Where AGI timelines go wrong | Toby Ord, Oxford University

Both Silicon Valley and the public can’t get enough of ‘AGI timelines.’ But Toby Ord, senior researcher at Oxford’s AI Governance Initiative and author of _The Precipice,_ believes we consistently make big mistakes when thinking about them. He lays out the 14 ways he most often sees people go wrong: 1. Assuming AI research is just hill-climbing 2. Imagining AI research is just programming 3. Forecasting “could” instead of “will” 4. Believing the current benchmark is the last one 5. Extrapolating trends with no clear finish line 6. Assuming inputs keep scaling at the same rate 7. Conflating in