The post says AI safety workers often pick projects by feeling.
This may not beat what else they could do.
The field needs people who deeply understand the core arguments.
What happened
A post on LessWrong argues that AI safety researchers, including the authors, often choose projects based on intuition rather than a deep understanding of the problems, potentially leading to less impactful work than a plausible alternative.
Why it matters
The field is described as talent-constrained, but the bottleneck is not just adding more people; it needs people who truly grasp the core arguments of AI safety to make meaningful contributions.
What to watch
The post calls for a shift toward deliberately understanding and thinking hard about the problems before selecting work, which could change how the community prioritizes efforts.
Ask the AI about this article →
The post reflects a self-critical trend within the AI safety community, where practitioners worry that their efforts might be misdirected. It contrasts 'running a conference' and 'doing pragmatic alignment research' as potentially good, but notes that such choices are often made without rigorous analysis of their true impact. This introspection suggests a push toward more deliberate problem selection, which could influence how individuals and organizations allocate their time and resources in the field.
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