Yves here. Hoo boy, if any future civilizations deign to study our attempt at one, this sort of thing, an exercise in radical subjectivism. would likely be seen as degenerate or deranged. This school of thought dignifies cargo cults and la la land.
By Peter Dorman, professor of economics at The Evergreen State College. Originally published at Econospeak
Let’s get the up-or-down part of this review over with quickly: Escape from Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do About It by Erica Thompson is a poorly written, mostly vacuous rumination on mathematical modeling, and you would do well to ignore it.
Now that that’s done, we can get on with the interesting aspect of this book, its adaptation of trendy radical subjectivism for the world of modeling and empirical analysis. The framework I’m referring to goes something like this: Each of us exists in our own bubble, a product of our experiences and perspectives. Our thoughts express this subjective world, and they are true in relation to it but false beyond its boundaries. This means no one has the right to speak for nor criticize anyone else. In some versions, bubbles can be shared among people with the same set of identities, but, as before, not across them. In some unspecified way, we will be happy and productive if we embrace the diversity of our incommensurable worlds and their corresponding truths. Oppression occurs when some privileged people think their bubbles are universal, the doctrine of false objectivity. We must be re-educated out of such a delusion.
This of course is a cartoon version, but I think it expresses the core of the cognitive bubble framework. Its adherents think it is very radical and liberating, and self-evidently correct. I won’t belabor the obvious contradiction between the no-objective-criteria-across-bubbles hypothesis and the claim that the cognitive bubble world is the one we all live in. The only other point I’ll make is that, true to their belief that each cognitive world is impervious to criticism from another, adherents never, and I mean never, acknowledge, much less grapple with, serious criticism of their worldview. Instead, they argue by authority: Author X, who is much admired by people like us, says thusly, and so we can use this insight as a basis for further analysis. “Argument” in this context tends to take the form of exemplary analogy: here is a good way to think about the topic at hand because something like it works in a situation that is analogous to it in some respects. Argument by analogy fits a subjectivist framework, since its salience derives from aha-ness, not the sort of reasoning or empirical evidence that depend on objective criteria.
So how can this framework be extended to the world of information sciences and mathematical modeling? Thompson’s insight is that each model can be thought of as existing within its own cognitive bubble, composed of the assumptions that structure it and the purposes it’s designed to serve. Each model is true within its own bubble, but we need to step outside them, into the world of social and cognitive diversity, to see their limitations and escape their claims to any broader truth or objectivity. And that’s sort of it. While (as you can see) Thompson didn’t persuade me of any of this, I think there’s a chance her book will be successful on its own terms: future writers of the radical subjectivist persuasion may cite her as the reason why we should all think about models in this way.
My own view is probably clear from the way I describe hers, but just to be complete, here is its own cartoon version: There really are better and worse models, based on criteria that apply across different social and intellectual divides. Our self-knowledge is imperfect, and others often understand things about us we don’t see. We benefit from their criticism. They can also represent us, sometimes better and sometimes worse than we would represent ourselves. Arguments that evade engagement with counterargument are generally weak and unreliable. Arguments based on reasoning and evidence are better than those based on some version of grokking, and those are the criteria we’ll need to use if we’re serious about positive social change. How much we share with one another, cognitively and otherwise, is not a matter for ex cathedra generalizations; it’s something we discover through interacting with others—or better, something we can create by building on what already connects us.
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Agreed that this is a cartoonishly simple way of looking at modeling, and that many models do not fit into this bubble analogy. However, even if we took this analysis to be true, it would still be possible to merge many bubbles by finding their commonalities, and then discarding the parts that don’t fit the larger picture. Hence, even in a bubble-model world, there are many possibilities for merging and expanding models to come to a more accurate picture of the system under study.
Sure but at some point value judgments must be made. Certain ideas are superior in the way they comport with specific realities and cultures. We’ve been “merging models” for decades now and it only results in globo-homo, corrupting MBA-type thinking that somehow always manages to serve the interests of entrenched power.
My only quibble with this is that most mathematical models in Economics are also a good example of cognitive bubbles. This is not to say that all mathemetical modeling in Economics fits this bill, just most of it. The method of trying to analyze fictitious economies by the use of formal mathematics is itself a form of radical, subjective idealism. Otherwise, I liked this article.
