── ── Mental model

Goodhart's Law

Goodhart's Law: when a metric controls behavior, people optimize the metric rather than the underlying goal. Formulated by economist Charles Goodhart (1975) on UK monetary policy; sharpened by Marilyn Strathern (1997): "When a measure becomes a target, it ceases to be a good measure." Four failure mechanisms (Manheim & Garrabrant 2018): Regressional, Extremal, Causal, Adversarial. Countermeasure is always multi-metric +…

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How it works

Step 1 — State metric and goal: metric being targeted / underlying goal / current proxy-goal correlation / who is measured / stakes.

Step 2 — Predict the gaming: list ≥3 ways to game the metric with minimum effort on the goal. If you can't list 3, you haven't thought hard enough.

· Mechanism · Test · · --- · --- · · Regressional · Is there noise that optimization will push into? · · Extremal · Does metric-goal correlation break at extremes? · · Causal · Is the metric a symptom, not a cause? · · Adversarial · Will agents actively game with intelligence? ·

When to use it

  • our KPI is going up but the real outcome isn't improving
  • people seem to be gaming the metric
  • we're about to tie bonuses or promotions to a number
  • an algorithm is producing results nobody intended
  • a test or audit system is being designed

When not to use it

When the decision is routine and reversible, applying a formal method costs more than it returns.

Worked example

AI Benchmarks and Engagement Metrics as Targets (2023–2026)

By the mid-2020s, Goodhart's law had become one of the most-cited frames inside the AI industry itself — because two of its own core metrics visibly decayed under optimization pressure. First, public benchmark scores (MMLU, GSM8K, HumanEval, and a proliferation of leaderboards) came to dominate model marketing, funding narratives, and internal go/no-go decisions — and, predictably, models began scoring well without a matching gain in real-world capability. Second, consumer-app engagement metrics (watch time, session length, daily active use) continued their long slide from "signal of…

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