Because not everybody wants to be in STEM. And because even those who are in STEM need to know that humanity does not live by STEM alone. (We'd like our STEM to treat people like humans, rather than like machines.)

A "liberal education" originally meant that those who pursued it were free. They weren't pursuing an education of mere techniques, which was for slaves. Even today, there is a place for learning things that don't have a direct economic impact, as part of becoming an educated person.

That's from the more idealistic side of me. Now here comes the cynicism. Why? Because people still want to major in them, so that they can say that they have a college degree without having to major in something rigorour. And those people pay tuition. And the colleges like getting paid.

Because music, history, and literature are just as important to human society as math, computer science, and physics. This unthinking disrespect for the humanities is embarrassing.

> Why are they even taught in colleges? They're more of a hobby thing really (and more enjoyable that way imo)

Because that's why colleges exist...? Historically universities were not the workforce mills they are today. You did not go to a university to help you find work. Stuff like business/management, engineering, medicine, etc really shouldn't be part of universities.

That's what colleges are for. Even for the hard sciences you don't really get much "real" world profit-seeking experience.

Why is science even taught in college? All you need is a math book and YouTube to have people show you how to do the mechanical steps needed to solve problems.

(I'm sarcastic of course. Sciences and humanities are both cool and good and contribute to a better understanding of the world around us, and one wouldn't be much without the other.)

Because the operation (not just the physical structure) of the human brain (a complex neural network) and networks of brains (society) are just as important, if not more important subjects of study than physical systems and computers. Or are you suggesting that we completely abandon the understanding of human behavior at scale?

Humanities are the most effective method of teaching empathy that I am aware of.

The story reminds me of the HR practices of 'measuring' personality based on questionnaire to judge the competence of people for certain positions and determine their carrier path inside the organization (e.g. at Trimble). Imagine you are a software engineer applying for an engineering role and they ask you a hundred or more questions to compare the importance of aspects such as punctuality, trust, being patient, lawfulness, honesty and several more, 3 at a time, make a strict order of importance. Without specifics on the work context and situation. Then they build a multi dozen component report how good you are in this and that on a 1 to 5 scale. The way you work. Based on answers to strange questions, not actual work. When it is impossible to answer accurately (because it depends, or there is no order like between playing piano or being tall) then the results will be inaccurate, yet they use it to classify workforce like steel by its properties, determining their fate. Assessing work performance before doing any work. And they take it dead seriously like gauge on a pressure tank. It is just so ... well dumb, forcing any kind of oversimplified measurement on complex and fluid things, sounds like measuring friendliness by meter. People change, people adapt, people behave differently in different circumstances, very very differently, and definitely not how they admit it, no one can count how many influential factors there are, these robotic and unified approaches are just distorting for the purpose of appearing fair. It is far from fair, it is just robotic - which is ironic from a department called human resources, feels like robots work there not humans. Measuring fish by how high it can jump before allowing to swim.

It is just pretentious not scientific.

This is such a horrible article. Many have already mentioned the conflation of humanities and social sciences. Then by using the example of books (because most would agree books would loose their essence if we just describe them by numbers) it constructs a straw man that somehow we loose something (the beauty?) by using quantitative measures.

Sure many studies have flaws (not just in the social sciences), but what is the alternative that we simply use theories because of their "beauty" (whatever that means)? Shall we start psychological therapies just because someone thought it sounded good, instead of measuring if it works?

Articles and generally ideas like this always seem too dismissive. CPUs are nothing like brains because: intricacies. Algorithms can't be applied to literature because: intricacies. It is almost an appeal to emotions to say that rather than saying "ok well we tried to apply these electric constructs and algorithms in order to understand ideas and literature better, we got nowhere and here's exactly why", they are like "it can't be applied oh no it can't our humanity is so distinct and precious there are some lines not to be crossed and here's a million contrived examples as to why".

And to this approach I say, ignorant and cowardly.

This conflates social science with the humanities. I agree with respect to the humanities. Less so with respect to social science. People in large groups do in general follow certain trends and we do have decent ways of establishing causation. Now there is a lot of stuff that people do that we can't analyze quantitatively due to lack of data or other blockers. For these qualitative methods will have to do. Fine, but then we should accept that the conclusions from qualitative analysis are less firm and judge them accordingly.

I would add to this list economics.

Oxford Economist Kate Raeworth has made the exact same argument about her own discipline and the allure of the ‘hardness’ of maths and physics. The way early 20th century increasingly turned to Newtonian-like mechanistic descriptions of economic processes, reductionist and absurd ideas about ‘human nature’, and extracting Universal laws from historical and accidental correlations.

