Three-Toed Sloth

Books to Read While the Algae Grow in Your Fur, April 2018

Attention conservation notice: I have no taste. I also have no qualifications to opine on the history of Renaissance astrology.

Laura Lippman, Sunburn

Noir mystery, set in the archaic past of 1995. Every single viewpoint character is deceiving everyone they interact with, and in a few cases themselves, and there is quite a bit of Lippman mis-leading the reader as well. I nonetheless found myself rooting very hard for the protagonists, despite their tendency to eat everyone around them alive. This might be the best novel Lippman's ever written, which is saying a lot.

Susan Wolfe, Escape Velocity

Mind candy mystery, in which the daughter of an Arkansas con-man makes her way, mostly legitimately, into a job in a flailing Silicon Valley company, in search of a better life for her and her teenage sister, and proceeds to find scope for her "special talents". The novel succeeds in three big ways: its presents poverty amid crazy wealth unsparingly but matter-of-factly; it doesn't drink any of the Silicon Valley kool-aid; and it makes you want to see the heroine succeed, despite her increasingly criminal acts --- and leaves you in no doubt that those are criminal and reprehensible acts. Its big failing, to my mind, is that it's really not savage enough about the specific craziness and pomposity of the Valley; a few local references aside, this could be a satire of just about any corporation anywhere in the US. Considering Wolfe's evident gifts as a writer, this seems like a lost opportunity, but perhaps there will be a sequel.

Martha Wells, All Systems Red

Mind candy science fiction. The novelty here is this nice but straight-forward story being narrated by a self-named "Murderbot", which has hacked itself to be able to ignore human commands, but just wants to be left alone to watch its "serials". This is an amusing twist, and it's a fun novella with a dry sense of humor, but I fail to grasp why so many people are so rapturous about it. Still, since I think Wells has been under-rated for decades, I'm not sad to see her get some recognition!

Pamela Ribon and Cat Farris, My Boyfriend Is a Bear

Comic book mind candy: the title is meant literally. Fundamentally, it's yet another avatar of the ancient tale of the lost Magic/Animal Husband (Aarne-Thompson index number 425A), done this time as a very sweet romance. Any attempt to read it as an allegory for our contemporary controversies about non-traditional forms of sex will, I think, dissolve into incoherence (which doesn't mean that they won't be attempted, or even that such allegories weren't intended by the authors).

Not via Jeet Heer, remarkably enough.

Anthony Grafton, Cardano's Cosmos: The Worlds and Works of a Renaissance Astrologer

On one level, this is a readable exposition of how Cardano worked and thought as a practicing astrologer, including extensive background on the sophisticated and ancient astrological tradition he came out of, with some glances at how that connected to his practice as a medical doctor and a mathematician (though there's less about the latter than I would have liked). My fellow Eisensteinians will be especially intrigued by the way one of Cardano's signature projects, assembling and publishing a large collection of supposedly-reliable "genitures" of well-known figures (i.e., horoscopes cast for the purported time of birth, with all relevant planets and stars properly accounted for and interpreted) was in part about bringing information which had circulated in manuscript form among social networks into public print.

On another level, this book is Grafton subtly, or not-so-subtly, insinuating that the quantitative social sciences are no better than Cardano's quantitative astrology.

Cardano's theories were not so obviously superior to rival ones as he would have liked. Accordingly, he buttressed them with replies to potential objections. To the argument that a given star should affect not a single city or state but everyone living anywhere on the parallel over which it passed perpendicularly, for example, Cardano replied with qualifications. The star would have such effects only if it had reach that position on the data when the city or state in question was founded, at noon, and in conjunction with the sun. What technical arguments could not achieve, the language of somber threat and mystification might. Cardano gave his readers not only clear, easily applied rules of prediction which anyone could easily grasp and use, but also rules of interpretation as rich in predictive force and slippery in practical application as any master of astrology could hope to provide:

In every geniture there is a best position, which controls all good fortune, and a worst one, which controls all misfortune. The best place is the tenth house, or the first one, or a luminary, if there is joined with these fortune, or a propitious ray, or that of the other luminary, or a fortunate star, so that the good fortune is doubled. Thus the place of misfortune is misfortune multiplied twice.

Anyone who could grasp the method laid out here --- and work out exactly which planetary and stellar positions must be taken into account in applying it --- obviously had access to a powerful tool for determining the effects of a given configuration of the planets unequivocally.

