Distant Reading and the “Evolution” Metaphor

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Are there any corpora that purposefully avoid “diachronicity”? There are corpora that possess no meta-data about publication dates and whose texts are therefore organized by some other scheme—for example, the IMDB movie review corpus, which is organized according to positive/negative polarity; its texts, as far as I know, are not arranged chronologically or coded for time in any way. And there are cases where time-related data are not available, easily or at all. But have any corpora been compiled with dates—the time element—purposefully elided? Is time ever left out of a corpus because that information might be considered “noise” to researchers?

Maybe in rare situations. But for most corpora whose texts span any length of time greater than a year, the texts are, if possible, arranged chronologically or somehow tagged with date information. In this universe, time flows in one direction, so assembling hundreds or thousands of texts with meta-data related to their dates of publication means the resulting corpus will possess an inherent diachronicity whether we want it to or not. We can re-arrange the corpus for machine-learning purposes, but the “time stamp” is always there, ready to be explored. Who wouldn’t want to explore it?

If we have a lot of texts—any data, really—that span a great length of time, and if we look at features in those data across the time span, what do we end up studying? In nearly all cases, we end up studying patterns of formal change and transformation across spans of time. The “evolution” metaphor suggests itself immediately. Be honest, now, you were thinking about it the minute you compiled the corpus.

One can, of course, use “evolution” as a general synonym for change. This is probably the case for Thomas Miller’s The Evolution of College English and for many other studies whose data extend only to a limited number of representative sources. However, when it comes to distant readings, the word becomes much more tempting. The trees of Moretti’s Graphs, Maps, Trees are explicitly evolutionary:

For Darwin, ‘divergence of character’ interacts throughout history with ‘natural selection and extinction’: as variations grow apart from each other, selection intervenes, allowing only a few to survive. In a seminar a few years ago, I addressed the analogous problem of literary survival, using as a test case the early stages of British detective fiction . . . (70-71)

The same book ends with an afterword by geneticist Alberto Piazza (who worked with Luigi Luca Cavalli-Sforza on The History and Geography of Human Genes). Piazza writes:

[Moretti’s writings] struck me by their ambition to tell the ‘stories’ of literary structures, or the evolution over time and space of cultural traits considered not in their singularity, but their complexity. An evolution, in other words, ‘viewed from afar’, analogous at least in certain respects to that which I have taught and practiced in my study of genetics. (95)

Analogous at least in certain respects . . . For Moretti and Piazza, literary evolution is not just a synonym for change in literature. Biological evolution becomes a guiding metaphor (not perfect, by any means) for the processes of formal change analyzed by Moretti. Piazza continues:

The student of biological evolution is especially interested in the root of a [phylogenetic] tree (the time it originated). . . . The student of literary evolution, on the other hand, is interested not so much in the root of the tree (because it is situated in a known historical epoch) as in its trajectory, or metamorphoses. This is an interest much closer to the study of the evolution of a gene, the particular nature of whose mutations, and the filter operated by natural selection, one wants to understand . . . (112-113)

Obviously, for Piazza, Moretti’s study of changes to and migrations of literary form in time and space evokes the processes and mechanisms of biological evolution—there’s not a one-to-one correspondence, of course, and Piazza points this out at length, but the similarities are evocative enough that he, a population geneticist, felt confident publishing his thoughts on the subject.

In Distant Reading, Moretti has more recently acknowledged that the intense data collection and quantitative analysis that has marked work at Stanford’s Literary Lab must at some point heed “the need for a theoretical framework” (122). Regarding that framework, he writes:

The results of the [quantitative] exploration are finally beginning to settle, and the un-theoretical interlude is ending; in fact, a desire for a general theory of the new literary archive is slowly emerging in the world of digital humanities. It is on this new empirical terrain that the next encounter of evolutionary theory and historical materialism is likely to take place. (122)

In Macroanalysis, Matthew Jockers also acknowledges (and resists) the temptation to initiate an encounter between evolutionary theory and the quantitative, diachronic data compiled in his book:

. . . the presence of recurring themes and recurring habits of style inevitably leads us to ask the more difficult questions about influence and about whether these are links in a systematic chain or just arbitrary, coincidental anomalies in a disorganized and chaotic world of authorial creativity, intertextuality, and bidirectional dialogics . . .

“Evolution” leaps to mind as a possible explanation. Information and ideas do behave in a ways that seem evolutionary. Nevertheless, I prefer to avoid the word evolution: books are not organisms; they do not breed. The metaphor for this process breaks down quickly, and so I do better to insert myself into the safer, though perhaps more complex, tradition of literary “influence” . . . (155)

And in the last chapter to Why Literary Periods Mattered, Ted Underwood does not mention evolution at all but there is clearly an evolutionary connotation to the terms he uses to describe digital humanities’ influence on literary scholars’ conception of history:

. . . digital and quantitative methods are a valuable addition to literary study . . . because their ability to represent gradual, macroscopic change brings a healthy theoretical diversity to literary historicism . . .

. . . we need to let quantitative methods do what they do best: map broad patterns and trace gradients of change. (159, 170)

Underwood also discusses “trac[ing] processes of change” (160) and “causal continuity” (161). The entire thrust of Underwood’s argument, in fact, is that distant or quantitative readings of literature will force scholars to stop reading literary history as a series of discrete periods or sharp cultural “turns” and to view it instead as a process of gradual change in response to extra-literary forces—“Romanticism” didn’t just become “Naturalism” any more than homo erectus one decade decided to become homo sapiens.

