Scott Alexander challenges the idea of an 'AI race', comparing AI to other transformative technologies and discussing scenarios where the race concept might apply. Longer summary

Scott Alexander argues against the notion of an 'AI race' between countries, suggesting that most technologies, including potentially AI, are not truly races with clear winners. He compares AI to other transformative technologies like electricity, automobiles, and computers, which didn't significantly alter global power balances. The post explains that the concept of an 'AI race' mainly makes sense in two scenarios: the need to align AI before it becomes potentially destructive, or in a 'hard takeoff' scenario where AI rapidly self-improves. Scott criticizes those who simultaneously dismiss alignment concerns while emphasizing the need to 'win' the AI race. He also discusses post-singularity scenarios, arguing that many current concerns would likely become irrelevant in such a radically transformed world. Shorter summary

Scott Alexander analyzes a paper suggesting scientific progress is slowing relative to researcher numbers, arguing this trend is expected and possibly beneficial. Longer summary

Scott Alexander discusses a paper by Bloom, Jones, Reenen & Webb (2018) that suggests scientific progress is slowing down relative to the number of researchers. The paper shows that while progress in various fields (e.g., transistor density, crop yields) remains constant, the number of researchers has increased exponentially. Scott argues that this constant progress despite exponential increase in inputs should be our null hypothesis, as expecting proportional increases would lead to unrealistic outcomes. He suggests that the 'low-hanging fruit' explanation is most plausible, where early discoveries were easier to make. Scott also warns against trying to 'fix' this trend, as it could lead to dangerous consequences if scientific progress accelerated too quickly. Shorter summary