Equally obviously --- or so it seems now --- no one could hope to use rules like these as rigorously as one could apply Cardano's instructions for determining the time at night or the position of Venus. The doctrine itself was complex: the multiple possible ways of applying it ensured that the results could turn out as seemed best, in a given situation, to the astrologer. [pp. 63--64]

As so often, Cardano's astrology lends itself to parody when seen in retrospect. Like good economists, the ancient author [Ptolemy] and his modern annotator [Cardano] explain in chorus why their discipline matters to humanity even though it cannot, and supposedly does not try to, predict specific outcomes with absolute certainty. Much of Cardano's practical advice --- like the suggestion that one travel in as large a group as possible, since if most of the passengers on any given ship are not foredestined to die in a wreck, the danger is lessened --- has all the precision and intelligence of a modern discount broker's newsletter. [p. 143]

The contrast between Cardano's practices [in mathematical and observational astronomy] and normal ones [of astrologers] was sharp. Most astrologers used their tables as social scientists sometimes apply software packages: they treated these paper devices as black boxes, understanding little or nothing of the principles on which they rested and having little or no ability to compensate for their defects. Their nasty remarks about their competitors rarely rested on a demonstrated mastery of astronomical materials and methods. [p. 61]

Cardano... never saw his own experiences of the autonomy of politics and the power of change [sic; read "chance"?] as reasons for rejecting astrology, either in the political or in the personal sphere. Though he sometimes explained particular events in terms that denied belief in occult influences, he consistently resorted to astrology, as a practice, a well-used set of tools, worn and polished by the use of decades. Even though some of his late comments sugges that he had less faith in astrology than in medicine, he still used it... to organize his last substantial work, his autobiography. Cardano's ability to wield other, radically different tools at the same time should occasion little surprise. Many scholars nowadays use computers to write and fax machines to submit the conference papers in which they unmask all of modern science as a social product, a game like any other. Though they hold that the laws of fluid dynamics are only one way, no more valid than many others, of describing the motion of air over wings, they take airplane trips to participate in the self-congratulatory discussions that ensue. Compared to the sterile credulity of the modern arts of analysis. Cardano's arts of prediction look bright, warm, and solid enough to explain their appeal to the wide range of intelligent readers they attracted and informed. [p. 176]

Grafton does not bother himself with refuting astrology, though he does mention some of the sound arguments against it which were already familiar in Cardano's time. Here is one which particularly struck me:

Nicole Oresme observed [in the 14th century] that it took millennia for celestial phenomena to recur even once; some never did. The astrologers, who had been working for only the few thousand years since Noah's Flood, could not possibly have derived their rules for interpreting the effects of conjunctions and oppositions from observation. They simply had not had enough time. [p. 51]

I highlight this one because it applies, mutatis mutandis, to the macroeconomists. §

Update: More Cardano.

Mary Louise Kelly, Anonymous Sources

Mind-candy thriller, in which nuclear terrorism is foiled by an Intrepid Lady Reporter. Kelly gets extra points for making the ILR a very un-apologetic person who has done some very un-nice things, but is still sympathetic. It's not as good as her second novel, The Bullet (where I now realize the ILR has a brief cameo), but still fun.

Books to Read While the Algae Grow in Your Fur; Pleasures of Detection, Portraits of Crime; Scientifiction and Fantastica; Writing for Antiquity

Course Announcement: Data over Space and Time (36-467/667), Fall 2018

Attention conservation notice: Notice of an advanced statistics class at a university you probably don't attend, covering abstruse topics you probably don't care about. Also, it's the first time the class is being offered, so those who do take it will have the fun of helping me debug it.

This course is an introduction to the opportunities and challenges of analyzing data from processes unfolding over space and time. It will cover basic descriptive statistics for spatial and temporal patterns; linear methods for interpolating, extrapolating, and smoothing spatio-temporal data; basic nonlinear modeling; and statistical inference with dependent observations. Class work will combine practical exercises in R, some mathematics of the underlying theory, and case studies analyzing real problems from various fields (economics, history, meteorology, ecology, etc.). Depending on available time and class interest, additional topics may include: statistics of Markov and hidden-Markov (state-space) models; statistics of point processes; simulation and simulation-based inference; agent-based modeling; dynamical systems theory.

Co-requisite: For undergraduates taking the course as 36-467, 36-401. For graduate students taking the course as 36-667, consent of the professor.

Course materials will be posted publicly on the class website (once that's up).

Corrupting the Young; Enigmas of Chance; Data over Space and Time

Major depression, qu'est-ce que c'est?

