# How to actually slow down AI development > Researchers are mapping out concrete ways governments and companies could pump the brakes on dangerous AI progress. - Title: How to actually slow down AI development · WIRED | Shortify - Summary: Researchers are mapping out concrete ways governments and companies could pump the brakes on dangerous AI progress. Slowing AI requires independent… - Keywords: ai safety, ai regulation, ai slowdown, anthropic, openai, google deepmind, recursive self-improvement, gpu tracking, ai oversight, ai governance, compute limits, ai evaluations - Source: WIRED — https://wired.com/story/heres-how-an-ai-slowdown-could-actually-work - Author: Will Knight - Published: 2026-09-18T19:21:09.865+00:00 - Read time: 2 min - Topics: ai safety, ai regulation, ai slowdown, anthropic, openai, google deepmind, recursive self-improvement, gpu tracking, ai oversight, ai governance, compute limits, ai evaluations ## AI researchers fear their creation Many AI researchers believe the technology they're developing could become very dangerous, but there's no clear consensus on how to control it. ## A growing list of control ideas Proposals range from tighter government regulations and new progress metrics to more extreme measures like placing tracking devices in GPUs or destroying AI chips. ## Slowing AI is unsolved A new report from University of Toronto researcher Raymond Douglas warns that slowing down AI development remains an unsolved puzzle with unclear options. > We need to start treating this as a research problem. ## AI doom fears intensify An Anthropic researcher recently warned that AI could wipe out humanity within a couple of years, prompting leaders at major AI companies to support some form of slowdown. ## The recursive loop problem AI companies are now using AI to build more powerful models, creating fears of a recursive self-improvement loop that could outpace human understanding within years. ## Anthropic tracks its own progress Anthropic announced new tracking methods showing Claude now does 26 percent of their AI research and they spend 6 percent of compute budget on AI safety. ## Independent evaluators could help Third-party evaluators could test AI models and try to trigger misbehavior, though critics argue current inspections lack rigor and true independence. > When [big AI companies] say 'independent evaluators,' they mean 'I want to pay my friends who live in my group houses to look at my prompts.' ## Track compute, not just capability Experts propose monitoring GPU usage, power consumption, and billing records at data centers to detect when companies train models beyond safe thresholds. ## Modify chips for oversight Researchers suggest adding cryptographic components to GPUs that record compute runs, or even building remote kill switches that require authorization to run certain models. ## International treaties are essential Controlling AI requires global cooperation since China and other nations can also build frontier AI. One proposal suggests mutual hardware reduction via treaty. ## The nuclear option Some philosophers have proposed that if nations agree the risk is grave enough, they could bring GPUs to neutral territory and destroy them together. ## Measuring AI's self-improvement A new benchmark called the RSI Index tracks AI-powered AI development. It suggests AI could perform research work that human researchers cannot follow within a year. ## Bad controls could backfire Rushing to implement poorly designed controls risks political gridlock or regulatory capture. Experts warn that a flawed plan could be worse than no plan at all. > Going off half-cocked with a bad plan could end up worse than nothing. ## Key takeaway Slowing AI requires independent oversight, compute tracking, and international treaties, but no single solution exists yet.