Verified65% confidenceFactExact time
Goodhart's Law states that when a metric becomes a target in itself it is no longer a good metric, and introducing test sets into training data causes a model's exam scores to decouple from its true capabilities
3
Sources
65%
Confidence
Long-term
Relevance
7/19/2026
First Seen
Sources
GPT-5.6发布即预警:算力瓶颈才是大模型真正的考验
Related Claims
Verified跑分榜单衡量的是模型考试能力而非解决真实问题的能力81% similarUnverifiedGoodhart's Law states that when a quality metric becomes an optimization target, it is no longer a good measure of quality, as the model may learn to game the score rather than genuinely improve.79% similarVerified古德哈特定律描述:当一个度量指标变成目标时,它就不再是好的度量指标了79% similarUnverifiedBenchmark tests have limitations, and high scores do not necessarily equate to real-world application capability.78% similarUnverifiedThe Goodhart's Law effect refers to the phenomenon where, when a metric becomes a target, it ceases to be a good metric, potentially causing models to learn to manipulate the evaluation system rather than genuinely understanding human intent.78% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/560014API
curl https://kongchang.com/api/v1/knowledge/claims/560014MCP
get_claim(id=560014)