Attention conservation notice: 1100+ words on a speculative scientific paper, proposing yet another reformation of psychopathology. The post contains equations and amateur philosophy of science. Reading it will not make you feel better. — Largely written in 2011 and then forgotten in my drafts folder, dusted off now because I chanced across one of the authors making related points.

As long-time readers may recall, I am a big fan of Denny Borsboom's work on psychometrics, and measurement problems more generally, so I am very pleased to be able to plug this paper:

Denny Borsboom, Angélique O. J. Cramer, Verena D. Schmittmann, Sacha Epskamp and Lourens J. Waldorp, "The Small World of Psychopathology", PLOS ONE 6 (2011): e27407 [Data, code, etc., not verified by me]

Abstract: Mental disorders are highly comorbid: people having one disorder are likely to have another as well. We explain empirical comorbidity patterns based on a network model of psychiatric symptoms, derived from an analysis of symptom overlap in the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV).

We show that a) half of the symptoms in the DSM-IV network are connected, b) the architecture of these connections conforms to a small world structure, featuring a high degree of clustering but a short average path length, and c) distances between disorders in this structure predict empirical comorbidity rates. Network simulations of Major Depressive Episode and Generalized Anxiety Disorder show that the model faithfully reproduces empirical population statistics for these disorders.

In the network model, mental disorders are inherently complex. This explains the limited successes of genetic, neuroscientific, and etiological approaches to unravel their causes. We outline a psychosystems approach to investigate the structure and dynamics of mental disorders.

In the initial construction of the graph here, two symptoms are linked if they are mentioned in the DSM as criteria for the same disorder. That is, Borsboom et al. think of the DSM as a bipartite graph of symptoms and disorders, and project down to just symptoms. (There is some data-tidying involved in distinguishing symptoms and disorder.)

The small-world stuff leaves me cold — by this point it might be more interesting to run across a large-world network — but the model is intriguing. Each node (i.e., symptom) is a binary variable. The probability that node $i$ gets activated at time $t$, $p_{it}$, is a function of the number of activated neighbors, $A_{i(t-1)}$: \[ p_{it} = a + (1-a) \frac{e^{b_i A_{i(t-1)}-c_i}}{(1-a)+e^{b_i A_{i(t-1)}-c_i}} \] In words, the more linked symptoms are present, the more likely it is for symptom $i$ to be present to, but symptoms can just appear out of nowhere.

Statistically, this is a logistic regression: $b_i$ is how much symptom $i$ is activated by its neighbors in the graph, $c_i$ is a threshold specific to that symptom, and $a$ controls the over-all rate of spontaneous symptom appearance and disappearance. Using a very interesting data set (the National Comorbidity Survey Replication of about 9200 US adults), Borsboom et al. in fact fixed the $b_i$ and $c_i$ parameters by running logistic regressions. The $a$ parameter, which was kept the same across symptoms, was tweaked to make the rate of spontaneous occurrence not too unreasonable.

What Borsboom et al. did with this model was to run it forward for 365 steps (i.e., a year), and then look at whether, in the course of the previous year, it would have met the DSM criteria for major depression, and for generalized anxiety disorder, and then repeat across multiple people. It did a pretty good job of matching the prevalence of both disorders, and got their co-morbidity a bit too high but not crazily so.

Now, as a realistic model, this is rubbish, for a host of reasons. Lots of the edges have to be wrong; the edges should be directed rather than undirected; the edges should be weighted; the logistic form owes more to what psychologists are used to than any scientific plausibility. (Why should psychopathology be a spin glass?) The homogeneity of parameters across people could easily fail. And yet even so it comes within spitting distance of reproducing the observed frequencies of different conditions, and their co-morbidities.

Notice that despite this, there are no underlying disease variables in this network, just symptoms. So why do we believe that there are unitary disease entities? I can see at least three routes to that:

