“Adoption of Singular ‘Gold Standard’ Models” Closes “Off Other Important Avenues of Inquiry”

(p. A15) Ubiquitous and persuasive, models . . . drive decisions—one reason why, in Ms. Thompson’s view, they require our urgent attention. She tells us that, as a graduate student studying North Atlantic storms, she noticed how different models predicted different overall effects and produced contradictory results.

. . .

The problem is that Model Land is easy to enter but difficult to escape. Having built “a beautiful internally consistent model,” Ms. Thompson writes, it can be “emotionally difficult to acknowledge that the initial assumptions on which the whole thing is built are literally not true.”

There are all sorts of ways that models can lead us astray. A small measurement error on an input can lead to wildly inaccurate forecasts—a phenomenon known as the Butterfly Effect. Fortunately, this type of uncertainty is often manageable. Far more problematic are what Ms. Thompson calls “unquantifiable unknowns”—things that are left out of a model’s calculation because they can’t be anticipated, such as the unexpected arrival of a transformative technology or the abrupt collapse of a robust market. It is not always true, she observes, that the data we have now will be relevant to the future—as traders discovered in the stock-market crash of 1987, when their models catastrophically failed.

. . .  We may be inclined to regard models as objective expressions of truth, yet they are deliberately constructed interpretations, imbued with the values and viewpoints of the modelers—primarily, as Ms. Thompson notes, well-educated, middle-class individuals. During the pandemic, models “took more account of harms to some groups of people than others,” resulting in a “moral case” for lockdowns that was “partial and biased.” Modelers who worked from home—while others maintained the supply chain—often overlooked “all of the possible harms” of the actions their models were suggesting.  . . .

The promise and peril of models, Ms. Thompson recognizes, has deep resonance in biomedicine, where so-called model organisms, like yeast and zebrafish, have led to foundational insights and accelerated the development of therapeutics. At the same time, treatments that work brilliantly in Model Land often fail in people, devastating patients and disappointing drug developers. The search for improved disease models can be complicated when proponents of one model suppress research into alternative approaches, as the late journalist Sharon Begley documented in a powerful 2019 report. Ms. Thompson perceptively critiques the adoption of singular “gold standard” models, noting that the “solidification” of one set of assumptions can lock us into one way of thinking and close off other important avenues of inquiry.

For the full review see:

David A. Shaywitz. “BOOKSHELF; Seduced By Numbers.” The Wall Street Journal (Wednesday, Dec. 28, 2022): A15.

(Note: ellipses added.)

(Note: the online version of the review has the date December 27, 2022, and has the title “BOOKSHELF; ‘Escape From Model Land’ Review: Seduced by Numbers.”)

The book under review is:

Thompson, Erica. Escape from Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do About It. New York: Basic Books, 2022.

Sharon Begley’s “powerful” 2019 report, mentioned above, is:

Begley, Sharon. “The Maddening Saga of How an Alzheimer’s ‘Cabal’ Thwarted Progress toward a Cure for Decades.” STAT; Reporting from the Frontiers of Health and Medicine, Posted June 25, 2019. Available from https://www.statnews.com/2019/06/25/alzheimers-cabal-thwarted-progress-toward-cure/.

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