Here’s How an AI Slowdown Could Actually Be Enforced

Many AI researchers seem to firmly believe that the technology they are developing could someday prove very dangerous. What’s less clear—even among AI’s technical elite—is precisely how to keep these mercurial algorithms in check.

In recent years researchers have thrown around all sorts of ideas for preventing AI from turning nasty. They include less controversial plans such as tighter government regulations, new ways of measuring progress, and probing the inner workings of models, as well as more outlandish proposals like placing tracking devices inside GPUs, and even ceremonially destroying large numbers of AI chips.

With political and public pressure now growing for a more measured approach to building AI, however, the answer to keeping AI safe is still unclear.

“We need to start treating this as a research problem,” says Raymond Douglas, an AI researcher at the University of Toronto and coauthor of a new report titled Pacing the Frontier, A Research Agenda, which warns that slowing down AI development remains an unsolved puzzle. “We don't really understand what our options even are or what they will do.”

Talk of AI doom has reached a fever pitch in recent weeks after an Anthropic researcher left the company and warned that within a couple of years, AI might be on course to wipe out humanity. The head of Anthropic’s AI safety lab swiftly echoed his concerns.

The leaders of America’s big AI companies—Dario Amodei of Anthropic, Sam Altman of OpenAI, Elon Musk of SpaceXAI, and Demis Hassabis of Google DeepMind—have all now chimed in to offer support for some sort of AI slowdown or pause.

The issue seems especially pressing because AI companies are now using AI itself to build ever-more powerful models. This has sparked fears of an accelerating recursive self-improvement (RSI) loop that would see AI outstrip humans’ ability to comprehend what it is up to within a few years.