I do recommend reading the first half of her Doughnut Economics where she makes this case at length, from someone inside the discipline.

My father (a physicist) used to quote Rutherford to me: "all science Is either physics or stamp collecting". An extreme position perhaps. I now work in a college of humanities and have frequently collaborated with engineers. I have seen first hand how poorly applied scientific thinking has become within the humanities. But I cannot blame them. They are only giving to the uni what has been asked of them.

The untold reason why humanities now self-describes as 'social science' goes back to Thatcher years in the UK. She was the first to link university funding (and tenure) to research output. Research output was in turn defined by ranked publication and patents. This worked ok-ish in the sciences, but not so well in the arts. The humanities were obliged to ape the sciences in the way they spoke, the way they defined their outcomes and the functions they served. The scientific method is simply not a good fit for the arts.

This is a terrible article.

First of all, the introduction which bashes the paper which applying social network techniques to fiction? If the author had bothered to look it up, they would have realized the authors are an applied mathematician and theoretical physicist. Not humanities.

Then they goes on to criticize political science and psychology as their poster children for the humanities, except these are social sciences, and only "humanities" in a very broad umbrella term. "Humanities" is more often used to refer to disciplines such as history, art, literature. So a complete mix-up of fields.

Third, the assumption that social sciences has a "reliance, insistence, even, on increasingly fancy statistics and data sets to prove any given point" is simply flat-out wrong. For example, of course political science relies on "big-N" studies which try to find or refute correlations between democracy and various other country indicators. But political science also relies heavily on "comparative politics" which is much closer to literature or history in a classic "compare and contrast" aspects of two countries. Similarly psychology has many different approaches taken in published papers and books, some quantitative and others more qualitative.

I could go on and on. But this article is completely ridiculous, arguing against a straw man that simply doesn't exist. It's like the author isn't even familiar with academia. Bizarre.

One of the most valuable courses I took as an undergrad was an anthropology course. In it, we studied the life of JR Oppenheimer and his relationship with the government patrons of his science.

The sort of scoundrels naturally attracted to power will always find cynical use for talent of the kind possessed by Oppenheimer. However, every aspect of such a relationship will be thoroughly cynical.

If you are a future STEM person, understanding this fact will save you a lot of grief. Learn it early.

Perhaps the currency of social sciences should be anecdotes with full context (of which you can obviously get only a limited number unless you have unlimited budget) rather than collecting extensive data points on a limited number of variables. While physical systems can be approximated (or some independent variables dropped) without affecting the aspect being studied (think perfectly spherical objects), when it comes to humans, there are no independent variables. Approximation or simplified models are much harder.

I think looking for statistical patterns (e.g. in literature) is perfectly good science as long as you are cognizant that patterns merely invite more study an should not be used to reach conclusions, also being aware that patterns might disappear when you expand your data set.

Finally, as someone trained in the physical sciences, I used to look down on social scientists. I no longer do this. At least they're brave enough to tackle a complex monster with the limited tools at their disposal, stumbling and even enduring ridicule from the hard sciences. We ignore the human mind and collections thereof, because it's too complex and prefer the relative comfort of simple, predictable systems. I don't believe that's good.

Some people submitted nonsense papers (for example: rape culture at dog parks, and an excerpt from Mein Kampf), and they were accepted for publication.

https://www.timesofisrael.com/duped-academic-journal-publish...

The first paper she studies sounds interesting. Regression analysis on vocabulary has been used to identify authors of work whose authorship had been lost or to find context of where and in what circumstances certain authors grew up.

Mathematical analysis of linguistics has pointed to. Irrational patterns later confirmed by genetic analysis.

I don’t mind pointing out the vacuity of what often passes for scholarship. But she didn’t start with a good example.

I think one of the points that the article tries to make, is the point that proving something in a soft science using models is often based on many assumptions, be it implicit or explicit, and that this is problematic. To that I agree to some degree.

In hard sciences all inputs to a proof are either verifiable theorems known to be absolutely true, conjectures/hypotheses (in which case the proof becones a conjecture) and seldomly axioms. In soft sciences on the other hand, it is common to construct models quite arbitrarily, in order to try and match empirical results. If however, we would like these models to have any indication of "absolute" truth, similar to the hard sciences, currently we can't or don't.

