Oxford computer scientist and artificial intelligence researcher Michael Wooldridge says the rapid expansion of artificial intelligence is being shaped less by scientific inevitability than by competitive pressures among a small group of technology companies racing to avoid falling behind rivals.

In an interview discussing his latest book, Life Lessons from Game Theory: The Art of Thinking Strategically in a Complex World, Wooldridge argued that many of the current tensions surrounding artificial intelligence can be understood through the framework of game theory, particularly scenarios in which competitors continue escalating despite recognizing collective risks.

Wooldridge, a professor at the University of Oxford and one of Britain’s most prominent public communicators on artificial intelligence, said the industry increasingly resembles a strategic trap in which companies continue investing heavily in advanced systems because they believe competitors would gain advantage if they slowed development.

“We’ve got a small number of very wealthy companies that are busy pursuing AI, while at the same time saying that they are afraid that something’s going to go horribly wrong with it,” Wooldridge said. “So why are they busy pursuing it? Because they think if we back down and we don’t pursue it, somebody else will.

”The comments come amid intensifying global competition over artificial intelligence infrastructure, computing capacity and access to data. Major technology firms including OpenAI and Google DeepMind have expanded investments in large-scale machine learning systems, while governments in the United States, Europe and China are increasingly treating AI as a strategic industry tied to economic growth and national security.

Wooldridge said many of the core technologies underpinning today’s AI systems are not recent discoveries. He noted that key neural network techniques central to modern machine learning were developed by the mid-1980s, but computing power and data limitations prevented their wider deployment at the time.

“The only obstacle standing in the way of the AI revolution in the 1980s, really, was that computers weren’t powerful enough and we didn’t have enough data,” he said.He described the emergence of GPT-3 in 2020 as a turning point driven largely by scale rather than a fundamentally new scientific breakthrough.

According to Wooldridge, many researchers initially doubted whether simply expanding computational power and training data would substantially improve performance. He said the success of that approach surprised a significant portion of the research community.

OpenAI’s development strategy demonstrated that scaling existing methods could generate major commercial results, he said, although he cautioned against interpreting those advances as evidence that artificial general intelligence, or AGI, is imminent.Executives including Sam Altman and Demis Hassabis have publicly discussed the possibility of achieving human-level general intelligence within years. Wooldridge said those forecasts remain overly optimistic.

He argued that current systems still struggle with tasks requiring physical reasoning and adaptation in unfamiliar environments. While advanced chat systems can process complex linguistic queries, he said they remain unable to reliably perform many basic real-world activities that humans execute routinely.

“You can talk to ChatGPT about quantum mechanics in Latin,” Wooldridge said, “but at the same time, we don’t have AI that could come into your house, that it had never seen before, locate the kitchen and clear the dinner table.”Wooldridge said data availability may become one of the industry’s most significant constraints.

He noted that large language models already consume enormous quantities of text and digital material, creating pressure to secure new sources of information for future training cycles.“The whole of Wikipedia made up just 3% of GPT-3’s training data,” he said. “Where do you get 10 times more data from next time around?”That search for data, he argued, could reshape relationships between governments, corporations and individuals.

Wooldridge pointed to healthcare systems, wearable devices and online content creators as examples of potentially valuable data sources for future AI development.“The NHS is sitting on a huge amount of data about human beings,” he said. “That’s the most valuable kind of data imaginable.”He warned that commercial pressure to obtain increasingly detailed behavioral information could create incentives for broader surveillance and monitoring.

Wooldridge suggested future generations of online influencers may routinely agree to extensive data collection arrangements in exchange for visibility and commercial opportunity.The professor’s latest work focuses primarily on game theory, which he defines as the study of interactions between self-interested actors.

He said many geopolitical disputes, commercial rivalries and social conflicts can be interpreted through a relatively small number of strategic models.One recurring example in his analysis is the “game of chicken,” in which opposing sides continue escalating until one party backs down or both suffer severe consequences.

Wooldridge compared the framework to current tensions involving the United States and Iran, describing unpredictability as a recognized strategic tactic within game theory.“You’ve got two sides with ever-escalating threats against each other,” he said. “Somebody’s got to back down at some point.

”Wooldridge added that highly unpredictable behavior can complicate strategic decision-making because opponents struggle to assess likely responses and risks. Under such conditions, he said, game theory often encourages actors to prepare for worst-case outcomes.He also criticized what he described as a growing “zero-sum” political mindset in parts of modern public discourse.

In game theory, he said, zero-sum situations are not merely competitions where one side wins and another loses, but systems where actors are incentivized to maximize damage to opponents.“This zero-sum mentality is very damaging,” Wooldridge said.

“One of the important lessons from game theory is that, actually, the majority of interactions that we’re in are not zero-sum.”He linked that framework to populist political narratives that portray economic or social gains by one group as direct losses for another. As an alternative, Wooldridge highlighted the “Veil of Ignorance,” a philosophical model developed by political philosopher John Rawls in 1971.

The thought experiment asks individuals to design a society without knowing which position they themselves would ultimately occupy within it.Wooldridge said the model creates incentives for fairer social systems because participants must account for the possibility of ending up disadvantaged. He noted that former U.S. presidents Bill Clinton and Barack Obama had both expressed interest in Rawls’ ideas.

Despite concerns surrounding AI development, Wooldridge said he remains optimistic about technology and scientific inquiry. Growing up in rural Herefordshire, he taught himself programming after repeatedly visiting a local electronics shop that displayed a TRS-80 computer in its storefront during the early 1980s.

