Escape from Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do About It
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- Type：Epub+TxT+PDF+Mobi
- Create Date：2022-12-29 03:19:44
- Update Date：2025-09-06
- Status：finish
- Author：Erica Thompson
- ISBN：B09X5BK7RK
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Summary
Why mathematical models are so often wrong， and how we can make better decisions by accepting their limits
Whether we are worried about the spread of COVID-19 or making a corporate budget， we depend on mathematical models to help us understand the world around us every day。 But models aren’t a mirror of reality。 In fact， they are fantasies， where everything works out perfectly， every time。 And relying on them too heavily can hurt us。
In Escape from Model Land， statistician Erica Thompson illuminates the hidden dangers of models。 She demonstrates how models reflect the biases， perspectives， and expectations of their creators。 Thompson shows us why understanding the limits of models is vital to using them well。 A deeper meditation on the role of mathematics， this is an essential book for helping us avoid either confusing the map with the territory or throwing away the map completely， instead pointing to more nuanced ways to Escape from Model Land。
Whether we are worried about the spread of COVID-19 or making a corporate budget， we depend on mathematical models to help us understand the world around us every day。 But models aren’t a mirror of reality。 In fact， they are fantasies， where everything works out perfectly， every time。 And relying on them too heavily can hurt us。
In Escape from Model Land， statistician Erica Thompson illuminates the hidden dangers of models。 She demonstrates how models reflect the biases， perspectives， and expectations of their creators。 Thompson shows us why understanding the limits of models is vital to using them well。 A deeper meditation on the role of mathematics， this is an essential book for helping us avoid either confusing the map with the territory or throwing away the map completely， instead pointing to more nuanced ways to Escape from Model Land。
Reviews
Tom
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A refreshingly constructivist account of scientific knowledge and communication。 This book is at its best when it is most abstract， and really nicely describes some of the most significant issues with how we think about science today。 My major complaint is that I think the practical chapters/examples were too limited。 Covid and climate change are the obvious examples that have motivated this kind of understanding （popularly） of science as it relates to life， but it was too bad that she was less A refreshingly constructivist account of scientific knowledge and communication。 This book is at its best when it is most abstract， and really nicely describes some of the most significant issues with how we think about science today。 My major complaint is that I think the practical chapters/examples were too limited。 Covid and climate change are the obvious examples that have motivated this kind of understanding （popularly） of science as it relates to life， but it was too bad that she was less well versed/did not dive into the next step to this issue: ml/algorithmic decision makers that are already massively effecting our lives based on the kinds of meta-assumptions and embedded values that she talks about with disease and climate models。 Her “pragmatic constructivist” （？） framing would absolutely be useful to think about these problems。 It was also too bad that she didn’t explicitly reference Latour， whose sociological approach to science she seemed to effectively expand beyond the laboratory to the larger political/social/scientific system （to be clear， I need to read more than a few odd articles by latour， on the list）， and Pierce， whose semiotic understanding of science （I’m like a broken record） is slightly differently flavored， but I think instructive to how to resolve some of the dialectics Thompson identified but basically just shrugged off。 。。。more
Brian Clegg
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Over the last few years a number of books， notably Sabine Hossenfelder's Lost in Math， David Orrell's Economyths， Cathy O Neil's Weapons of Math Destruction and Tim Palmer's The Primacy of Doubt， have pointed out problems with the mathematical modelling done by businesses， physicists， meteorologists， epidemiologists， economists and more。 These are not anti-science polemics， but rather people who know what they're talking about pointing out the dangers of getting too carried away with elegant mat Over the last few years a number of books， notably Sabine Hossenfelder's Lost in Math， David Orrell's Economyths， Cathy O Neil's Weapons of Math Destruction and Tim Palmer's The Primacy of Doubt， have pointed out problems with the mathematical modelling done by businesses， physicists， meteorologists， epidemiologists， economists and more。 These are not anti-science polemics， but rather people who know what they're talking about pointing out the dangers of getting too carried away with elegant mathematics and models， often assuming that the models effectively are reality （and certainly presenting them that way in some of the writing and press releases from the scientists building and using the models）。Erica Thompson takes on the problems of mentally inhabiting the mathematical world she describes as 'model land'。 As she cogently points out， it's fine to play in model land all that you like - the problem comes with the way that you exit model land and tie back to the real world。 This book is loaded with examples from climate forecasts， economics， pandemic forecasting and more where the modellers have been unable to successfully get out of model land and present their information usefully to those who have to make decisions （or the public）。 This is not an attempt to get rid of models。 Thompson's key argument is that while models will pretty well always be wrong they can still be very useful - and an understanding of uncertainty/risk combined with expert interpretation is the best （if sometimes narrow） bridge to link model land to the real world。Unfortunately， unlike the books mentioned above， Thompson's doesn't read particularly well - the writing is very dry。 It's also arguable that having set us up to ask questions about scientific output and models， we don't get the same degree of analysis applied to Thompson's personal ideas。 So， for example， she tells us 'Diversity in boardrooms is shown to result in better decision making'。 I don't doubt this， or the parallel she is drawing for needing diversity of models - but how was success of decision making measured， and what does diversity mean in this context？ In fact diversity is something of a running theme， with Thompson several times referring to model makers as largely WEIRD （apparently standing for Western， Educated， Industrial， Rich， Developed） - the acronym seems an unnecessarily ad hominem jibe - and is it really possible to develop mathematical models without being educated？There are a few oddities and omissions。 One of Palmer's big points in The Primacy of Doubt is the oddity that economics hasn't taken up ensemble forecasting - something that isn't mentioned here。 The way （mathematical） chaos is presented is also a little odd - it's mostly referred to as 'the butterfly effect'， which is really only a specific example of a potential （though relatively unlikely） impact of a chaotic system。 Thompson also calls chaotic systems complex， yet they can be surprisingly simple。 It's also unfortunate when describing the limitations of vaccine modelling there is no mention of a point emphasised in the scientific journal Nature: the way surface transmission and cleaning continued to be pushed many months after there was clear evidence that transmission was primarily airborne。 Thompson's enthusiasm for diversity has one notable exception that throws into doubt her concept that the best way to use models is to have more intuitive human input from academics to interpret and modify the results。 She has an impressive list of diversity requirements - age， social class， background， gender and race for those academics。 But she omits the diversity elephant in the room， which is political leanings。 When the vast majority of academics are politically left wing， surely this too needs to be taken into account。Overall， some interesting points， but a dry academic writing style combined with some limitations means that it has less impact than the books mentioned above。 。。。more
Jeff
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