To achieve this I believe we could do an input analysis of ALL assumptions and try and quantify the aggregated certainty of the model's correctness, even before matching it with empirical data. In this way we could say for example: we have used a model with a predicted input accuracy of 0.82, that matches our empirical results 0.97,p < 0.05. This would then further strengthen and quantify the "standing on the shoulders of a giant" principle.

Of course this is easier said than done and I know this is a bit naïve. Currently no techniques exist to do this as far as I know. There is also discussion to be had about how to interpret model outputs (we now have three variables, how do we relate them? How to calculate this model's output accuracy?) and how to calculate subsequent model's accuracy based on different input accuracies and their inter-relations. This would also require re-building soft sciences all the way from the bottom up (from the most easily verifiable facts first) to be useful and a new science on hypthesized model accuracy calculation.

Anyway, enough hypothesizing thought experiments for the day. Any thoughts?

Kinda funny, I guess.

This is one of those instances where I might care about the case Konnikova was making if she bothered using any quantitative methods to convince me the humanities were awash in quantitative study while qualitative analysis clearly went the way of the dodo. Or that literature programs were churning out students who think network analysis is the best way to understand a text.

In the purely-qualitative realm, it just comes off as pearl-clutching over something I don't think anyone actually believes?

I fully agree with the premise that humanities aren't a science. In fact I am fairly certain that the current paradigm of science can not work for at least history, though I strongly suspect most of the humanities.

One of the problems is computability, when I try to build statistics on a space of human intentions, then I strongly suspect that this is at least as complicated as trying to build a measurable space atop the set of all Turing machines, and there I get immediately the issue of computability. (For example, calculating the average run time of halting Turing machines.) So, then assuming that one can meaningful build a statistic (just the claim that this is possible) will doom any too formal reasoning, by principle of explosion.

I think anything can be a subject to scientific study. Methods are what is essential for a study being scientific, not the subject.

The article is talking, essentially, to the humanities. But the point applies to those of us on the outside as well. We as well need to stop expecting the humanities to be science.

Provocative title. The author argues - more or less - that quantitative and mathematical approaches do not lend themselves to questions of the humanities or social sciences.

As an example they take a network analysis that was done on social relations of characters of fictional works. While the author finds this use dubious, I think it's the contrary. While the researchers might not fully understand the methods, they could very well have a mathematician on hand. What do we do in math if not model real problems of real people?

It might be nice for some people to not know an application of their research but for humanities to find novel ways in which to use mathematical tools is great and should be encouraged. Of course they will miss but they will also hit. We need a peer review where those methods are understood within the humanities and social sciences, in order to not draw false conclusions.

Of course, qualitative analysis isn't going the way of the dodo and the author agrees on that.

I just think the occasional misuse of mathematical models for humanities research is well worth the possible gain. Those problems should follow some rules with a mathematical models, right??? Let's help those researchers instead of banishing them to qualitative methods.

Science implies the use of the scientific method. Scientific method implies falsifiable hypotheses. Anything that is not falsifiable isn't a science.

Elegant conclusions can totally be arrived at in the humanities, it's just that statistical methods often aren't the best way to go about doing so. The traditional method of logical proof, which is valued just as much as data analysis in science, used to be the standard in the humanities. The human mind would compute the statistics more or less subconsciously, but would then use those empirical results to say something valuable through a process of logical induction. I think that's the key point that this article misses—it isn't that we don't want humanities to provide rational insight, it's that we want humanities to reduce its reliance on statistics and refocus on what it's historically been great at.

There's something important to be said here about the duality between logic and math, algebra and statistics, classical AI and modern DL, philosophy and science, rationalism and empiricism.

I would encourage those interested in the intersection of STEM and the Humanities to check out the Digital Humanities Minor/ Major being offered at a growing number of universities. I earned the minor at UCLA, and found the application of digital tools to historical and modern "humanities" focused types questions to be incredibly relevant.

Examples include: 3D modeling of the historic broadway district in Los Angeles, Natural Language Processing of ancient Roman texts, virtual reality's impact on human cognition, etc.

Say i agree with the sentiment expressed here, what does the curriculum of a neo-classical humanities look like. Let's presume you'd want to keep the good stuff, things like Arrow's impossibilities theorem, Bayesian statistics, Network theory, Language pragmatics, ect. You know the sort of stuff that might aid the organisation of complex systems without repeating the mistakes of the past.

Maybe it is unfair to judge the hole field on a silly paper, in all fairness they write about non existing geometries in physics

Can you create a hypothesis and then falsify it? Then it's science.

Polls are really useful + accurate and are one of my favorite examples of stuff that came from social science research.

