The Streetlight Effect Distorts What We Know
People search for information where it is easiest to look, not where it is most likely to be found. This systematically distorts what we collectively "know," because the map of available knowledge reflects the map of measurement convenience rather than the map of reality.
"A policeman sees a drunk man searching for something under a streetlight and asks what he has lost. He says he lost his keys and they both look under the streetlight together. After a few minutes the policeman asks if he is sure he lost them here, and the drunk replies, no, that he lost them in the park. The policeman asks why he is searching here, and the drunk replies, 'this is where the light is.'" — parable commonly attributed to Nasreddin
The streetlight effect is not merely an individual bias — it is a structural feature of knowledge production. Entire academic fields can be distorted by it. Economics overweights what can be quantified (GDP, employment) and underweights what cannot (social cohesion, institutional health, tacit knowledge). Medicine overstudies diseases with clear biomarkers and understudies conditions that are hard to measure. Data science gravitates toward problems with available datasets rather than the most important problems.
This connects directly to legibility: the state sees what it can measure, and what it can measure shapes what it tries to manage. The streetlight effect explains why legibility is so seductive — it's not that administrators are stupid, it's that measurable proxies are right there while the underlying reality is dark and expensive to illuminate. Goodhart's Law is the downstream consequence: once you optimize for what's under the streetlight, the thing in the dark gets worse.
Syntopical reading is one antidote. By reading across multiple sources on the same question, you are deliberately searching beyond the streetlight of any single author's methodology or dataset. The scholar who reads only within their discipline is confined to disciplinary streetlights.
Takeaway: When you notice that everyone is looking at the same data, using the same metrics, or studying the same questions, ask what is being systematically ignored because it is hard to see — that is where the important answers usually live.
See also: Legibility Kills What It Tries to Measure | Goodhart's Law Corrupts Every Metric | Monitor What Matters Not What Is Easy | Epistemic Legibility — Not Everything Can Be Made Explicit | Syntopical Reading Is How You Build Understanding