Four faculty members at the University of California San Diego have concluded that artificial general intelligence (AGI) has already arrived, according to a recently published comment in Nature. The group includes Associate Professor of Philosophy Eddy Keming Chen, Professor of Artificial Intelligence, Data Science and Computer Science Mikhail Belkin, Associate Professor of Linguistics and Computer Science Leon Bergen, and Professor of Data Science, Philosophy and Policy David Danks.
The researchers approached the question from several perspectives—philosophy, machine learning, linguistics, and cognitive science—and argued that current large language models (LLMs) meet reasonable standards for AGI. Their argument focused on three questions: defining general intelligence, understanding why their conclusion is controversial, and considering its implications for humanity.
Their discussions took place as UC San Diego researchers found in March 2025 that GPT-4.5 was identified as human 73% of the time in a Turing test—more often than actual humans.
Chen explained that perfection is not required for general intelligence: “There is a common misconception that AGI must be perfect — knowing everything, solving every problem — but no individual human can do that. The debate often conflates general intelligence with superintelligence. The real question is whether LLMs display the flexible, general competence characteristic of human thought. Our conclusion: insofar as individual humans possess general intelligence, current LLMs do too.”
The authors argue that universal mastery or perfection are unrealistic requirements for AGI; instead they focus on breadth (abilities across multiple domains such as mathematics and language) and depth (strong performance within those domains). They assessed evidence through levels similar to how humans evaluate each other’s intelligence: basic conversation skills (Turing-test level), expert-level performance in various fields (expert tier), and revolutionary scientific breakthroughs (superhuman tier). According to the team, frontier LLMs already achieve the first two levels.
Objections regarding errors made by LLMs were addressed by comparing them to human fallibility. The authors state that making mistakes does not disqualify either humans or machines from being considered generally intelligent.
Another point raised relates to embodiment—the idea that lacking a body limits machine intelligence—but examples like physicist Stephen Hawking challenge this view since his physical limitations did not affect his intellectual contributions.
Belkin commented on the emotional reactions provoked by these ideas: “This is an emotionally charged topic because it challenges human exceptionalism and our standing as being uniquely intelligent,” he said. “Copernicus displaced humans from the center of the universe, Darwin displaced humans from a privileged place in nature; now we are contending with the prospect that there are more kinds of minds than we had previously entertained.”
Concerns about social consequences make some people reluctant to accept AGI’s existence. Chen, Belkin, Bergen and Danks suggest approaching these emotions with curiosity rather than avoidance.
The essay also discusses economic pressures influencing perceptions about AI capabilities—such as demands for reliability or instant learning—which may distort assessments about AGI’s arrival. Industry expectations often exceed what is required from individual humans.
Bergen highlighted uncertainties around how LLMs learn: “We have built highly capable systems, but we do not understand why we were successful,” he said. “LLMs learned about the world through processes unlike human learning, and we lack a detailed account of how their abilities emerged. This gap in understanding grows more important as the systems grow more capable.”
Danks emphasized ethical concerns arising from increasingly autonomous AI systems: “We’re developing AI systems that can dramatically impact the world without being mediated through a human and this raises a host of challenging ethical, societal and psychological questions,” he explained. “AI is a future that we are building right now. Ultimately, we’re innovating because we want something better, and the very idea of better should have ethics and safety baked in.”
The four scholars’ collaboration represents UC San Diego’s emphasis on interdisciplinary research across humanities, social sciences and data science.
Learn more about research at UC San Diego related to artificial intelligence at https://ucsd.edu/research/artificial-intelligence.html