Humanities may not be a science, but being human sure is empirical.

Experience is all we have.

At the bottom of all of these bouts is then “demarcation problem”. What is a science, what isn’t a science?

I prefer Paul Fayerabend’s view: if it is useful To somebody somewhere - it is a science.

https://en.wikipedia.org/wiki/Epistemological_anarchism

Some people do not consider mathematics to be a science. They veiw it as a tool used in science, e.g., statitics.

On the one hand I completely agree that a lot of scientists across disciplines have too much confidence in the predictions of their models of complex systems. For example climate models predicting not only how much global temperature will rise but also on the local level, which seems far harder to predict. And the amount of studies that do not survive a replication attempt. But I don't believe that we can justify wasting tax money on people who don't try to back up their claims and instead just make up hypothesis after hypothesis, maybe based on a patient they knew, debating and sipping wine with their fellow intellectuals, prescribing morality under the guise of science and just laughing at us plebs. If you want to do that, become a writer or YouTuber, but not a scientist of any kind. If you're going to be a scientist at the very least try to back everything up with statistics. I know, It's work, it's not fun and it might not mean very much but you owe it to society to dig in and crunch those numbers.

Totally agree with you.

Given the title I expected to find an interesting article on what can go wrong if we overly rely on quantitative methods in the humanities. But this article doesn't distinguish between badly-applied quantitative methods and where the limits of those methods are even if they are executed well.

For example:

> We look at instances where the effect exists and posit a cause—and forget all the times the exact same cause led to no visible effect, or to an effect that was altogether different

This just sounds to me like bad quantitative modelling.

There is a huge argument to be made for qualitative research, and there is much-needed criticism of the idea that "hard" methods are more valuable than "soft" methods. I think this article manages neither.

When the measurement is flawed you will not know if the therapy works. Sorry. And the measurement is flawed! Actually, there is a crisis of reliability concerning modern research papers. (probably this is the source that many try to build castle out of dough?...)

> Shall we start psychological therapies just because someone thought it sounded good, instead of measuring if it works?

Yup. All psychotherapies were started just because someone thought they sounded good; and are still being practiced because they sound good. There are hundreds of different schools of psychotherapy today. There is a movement toward testing the effectiveness of therapies, but they just show whichever therapy the researcher fancies is the best, and metastudies reveal about equal effectiveness of all the major therapies.

The point is, I think, that quantitative measures are not lifting the scientific status of a field automatically; and can mask the lack of sound foundation.

It surprised me as well, especially because the author studied psychology, so she must know the difference between humanities and social sciences.

> conflation of humanities and social sciences.

You've missed the entire point. A sort of conflation is the problem - not by the author, but by people in and around soft sciences and humanities throwing a bit of statistical jazz into their papers and then drawing ostensibly rigorous conclusions which influence social policy.

The reality is that by their vary nature, both soft science and humanities (there is a lot of overlap) cannot be held to the same rigor as, say, mathematics, physics, chemistry. These sciences are pure theory (like gender studies), non experimental (like psychology), and fundamentally unfalsifiable in the majority of cases...but laymen, and apparently government officials, either don't understand or pretend they don't understand - either way shitty policy and legislation is passed and innocent people (society) are worse off frequently.

I'd hesitate to even call them intricacies. Billions of years of evolution in biochemistry and multicellular organisms, half a billion years in nervous systems, and over 200 million years in mammalian brains have culminated with about 50 million years of evolution of the primate brain. For every human being that has ever lived, nature has run 10^X continuous brute force "simulations" to arrive at our present civilization, where X is a ridiculously high number that's impossible to even estimate.

Sure, our intelligence allows us to skip a lot of those processes just like it allowed us to escape our gravity well and explore our solar system, but the jump from CPU to brain is like the jump from moon landing to intergalactic travel. The discrete nature of digital electronics alone prevents them from matching neurons because of sampling, let alone their lack of architectural (i.e. neural) plasticity. It's like trying to weld with a q-tip.

Can't upvote enough. It's easy to dismiss something you don't understand and wreck-less to assume you do. It's attitudes like these articles that led Planck to say, "Science progresses one funeral at a time"

If learning, math or otherwise, doesn't destroy your ego, you can do better. There is no shame in vocalizing uncertainty or a feeling of not understanding. Look at Stephen Hawkings - he had the courage to admit he was wrong and was one of his best critics.

Ego has no place in progress - scientific or otherwise.