Subjective muddling always rules in times like these. I believe the ancient Greek term was kairos. In times of upheaval, no model is trusted. In times of stability and consensus, the ruling model is always accepted as axiomatic. So the present day fashionable questioning of all models is a hopeful sign. Its the only way out.
“In times of upheaval, no model is trusted.”
An interesting point, but what do we make of a claim that no models can be trusted? That all models being subjective, they cannot apply across the “bubble”. I don’t think it’s the questioning of all models we see here but rather the denial of the ability to make models at all. Of course, as the author of the article notes, this is a patent contradiction, as such a claim is an attempt to model human behavior.
Its not that no model can be trusted. Instead we don’t have any acceptable criteria to evaluate the models. Its like we are in a really big room and someone has turned out the lights and rearranged the furniture.
This stuff is so goofy.
“Each of us exists in our own bubble, a product of our experiences and perspectives.”
Yes, and a significant portion of those experiences are of a world outside of us. Or are the sun, the moon, and the stars a product of your subjectivity? And how is it that we can speak of them and everyone knows what you are talking about, if it’s all in your head? How is it we can speak at all, if we all exist in our own little bubble? What is language but a means to pierce such bubbles? While our individual perceptions of them may differ to a small degree, they are ontologically distinct from our subjectivities.
“Our thoughts express this subjective world, and they are true in relation to it but false beyond its boundaries.”
OK, got it! So the next time someone tells me “All whites are racist!” or “Steve is a girl who was born with boy-parts!” I can safely ignore them. Because while subjectively true for the speaker, my thoughts tell me the first is just racism and the latter delusion. Since truth is subjective, all subjectivities are true. Check!
“This means no one has the right to speak for nor criticize anyone else.”
Yet the idiots who promote this garbage do exactly that when they criticize anyone who doesn’t agree with them. How can you come up with a notion of justice if you cannot criticize the actions of others? How can you represent the downtrodden, those without a voice, if you cannot speak for them?
“In some versions, bubbles can be shared among people with the same set of identities, but, as before, not across them.”
I believe this is know as “standpoint epistemology” in some circles. All of this arises from the fever-swamp of postmodernist epistemologies and ontologies, although I believe “standpoint epistemology” in it’s original incarnation was a Soviet Marxist concept that held that the working class had it’s own perspective on reality. I seriously doubt though that they took it to the inane extremes we hear of today.
If you are referring to the Frankfurt School, I think that they would have laughed themselves silly.
If I understand the idea of us being in our own bubbles, one can claim that nothing exists except in a person’s and so there is no right or wrong, no permanent categories, no nothing. It like “philosophical” supercharged liquid modernity meant to destroy what is left of society. Maybe, I could think of it as a mental lotus-leaf because if nothing is real except a person’s bubble, why try to change anything? I am probably getting it wrong, but this is what the ultimate conclusion of these ideas.
The Frankfurt School’s ideas were meant to bring understanding and perhaps improving society. It seems like much of thought done to bring such understanding in the past century have been deliberately twisted.
I wonder what they would tell a slave owner like John C. Calhoun, the man who claimed that slavery “a positive good.”
I’m not a philosopher (nor do I play on on T.V.), so I had never heard of “standpoint epistemology” and went to look it up (always like to learn something new). In my brief research I came across an academic paper titled, “The Development and Validation of the Epistemic Vice Scale.”
I never knew (or had reason to know) that there was an “Epistemic Vice Scale” or that one was being developed and validated. I think this is the beginning of the end for civil society (but then, I’m not a Sociologist either).
So I would be interested to know how these true believers deal with the ideas of R D Laing in regards to our world and the outside world, such as ““We all know from our personal experience that we can be ourselves only in and through our world and there is a sense in which ‘our’ world will die with us although ‘the’ world will go on without us.”
Well, there is always Power. Some bubbles have more Power than others, don’t they?
Alas, for many “bubbles,” their greatest ‘power’ is expressed when they “pop!”
My former girlfriend was a model (not).
She wasn’t known as “Bubbles,” was she?
[I hesitate to ask such a ‘personal’ question, but since this is an economics blog, it is pertinent: “Did she ever work at ‘Minsky’s’ burlesque?”]