1. Perhaps this symptom-network model simply fails to match the detailed statistics of the data, while latent-disease-entity models can. This might be a bit boring, perhaps, but it would be persuasive if one could show that no model without the disease entities could work. (I find that dubious, but my doubt is not evidence.)
2. Alternately, one might appeal to causal autonomy. The temperature of a gas, in a strong sense, amounts to the average kinetic energy of its molecules, and one can accurately simulate gases at a molecular level without ever invoking the notion of temperature. But if I manipulate the gas to have a certain temperature, then, very quickly, the effects on pressure and volume, and even the velocity distribution of individual molecules, is always (pretty much) the same, no matter how I bring the temperature about. This is what lets us give sensible causal, counter-factual accounts at the level of temperature, and thermodynamics more generally. (Cf. Glymour.)
   Now, in the network model, we can imagine "giving someone" generalized anxiety disorder, by activating some set of nodes which meets the DSM criteria for that condition. There are actually multiple, only partially-overlapping symptom sets which will do. In the network model, these different instantiations of generalized anxiety disorder will have similar but not identical consequences (for other symptoms, duration of the condition, response to treatments, etc). If, in reality, it makes no difference how someone comes to meet the criteria for generalized anxiety disorder, the implications for the future are always the same, that would be a powerful argument that the disorder is something real.
   More medically: think how we distinguish diabetes into type 1 (the body doesn't make enough insulin) and type 2 (the body doesn't respond properly to insulin). This is, I'd say, because they differ greatly in their causal implications, but once you find yourself in one of these classes, it makes little difference how you got there.
3. It could be that a description in terms of higher-level entities like depression allows for a higher efficiency of prediction than just sticking with symptoms. This notion could even be made fairly precise; it may also end up being the same as the second route.

Of course, it might be that to make any of these three defenses (or others which haven't occurred to me) work properly, we'd have to junk our current set of disorders and come up with others...

Minds, Brains, and Neurons; Networks; Enigmas of Chance

An _Ad Hominid_ Argument for Animism

Attention conservation notice: Note the date.

A straight-forward argument from widely-accepted premises of evolutionary psychology shows that humans evolved in an environment featuring invisible beings with minds and the ability to affect the material world, especially through what we'd call natural forces.

1. (Premise) Humans have evolved psychological modules, which carry out specific sorts of computations on very specific sorts of representations, as triggered by environmental conditions. These modules are in fact adaptations to the "environment of evolutionary adaptation", or, rather, environments.
2. (Premise) Indeed, when we encounter a human cognitive module, we should presume that it is an evolved adaptation.
3. (Premise) Humans have modules for theory-of-mind, social exchange, and otherwise dealing with intentional agents by reckoning with their beliefs, desires, intentions, and (crucially) capacities to act on those intentions.
4. Therefore, the human modules for theory-of-mind, social exchange, and dealing with intentional agents are evolved adaptations to our ancestral environment.
5. (Premise) Humans often engage those modules when dealing with invisible beings, often manifesting as (what scientists categorize as) natural forces.
   (In fact, such engagement of those modules was near-universal up to the emergence of WEIRD societies. The historical record shows aberrant individuals who did not do this, but it's plain even from texts those individuals authored, when they have come down to us, that their bizarre behavior had absolutely no traction on the vast, neurotypical majorities of their societies. [One is reminded of the militantly color-blind trying to convince others that colors do not exist.] Moreover, treating natural forces as manifestations of invisible beings who are intentional agents, amenable to bargaining, threats, supplication, etc., etc., is still very common in WEIRD societies, perhaps even modal.)
6. (Premise) Engaging a wrong or inappropriate module is expensive, even potentially dangerous, and thus mal-adaptive, and so should be selected against.
7. If natural forces are mindless and invisible beings did not exist in the EEA, then engaging theory-of-mind and social-exchange modules to deal with natural forces and invisible beings would be mal-adaptive.
   (Occasionally, people suggest that it's so dangerous to ignore another intentional agent that it was adaptive for our ancestors to suspect intentionality everywhere, on "better safe than sorry" grounds. I have never seen this supported by a concrete calculation of the costs, benefits and frequencies of the relevant false-positive and false-negative errors. I have also never seen it supported by a design analysis of why our ancestors could not have evolved to realize that storms, earthquakes, droughts, diseases, etc., were no more intentional agents than, say, fruit, or stone tools.)
8. Since those modules are adaptive, we must conclude that invisible beings with beliefs, desires, intentions, and the power to act on them, especially through "natural" forces were a common, recurring, predictable feature of the environments of evolutionary adaptation.

Of course, none of this implies that those invisible beings aren't as extinct as mammoths.

To spoil the [not very funny] joke: even if the relevant modules exist, they are engaged not by intentional-agent-detectors, but by human mental representations of intentional agents. Once the idea starts that storms are the wrath of some invisible being, that can be self-propagating. For further details, I refer to the works of Dan Sperber, especially Explaining Culture (and to some extent Rethinking Symbolism). Credit for the phrase "ad hominid argument" goes, I believe, to Belle Waring, back in the Early Classic period of blogging.

Modest Proposals; Minds, Brains, and Neurons; The Natural Science of the Human Species; Philosophy