This is a repetitive concept in modern society, just look at astronomy 100 years ago. People want their science to be more science than it is. If you build your models on faulty foundations, they don't mean anything. Many psychology studies use American college students, as if you can build a model of society in an international context with such a specific subset of people. This is valid criticism.

We can't predict how one person will react to a situation. But sometimes we can estimate, on average, how a large group of people will react.

Even a lot of engineering deals with similar types of uncertainty. We build huge structures out of metal, concrete, and wood on top of soils and other geological materials, often with the assumption they they are all homogeneous with constant material properties through the structure (they aren't). However, we can do this because the variations in properties tend to average out as the material sample gets larger. If we try to make the same assumption on very small scales, we find that there is a lot more uncertainty and our predictions aren't going to be as accurate. We see this in physics and many other scientific fields as well.

I agree. https://en.wikipedia.org/wiki/Psychohistory_(fictional)

When you describe continental drift, it doesn’t make the plates go faster. When you do economics, it changes the economy. Social sciences have a worse reflexivity problem than the arts, because with art, nothing turns on whether it’s right or wrong. With social sciences, if your hypothesis is wrong but widely believed, you can still kick off seventy years of communism.

social science is interpretation of data and much closer to history than science. The data will often change over time and thus the interpretation. Its very problematic that we treat it as science because it can be politized. To the extent its science its very very imprecise and is on the other end of the spectrum than something like physics which makes very very careful conclusions about very specific things and even they are to a certain extent also just interpretations. It should be called interpretational disciplines not science.

I’m not even sure the paper he starts off criticizing is that problematic - it sounds like it’s basically a quantitative study of various tropes in fiction and comparing it to real data.

I admit I haven't read or even heard of Kate Raeworth, but I am an academic economist. Most modern economic research is empirical, a paper poses a policy-relevant empirical question 'did policy X reduce unemployment' and then empirical evidence is presented (perhaps using data from a randomly controlled trial or using quasi-experimental variation). The statistics are calculated and the assumptions required for the validity of the statistical analysis discussed critically and at great length. Undergraduate econ classes unfortunately leave students with the impression that academic econ is mostly unrealistic theoretical models of behavior, but those models are just handy tools for hypothesis formation, and it is the empirical testing of hypotheses that makes a discipline a science, not the manner by which those hypotheses were formed.

To be fair, there is good economics out there - not as solid as the sciences of course, because the subject matter is more complex, but it does exist.

The main problem with the role of economics in society is that economics, and often pseudo-economics, are used to influence politics in a biased way.

Economists need to start strict self-policing and disavowing all the dishonest actors in political think tanks. It's difficult to do in practice because some of the dishonest actors get a lot of funding from political interests, but if economists want their discipline to earn respect as a science, they do need to clean up their act in this regard.

Yeah, it still baffles me that people think economics is a proven science and not built on a shaky foundation that falls apart soon as you prod it.

Do you think there is a factor of unknowns in both economics and humanities (disparate) that challenge scientific study? I.e. humanities and a further extension of art is currently immeasurable. If this sounds like a loaded question, I don't know how to phrase it correctly.

AKA, "The dismal science"

Not all economics is macroeconomics...

She did not confuse humanities and social sciences. She started off focusing on humanities then segued into a bigger complaint about humanities and social sciences together sharing the same problem. The author has a doctorate from Columbia in psychology. So there's probably a lot more thought behind her frustrations.

As for the home departments of the authors, that doesn't change the fact that their work was humanities research. Unless you're saying humanities departments shouldn't be blamed for arguably bad humanities research produced by "outsiders" and published in physics journals. It doesn't appear to me that the publication contained any new applied math or physics.

Correlations are not science by the way, no matter how repeatable they are, they're just statistics. You need to prove causation to be scientific. Big analyses of countries generally can't do controlled experiments so their findings are always dependent on what they chose to include (and not include) in their models as the supposed causal mechanism.

It may sound silly, but the article seems like a caricature of Big Bang's Sheldon disdain for social sciences. All the ingredients are there ready for easy consumption.

In all seriousness, there some valid criticisms of social sciences, but the article reads like a pop version of them.