Can you believe it? I hooked up with a model!
The muddle seems to me to be based on confusion about what the word “model” means.
It’s trivially true that we have no direct knowledge of the outside world (or even if there is one) and never can have. Our brains create a “model” of the world for us, partly based on what we take to be sensory inputs, but mostly on inference and memory, as cognitive psychologists have been documenting for decades. These “models” are by definition subjective and personal, so there’s no way of knowing whether that the colour I describe as “red” is perceived the same way by you.
The second use of “model” has little to do with the first, and amounts to a set of assumptions about how the world works. The classic example is the Conspiracy Model, which sees all events as determined by hidden forces, and is, of course, a development of the Providential Model, which sees everything organised by an all-powerful deity. But there are also more mundane models based on our judgement about “how the world works,” as well as how it “should” work. Since these models are based on our individual experiences and our emotions, it’s safe to say that there will be many different and incompatible models.
But I don’t see what mathematical modelling has to do with either of these things, except in the trivial sense that what you get from a model depends on the assumptions you start with. Mathematical models of (say) the economy are true or false insofar as they correctly describe or predict how the economy works. That’s it.
” trivial sense that what you get from a model depends on the assumptions you start with”
Trivial?
Why should our knowledge of ourselves be any better than our knowledge of anything else?
However much we may believe we know, it’s a lot less than we imagine. And as a general rule, we all suffer from a paucity of imagination
However much we may imagine we know, we understand substantially less.
That’s me, blowing bubbles!
War is the Father of All. You may have your own subjective view on how much artillery shells you need, and I may have my own subjective view of how much artillery shells I need, but when you and I contest each other, the first one to run out of artillery shells is toast. You can have subjective ideas about how to manufacture artillery shells, and you may different models about how to aim them at targets, but guess what happens in the real world.
Hard not to see this subjective bubble talk as a manifestation of late Maria Antionette/Nicolas and Alexandra decadent elite head space. Its conceptual oil for the guillotine.
I certainly don’t count myself as a radical subjectivist, but when it comes to Economics, I think subjectivism has a lot to add. Why? Because traditional economists need to come to an understanding that the assumptions and approach one chooses when building a mathematical model are inherintly subjective. Economics has neither the granularity nor precision in its data to make those decisions objective.
This was Milton Friedman’s contention, but it amounts to sophistry. Without comprehensive laboratory experiments one cannot determine which models “correctly” (nee, accurately) predict the economy. Economics consists almost exclusively of natural experiments where isolating variables is difficult.
I’d point to the recent post by Steve Keen (reproduced here at NC) where he notes the discipline’s refusal to alter its models in response to either J.K. Galbraith or Alan Binder’s real world observations about marginal costs.
I’d also point to the recent sophistry of Larry Summers claiming that economics has “laws” the way engineering does. Wrong on both counts. There are no laws of engineering. Physics has laws, engineering uses physics to produce art, physics is but one tool in the toolbox.
There is not one single model in economics which describes real world phenomena with the accuracy a physicist would require to elevate a model into a law. Bad economists may point to certain accounting, but that’s endogenous, it doesn’t count.
If the radical subjectivists can beat some sense into the Larry Summers’ of this world, so much the better, even if they’ve gone too far in their embrace of subjectivism.
I hadn’t assumed that economic models were necessarily accurate, and certainly not in the way that models derived from physics are. My point was that they are epistemologically different from, for example “models” of the world that we have in our heads. You could rephrase it to say “Mathematical models are only of value insofar as they yield results which are practically useful.”
I am waiting for the book with the cognitive bubble perspective on life boat ethics.
how timely. I interacted today with my checkout clerk at the grocery store. Guy is way smart. Comes out from behind his counter and rings up my beer and wine and then zooms thru the rest of it as he talks nonstop about SVB and the fact that this mess is all somewhat connected to crypto. His analysis makes good sense and all I add on my way out is that the regional Pacific Corp Bank is reportedly looking shaken and he says yes – that’s because the public perception is that PacificCorp, like they thought SVB was dealing in crypto, were also dealing in crypto. He knows SVP went down because of their loss on long bonds but he says everybody is on the verge of panic over crypto. He gave a surprisingly good little lecture. I’m thinking he is a burned-out professor. And as I leave the store I mutter to myself, Why didn’t they stop crypto? That’s still my big question.
