Executive summary: Analogies can be useful for explaining AI safety concepts, but they should be chosen carefully to avoid misrepresenting key ideas or distracting from the main arguments.
Key points:
Analogies highlight certain aspects of a concept while obscuring others, so analogies for AI safety should minimize lost nuance.
Simple comparisons stating two things share some property often add little, but arguments drawing unintuitive conclusions via analogy can be insightful.
Analogies serve purposes like providing evidence, aiding intuition, saving time, and consistency checking.
Common attacks on analogies question if the base conceptimplies the conclusion, if the analogues are sufficiently similar, or the conclusion itself.
Entrenched analogies can mislead policymakers, so new analogies should be scrutinized, especially if expressing AI safety skepticism.
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Executive summary: Analogies can be useful for explaining AI safety concepts, but they should be chosen carefully to avoid misrepresenting key ideas or distracting from the main arguments.
Key points:
Analogies highlight certain aspects of a concept while obscuring others, so analogies for AI safety should minimize lost nuance.
Simple comparisons stating two things share some property often add little, but arguments drawing unintuitive conclusions via analogy can be insightful.
Analogies serve purposes like providing evidence, aiding intuition, saving time, and consistency checking.
Common attacks on analogies question if the base conceptimplies the conclusion, if the analogues are sufficiently similar, or the conclusion itself.
Entrenched analogies can mislead policymakers, so new analogies should be scrutinized, especially if expressing AI safety skepticism.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, and contact us if you have feedback.