I call these hard science vs soft science. Please do not get me wrong, I shuffle from math and art quite a bit these days and get to take a look at various approaches in both areas. There is a trend of applying hard science approach to soft science. This is good thing until it results in research that is quite wishy washy. When you see "study" where experiment is mainly surveying people, its soft science. Unfortunately such soft science gets a lot of press. When you see articles like "Coffee found to reduce cancer by researchers in a study", you are reading soft science. A huge problem is that people doing hard as well as soft science are referred to as "researchers" or "scientists" and both of their works referred to as "science". But its quite not. Science demands not only evidence but understanding. If coffee was found to reduce cancer, can you elaborate exact mechanism? If you can't then science requires not to make such claims. Doing survey of graduate students is not sufficient. That's the nature of hard science which soft science (including economics) violets too often. Media needs to be more aware otherwise the trust in science that has been developed over centuries will no longer be there.

Hi, there. I've studied Political Science, Film "Science" and IT. And Pedagogy. Why do I say Film "Science"? Because I had to use refuted "science" to analyze films, among other things (Freudian Analysis, which was of course groundbreaking at the time, but that does not hold up to modern scientific standards anymore). The professor said to me that, "Yes, I understand you when you say that this isn't stricly 'science,' and that it has indeed been refuted. But you see, everyone in this field does these things, and so you should too, at least for the experience, and to communicate with these people." So since he wasn't trying to force me view it as sience, I accepted it and did it on those grounds, and I passed. Despite this one incident, Film "Science" was my favourite topic at college, not least because it teaches you genre and narrative techniques. But yeah, some of it was definitively "out there," and I wouldn't classify it as science in any meaningful way, though it is a valid system to communicate ideas. Hell, even postmodernism is, which I sadly know too much about now. Too much about now.

totally agree. And then it even brings out the good old "tax payer money" line and asks if it is useful. As if we should only pursue that which seems instantly useful.

More frustrating is that there is some valid criticism of "digital humanities" for being the cool new discipline that while capable of some great stuff is guilty of all too often neglecting the "humanities" part of the term in favor of just throwing up some graphs.

> First of all, the introduction which bashes the paper which applying social network techniques to fiction? If the author had bothered to look it up, they would have realized the authors are an applied mathematician and theoretical physicist. Not humanities.

Nonsense. Whether a piece of research belongs to the humanities doesn't have to do with the credentials of the researchers but with the subject matter. If we genuinely want to say that scientific and mathematical methods are fruitful to explore questions in the humanities (contra the main claim of the article), we have to at least allow this. Or would you say that the paper on the network structures in fictions is a piece of theoretical physics?

A lot of people have been and continue to make this criticism that’s in the article, across a variety of the softer disciplines. (It’s like you’re not even familiar with this line of critique.)

See, eg. a criticism of political science in the same vein from a political scientist https://www.chronicle.com/article/How-Political-Science-Beca...

> Then they goes on to criticize political science and psychology as their poster children for the humanities, except these are social sciences

Social sciences are a humanities. The term social science was invented fairly recently by sneaky academics to leech off the credibility of actual science.

> It's like the author isn't even familiar with academia.

Are you? This issue with "social science" has been going on for a few decades now.

Richard Feymann called social science a pseudoscience a few decades ago.

https://www.youtube.com/watch?v=tWr39Q9vBgo

The name social science was invented for the same reason creation science was invented because real science had such a good reputation and they didn't so they decided to manufacture some credibility by attaching "science" to their fields.

I don't think the author is arguing for a banishment of certain authors "to qualitative methods." The problem described in the article is one I frequently see in Silicon Valley - ok, a couple of engineers build a thing. Note how they didn't start from asking "what is a real problem?" No, they built some tool/app. Now they spend several investment cycles trying to find "product market fit" by attempting to find some place in the market where that thing solves a real problem. This very rarely works as a business strategy - you first need to find a real problem and then build a tool that solves that problem.

Problem -> so what? (we build a solution) -> real business.

Now, replace "app" with "mathematical modeling," and you'll start to feel the author's gripe.

I do think the author is right to ask - what is the point? So what? What are you trying to do with those mathematical models? What problem are you solving? For instance, we have the hypothesis that the researchers of the British paper posited:

> the relative likelihood that certain stories are originally based in real-world events

Based on:

>looking at the (very complicated) mathematics of social networks

So, we have a tool - that tool is looking at the mathematics of social networks. Does high fidelity between models of social networks predict "realness?" Does a certain model of a social network described in the relationships of protagonists in a book suggest that book's events are accurate historical ones?

No, right? Then why is that step glossed over when the researchers go ahead and start modeling anyway?

If you reduce the humanities to what is quantifiable, you kill them. (You also kill humanity.)

[Edit: After re-reading, I'm not sure the parent thinks that numbers should take over the humanities, so my comment may be misdirected. I'm leaving it anyway, because I think the point is valid, even if it doesn't address the parent's point.]