How Measurability/Mathematical Bias Limits the Scope of Scientific Inquiry and Human Discovery

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In a fun and intriguing paper, Nobel Prize physicist Eugene Vigner explores the seemingly unreasonable effectiveness of mathematics in predicting and describing the world. While mathematics is undeniably impressive, it may not be applicable to everything, particularly in social, cognitive, and philosophical fields where constructs and relationships are harder to quantify. This presents a gap that may be difficult to bridge.

There are maps, and there are territories, and humans frequently confuse the two. No matter how insistently this point has been made by cognitive neuroscience, epistemology, economics, and a score of other disciplines, one common human error is to act as if we know what we should measure, and that what we measure is what matters. But what we value doesn’t even always have a metric. And even reasonable proxies can distort our understanding of and behavior in the world we want to navigate. Even carefully collected biometric data can occlude the other factors that determine health, or can oversimplify a nuanced conversation on the plural and contextual dimensions of health, transforming goals like functional fitness into something easier to quantify but far less useful. This philosophical conundrum magnifies when we consider governance at scales beyond those at which Homo sapiens evolved to grasp intuitively: What should we count to wisely operate a nation-state? How do we practice social science in a way that can inform new, smarter species of political economy? And how can we escape the seductive but false clarity of systems that rain information but do not enhance collective wisdom?

Welcome to COMPLEXITY, the official podcast of the Santa Fe Institute. I’m your host, Michael Garfield, and every other week we’ll bring you with us for far-ranging conversations with our worldwide network of rigorous researchers developing new frameworks to explain the deepest mysteries of the universe.

This week on the show we talk to SFI External Professor Paul Smaldino at UC Merced and University of Utah Professor of Philosophy C. Thi Nguyen. In this episode we talk about value capture and legibility, viewpoint diversity, issues that plague big governments, and expert identification problems…and map the challenges “ahead of us” as SFI continues as the hub of a five-year international research collaboration into emergent political economies. (Find links to all previous episodes in this sub-series in the notes below.)

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Mentioned & Related Links:

Transparency Is Surveillance
by C. Thi Nguyen

The Seductions of Clarity
by C. Thi Nguyen

The Natural Selection of Bad Science
by Paul Smaldino and Richard McElreath

Maintaining transient diversity is a general principle for improving collective problem solving
by Paul Smaldino, Cody Moser, Alejandro Pérez Velilla, Mikkel Werling

The Division of Cognitive Labor
by Philip Kitcher

The Unreasonable Effectiveness of Mathematics in The Natural Sciences
by Eugene Wigner