Because crypto is just one spoke on the VC wheel. It’s the whole wheel that’s defective in a rising rate environment, not just individual spokes.
This whole discussion makes me think this is just cognitive bias for elites and PHDs. A way of processing information that is still beyond their comprehension, as intelligent as they are.
Very true. Along with a ghastly mix of appeal from the authority of (psuedo)science and self delusion about both relevance and ability.
This school of thought (alas) is close cousin to the one that we all live in a simulation. No one with a dental appointment really believes this life is a computer program, any more than any sane person believes his/her beliefs have no foundation in objective reality.
It’s just that the only objective reality the claimant is willing to acknowledge in public is that his possession of universal truth establishes that there is no objective reality.
I assume the reviewer did not like the book. From his not-exactly detailed critique I cannot tell if he even read it.
A couple of other reviews seem to disagree with Peter Dorman See below.
It looks like Thompson does not come from an economics background. The PH.D in Physics is a giveaway. I wonder if she criticized some economic modeling efforts? Dr Erica Thompson
https://eandt.theiet.org/content/articles/2022/11/book-review-escape-from-model-land-by-erica-thompson/
https://www.washingtontimes.com/news/2023/jan/12/book-review-escape-from-model-land/
He did read it but did not deem it to deserve a detailed treatment.
I just returned from a few days away and saw this. There’s so much to say, but briefly:
(1) Read the section on “Strong Objectivity” in the final chapter (10) of Thompson’s book. That’s the somewhat less cartoonish version of her we’re-all-in-our-bubbles philosophy.
(2) Read her discussion of climate modeling, a topic on which she is supposed to be well-informed. Her critique of Nordhaus is that (a) his damage numbers look small to her, and (b) his aggregate measures of warming-induced cost do not recognize the specific harm faced by low-income countries. Her solution is to locate an “assemblage” outfit (piecing together multiple model outputs) in a country in the global south, so that climate science can get out of its western, white bubble. (You can see why this would exasperate me in particular: compare to the detailed, very specific criticism — a whole chapter — I give to social cost of carbon models in Alligators in the Arctic and How to Avoid Them: Science, Economics and the Challenge of Catastrophic Climate Change.)
(3) Read her discussion of why economic models failed to predict the 2008 financial meltdown. There isn’t a single word about the intrinsic inability of representative agent models to explain or predict such events. There is no mention of multiple equilibria in valuation due to interactive beliefs, a phenomenon perfectly well described by Keynes (without the math). For Thompson it all comes down to who is doing the modeling and what their purpose is, so we don’t have to go into the structure of the models themselves; it’s enough to critique the bubbled nature of their authors and users.
(4) The two fawning reviews linked by jkrideau have no detail or substance.
One minor peeve: every chapter of Thompson’s book contains “greatest hit” quotes about models, science, the need for reflection, etc. Anyone who has worked in this field has seen these quotes dozens of times. It’s like reading a mediocre term paper.
Hard to tell from the cartoonish description what the book being criticized is actually trying to say, and whether it attempts to do something worthwhile even if unsuccessfully. Mathematical modelling of e.g. the economy or of business or military activity is of course perfectly fair game for criticism, and that the models fail to account for important stuff is a well known idea. The McNamara fallacy (anything that can’t be measured doesn’t exist) and Bonini’s paradox (models inevitably can’t explain things more complicated than the model) are both subjects of wikipedia articles.
I thought this was interesting though itself unsuccessful in leading to a solution with basic fairness, because of unavoidable inconsistency between decisions: https://philosophynow.org/issues/141/On_Casuistry
Jill Lepore just posted a short article on the topic – The Data Delusion:
https://www.newyorker.com/magazine/2023/04/03/the-data-delusion
Possibly a better formulation of the critique of math-ism. Though undoubtedly too short for serious discussion.
The American Prospect has started a series of articles on the perils of over-reverence for models. The first piece is by none other than Joseph Stiglitz:
https://prospect.org/economy/2023-04-03-how-models-get-economy-wrong/