Thesis ID: CBB774678693

Progressibility: Why Can Some Technologies Improve More Rapidly Than Others? (2023)


Over the last few hundred years, best practice in some fields of human action—e.g., the treatment of heart disease, the transportation of persons, goods, and messages, and the destruction of landscapes, structures, and lives—has become dramatically more effective. At the same time, best practice in other fields, e.g., the amelioration of poverty or the teaching of reading, writing, or math, has improved more slowly, if at all. I argue that practice and technology (“know-how”) can only improve rapidly under rather special conditions: that, at any given point in time, some fields are more “progressible” than others. I articulate a conceptual framework describing several characteristics of practice in a field that may facilitate rapid progress. These characteristics, while not fixed, tend to remain fairly stable for long periods of time. I argue that know-how can improve more quickly 1) when offline “vicarious trial” of variations in practice is feasible and useful; 2) when practice is formal and standardized; 3) when practice is substantially performed by artifacts rather than by humans; 4) when outcomes of variations in practice may be rapidly evaluated; 5) when goals of practice are consistently agreed upon; 6) when contexts and objects of practice may be treated as, or have been made, consistent for the purposes of intervention; 7) when components of task systems are not heavily interdependent; and 8) when labor is finely and sharply divided. I illustrate and elaborate this framework through comparative case studies on efforts to improve practice in three differentially “progressible” fields. I examine rapid improvement in a COVID-19 testing lab, inconsistent improvement in undergraduate algebra instruction, and ambiguous improvement in regional water modeling to support municipal water management. These cases indicate that my theory may inform judgments about the plausibility of rapid advance within a field of practice, absent disruptive change in methods or problem formulation. My theory may also shed light on which varieties of innovative effort may and may not foreseeably contribute to improving practice in a given field—more formal, theoretical, and context-independent work in high-progressibility domains, more tacit, grounded, and localized work in low-progressibility ones.

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Authors & Contributors
Achterhuis, Hans
Bai, Ye-xin
Baldeweg, Juan Navarro
Bleecker, Julian C.
Böhme, Gernot
Buchanan, Bruce
European Legacy
History of the Human Sciences
Humanities and Technology Review
Journal of Dialectics of Nature
Research in Philosophy and Technology
Spontaneous Generations
Lexington Books
University of Minnesota Press
University of California, Santa Cruz
Alvar Aalto Foundation
Fordham University Press
Philosophy of technology
Philosophy of science
Computers and computing
Heidegger, Martin
Ihde, Aaron John
Bacon, Francis, 1st Baron Verulam
Bakhtin, Mikhail Ivanovich
Besson, Jacques
Horkheimer, Max
Time Periods
20th century
20th century, late
16th century
20th century, early
21st century
Soviet Union
New Guinea
Los Alamos Scientific Laboratory

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