He later completed a doctorate in artificial intelligence and went on to publish more than 500 scientific papers and multiple books, while also presenting public lectures on the social implications of AI.

Asked whether students should avoid fields vulnerable to automation, Wooldridge rejected the idea that education should be driven solely by labor market forecasts.

“I didn’t get into computing because I thought it was going to give me a good job,” he said. “I got into it because I was just really interested in it.”

Musk, a co-founder of OpenAI, is suing the company, Chief Executive Sam Altman, President Greg Brockman and major investor Microsoft, alleging they abandoned OpenAI’s original mission of developing artificial intelligence for the benefit of humanity and instead turned it into a commercial enterprise focused on profit.

“If we make it okay to loot a charity, the entire foundation of charitable giving in America will be destroyed,” Musk told the court on the first day of trial. “That’s my concern.”Musk is seeking $150 billion in damages from OpenAI and Microsoft, with the proceeds directed to OpenAI’s charitable arm. He is also asking the court to require OpenAI to return to nonprofit control and to remove Altman and Brockman from leadership roles, while seeking Altman’s removal from the board.

The lawsuit includes claims of breach of charitable trust and unjust enrichment and could have significant implications for OpenAI’s governance as the company explores a potential initial public offering that Reuters has previously reported could value it near $1 trillion.

OpenAI lawyer Bill Savitt told jurors during opening arguments that Musk had originally supported the idea of turning OpenAI into a for-profit structure and only sued after failing to gain control of the company and later launching his own rival artificial intelligence venture, xAI.Savitt said Musk wanted “the keys to the kingdom” and pursued litigation only after OpenAI rejected his ambitions to lead the company.

“What he cares about is Elon Musk being on top,” Savitt said. “We are here because Mr Musk didn’t get his way.”OpenAI’s legal team argued that its decision in March 2019 to establish a for-profit entity was necessary to secure the computing resources and talent needed to compete with rivals such as Google’s DeepMind artificial intelligence division.

Musk’s lawyer Steven Molo rejected that argument, saying OpenAI’s leadership shifted focus once major investors, including Microsoft, entered the picture.“It wasn’t a vehicle for people to get rich,” Molo said.Before jurors entered the courtroom, U.S. District Judge Yvonne Gonzalez Rogers warned Musk over his social media activity after OpenAI lawyers raised concerns about his posts on X, where he referred to Altman as “Scam Altman” and accused him of stealing a charity.

Rogers said she was reluctant to impose a gag order but urged Musk to avoid using social media to influence matters outside the courtroom.Musk agreed to reduce his online commentary, as did Altman. Both are expected to testify, along with Microsoft Chief Executive Satya Nadella.

The trial is expected to provide a rare public examination of OpenAI’s evolution from a nonprofit founded in 2015 in Brockman’s apartment into one of the world’s most valuable artificial intelligence companies, currently estimated to be worth more than $850 billion.

Musk testified that his concerns about artificial intelligence safety were central to OpenAI’s founding and intensified after discussions with former U.S. President Barack Obama and with Larry Page, whom he said did not take the risks of advanced AI seriously enough.“We had to have a counterpoint against Google,” Musk said.

OpenAI disputed that characterization, with Savitt telling jurors that Musk had dismissed employees focused on AI safety and that such concerns were not his primary motivation.

Musk has said he contributed about $38 million to OpenAI before leaving its board, later objecting to its restructuring and Microsoft’s multibillion-dollar investment.

Microsoft lawyer Russell Cohen said the company had acted properly throughout its partnership with OpenAI and described it as “a responsible partner every step of the way.”

Chinese startups are setting up operations in Singapore to reassure global clients that their intellectual property is insulated from Beijing’s oversight, while U.S. firms are drawn by easier access to international talent amid tightening visa rules at home, industry executives and analysts said.

Kerry Goh, chief executive of Kamet Capital, said relocating operations to Singapore provides “comfort” to international clients by ensuring data and intellectual property are governed locally. He cited support for a new AI video venture launched by former executives of Alibaba as an example of this shift.

The trend reflects broader fallout from intensifying Sino-U.S. competition over advanced technologies, including export controls and talent mobility restrictions. Policies under U.S. President Donald Trump, particularly changes to H-1B visa rules, have made it harder for companies to deploy global workforces in the United States.

Singapore has responded with incentives aimed at building an AI-focused economy, including fast-track visas for skilled workers and tax benefits for intellectual property registration. Officials say these measures have strengthened the country’s appeal as a technology hub.

Major global firms are expanding their presence. AI developer Anthropic is planning a Singapore office, according to people familiar with the matter, joining companies such as OpenAI, Meta’s Superintelligence Labs, and Google’s DeepMind.

At the same time, the shift has raised concerns among policymakers. Washington has tightened restrictions on advanced chip exports, including limits on sales by Nvidia to China, while Beijing has reportedly imposed constraints on talent mobility for some AI firms expanding overseas.

Analysts warn Singapore’s growing role as a “neutral” jurisdiction could draw scrutiny from both sides. Chong Ja Ian, a political scientist at the National University of Singapore, said the city-state risks being viewed as a grey zone for technology transfers, potentially prompting regulatory pushback.

Despite such risks, companies continue to be attracted by Singapore’s streamlined visa processes, with some employment passes approved within days, and its reputation as a stable, business-friendly environment.