Tech giants, stop trying to build godlike AI

WE have ChatGPT because Sam Altman wanted to build a god.

For all the buzz, the chatbot is only a prototype along the way to a loftier goal of AGI, or “artificial general intelligence” that surpasses the cognitive abilities of humans. When Altman co-founded OpenAI in 2015, the non-profit’s goal. Five years earlier, Demis Hassabis co-founded DeepMind Technologies Ltd., now Google’s core AI division, with the same AGI objective. Their reasons were utopian: AGI would create financial abundance and be “” to humanity, according to Altman. It would , according to Hassabis.

There are problems with these noble goals. First, the financial incentives of large tech firms are likely to skew AGI efforts towards benefiting their coffers first and foremost. Those early altruistic objectives of Altman and Hassabis have fallen by the wayside in the last few years as the generative AI boom has sparked a race to “win,” whatever that means. In the last few years, DeepMind’s website has removed content on health research or discovering new forms of energy creation to become more product-focused, spotlighting Google’s flagship AI platform Gemini. Altman still talks about benefiting humanity, but he’s no longer a non-profit “” per his 2015 founding statement, and more of a product arm of Microsoft Corp., which has since sunk roughly $13 billion into his company. 

The other issue is that even the people who are building AGI are fumbling in the dark, despite how sure they are of their timeline predictions. Anthropic CEO Dario Amodei has said . Altman has said it’s “” away and we’ll have the first AI agents joining the workforce this year. Billionaire Masayoshi Son thinks we’ll have it in two or three years. Ezra Klein, a New York Times podcaster who regularly has AI leaders on his show, recently , “It’s really about to happen. We’re about to get to artificial general intelligence.”

But ask the tech leaders what AGI actually means and you’ll get a smorgasbord of answers. Hassabis describes it as software that can perform “at human level.” Altman says it will “outperform humans.” Both, alongside Amodei, often take greater pains to talk about the complexity and challenges of defining AGI. Altman has also a “weakly defined term.” And Microsoft Chief Executive Officer Satya Nadella has even as “nonsensical benchmark hacking.”

I get little comfort from seeing AI’s top leaders trash talking or dancing around the definition of their North Star, while simultaneously racing toward it. Not just because computer-science experts, along with Elon Musk, worry that the advent of AGI will also come with rather high stakes, existential risks to human civilization. But because tilting at a vaguely defined goal opens the door to unintended consequences.

A more worthwhile aspiration would be narrower and more concrete, such as building AI systems that reduce medical diagnostic errors by 30%. Or in education, improving math proficiency in students by 15%. Or systems that could enhance energy grids to reduce carbon emissions by 20%. Such goals not only have clear metrics for success but serve concrete human needs, just as AI builders like Altman and Hassabis originally envisioned.

There is no evidence that when a company like Google or Microsoft (or China’s DeepSeek) claim to have finally built AGI, they will have the key to curing cancer, solving climate change, or increasing the wealth of everyone on earth by “trillions” of dollars, . So intense has the arms race become that it seems more likely they will instead position themselves as having a competitive advantage in the market, raise prices, and lock down information sharing. There will be questions about geopolitical ramifications. When he founded OpenAI, Altman said that if his team ever noticed another research lab was getting closer to AGI, they would down tools and collaborate. That looks like a pipe dream today.

Last month a large group of academic and corporate AI researchers that called on tech firms to stop making AGI the be-all and end-all of AI research. They argued that not only was the term too vague to measure properly, creating a recipe for bad science, it left key people out of the conversation — namely, all those whose lives would be changed. Technologists in 2025 have far more societal power than they did at the turn of the millennium, able to reshape culture and individual habits with the social media products they’ve deployed, and now large swathes of jobs too with AI, with few checks and balances.

The researchers, including Google’s former AI ethics lead Margaret Mitchell, suggest not only that tech firms include more voices from different communities and fields of expertise in their AI work, but that they drop the vague shtick about AGI, which one scientist memorably defined for me as “the rapture for nerds.”

The obsession with “bigger is better” has gone on long enough in Silicon Valley, as has the jostling between people like Musk and Altman to have the biggest AI model or the biggest cluster of Nvidia Corp.’s AI chips. J. Robert Oppenheimer had much regret for his role as the father of the atomic bomb, and now epitomizes the notion that “just because you can, doesn’t mean you should.”

Rather than look back in hindsight with remorse, tech leaders would do well to avoid the same trap of gunning for glory and trying to build gods, especially when the benefits are far from certain.

BLOOMBERG OPINION