, studies from the late 1980s revealed that the services sector—what economist Stephen Roach described as 'the most heavily endowed with high-tech capital"—registered the worst productivity performance during this same period. In response, economist Robert Solow had famously quipped that 'we see computers everywhere except in the productivity statistics." Economists advanced multiple explanations for this puzzle (also known as 'Solow's Paradox'). Least satisfying, perhaps, was the claim, still made today, that the whole thing was a mirage of mismeasurement and that the effects of massive automation somehow failed to show up in the economic data. Others have argued that the failure of infotech investments to live up to the hype can be laid at the feet of managers. There's some merit to this argument: studies of infotech adoption have shown that bosses spent indiscriminately on new equipment, all while hiring expensive workers charged with maintaining and constantly upgrading these systems. Computers, far from cutting the workforce, bloated it. More compelling still was the 'time lag' hypothesis offered by economist Paul A. David. New technological regimes, he contended, generate intense conflict, regulatory battles and struggles for market share. Along the way, older ways of doing things persist alongside the new, even as much of the world is remade to accommodate the new technology. None of this translates into immediate efficiency—in fact, quite the opposite. As evidence, he cited the advent of electricity, a quicker source of manufacturing power than the steam it would eventually replace. Nonetheless, it took 40 years for the adoption of electricity to lead to increased worker efficiency. Along the way, struggles to establish industry standards, waves of consolidation, regulatory battles and the need to redesign every single factory floor made this a messy, costly and prolonged process. The computer boom would prove to be similar. These complaints did not disappear, but by the late 1990s, the American economy finally showed a belated uptick in productivity. Some economists credited it to the widespread adoption of information technology. Better late than never, as they say. However, efficiency soon declined once again, despite (or because of) the advent of the internet and all the other innovations of that era. AI is no different. The new technology will have unintended consequences, many of which will offset or even entirely undermine its efficiency. That doesn't mean AI is useless or that corporations won't embrace it with enthusiasm. Anyone expecting an overnight increase in productivity, though, will be disappointed. ©Bloomberg The author is professor of history at the University of Georgia and co-author of 'Crisis Economics: A Crash Course in the Future of Finance'.

DOWNLOAD THE APP

Get Started Now: Download the App

Ready to dive into a world of global content with local flavor? Download Daily8 app today from your preferred app store and start exploring.
app-storeplay-store