Tracing processes of gradual, macroscopic change . . . if that doesn’t invoke evolutionary theory, I don’t know what does. Underwood doesn’t even need to use the word.

Moretti, Jockers, and Underwood are three big names in digital humanities who have recognized, either explicitly or implicitly, that distant reading puts us face to face with cultural transformation on a large, diachronic scale. Anyone working with DH methods has likely recognized the same thing. Like I said, be honest: you were already thinking about this before you learned to topic model or use the NLTK.

 

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Human culture changes—its artifacts, its forms. This is not up for debate. Even if we think human history is a series of variations on a theme, the mutability of cultural form remains undeniable, even more undeniable than the mutability of biological form. Distant reading, done cautiously, gives us a macro-scale, quantitative view of that change, a view simply not possible to achieve at the scale of individual texts or artifacts. Given the fact of cultural transformation, then, and DH’s potential to visualize it, to quantify aspects of it, one of two positions must be taken.

1. The diachronic patterns we discover in our distant readings are, to use Jockers’ words, “just arbitrary, coincidental anomalies in a disorganized and chaotic world of authorial creativity, intertextuality, and bidirectional dialogics.” Theorizing the patterns is a fool’s errand.

2. The diachronic patterns we discover are not arbitrary or random. Theorizing the patterns is a worthwhile activity.

Either we believe that there are processes guiding cultural change (or, at least, that it’s worthwhile to discover whether or not there are such processes) or we assume a priori that no such processes exist. (A third position, I suppose, is to believe that such processes exist but we can never know them because they are too complex.) We can all decide differently. But those who adopt the first position should kindly leave the others to their work. In my view, certain criticisms of distant reading amount to an admonition that “What you’re trying to do just can’t be done.” We’ll see.

 

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When we decide to theorize data from distant readings, what are we theorizing? Moretti, Jockers, and Underwood each provide a similar answer: we are theorizing changes to a cultural form over time and, in some instances, space. Certain questions present themselves immediately: Are the changes novel and divergent, or are they repeating and reticulating? Is the change continuous and gradual, or are there moments of punctuated equilibrium? How do we determine causation? Are purely internal mechanisms at work, or also external dynamics? A complex interplay of both internal mechanisms and external dynamics? How do we reduce data further or add layers of them to untangle the vectors of causation?

To me, all of this sounds purely evolutionary. Even talking about gradual vs. quick change is a discussion taken right out of Darwinian theory.

But we needn’t adopt the metaphor explicitly if we are troubled that it breaks down at certain points. Alex Reid writes:

Matthew Jockers remarks following his own digital-humanistic investigation, “Evolution is the word I am drawn to, and it is a word that I must ultimately eschew. Although my little corpus appears to behave in an evolutionary manner, surely it cannot be as flawlessly rule bound and elegant as evolution” (171). As he notes elsewhere, evolution is a limited metaphor for literary production because “books are not organisms; they do not breed.” He turns instead to the more familiar concept of “influence” . . . Certainly there is no reason to expect that books would “breed” in the same way biological organisms do (even though those organisms reproduce via a rich variety of means). [However], if literary production were imagined to be undertaken through a network of compositional and cognitive agents, then such productions would not be limited to the capacity of a human to be influenced. Jockers may be right that “evolution” is not the most felicitous term, primarily because of its connection to biological reproduction, but an evolutionary-type process, a process as “natural” as it is “cultural,” as “nonhuman” as it is “human,” may exist.

An “evolutionary-type” process of culture is what we’re after, one that is not necessarily reliant on human agency alone. Will it end up being “flawlessly rule bound and elegant as evolution”? First, I think Jockers seriously over-estimates the “flawless” nature of evolutionary theory and population genetics. If the theory of evolution is so flawless and elegant, and all the science settled, what do biologists and geneticists do all day? Here’s a recent statement from the NSF:

Understanding the tree of life has been a goal of evolutionary biologists since the time of Darwin. During the past decade, unprecedented gains in gathering and analyzing phylogenetic data have demonstrated increasingly complex genealogical patterns.

. . . . Our current knowledge of processes such as hybridization, endosymbiosis and lateral gene transfer makes clear that the evolutionary history of life on Earth cannot accurately be depicted as a single, typological, bifurcating tree.

Moretti, it turns out, needn’t worry so much about the fact that cultural evolution reticulates. And Jockers needn’t assume that biological evolution is elegantly settled stuff.

Secondly, as Reid argues, we needn’t hope to discover a system of influence and cultural change that can be reduced to equations. We probably won’t find any such thing. However, within all the textual data, we can optimistically hope to find regularities, patterns that can be used to make predictions about what might be found elsewhere, patterns that might connect without casuistic contrivance to theories from the sciences. Here’s an example, one I’ve used several times on this blog: Derek Mueller’s distant reading of the journal College Composition and Communication. Mueller used article citations as his object of analysis. When he counted and graphed a quarter century of citations in the journal, he discovered patterns that looked like this:

muellerlongtail

Actually, based on similar studies of academic citation patterns, we could have predicted that Mueller would discover this power law distribution. It turns out that academic citations—a purely cultural form, a textual artifact constructed through the practices of the academy—behave according to a statistical law that seems to affect all sorts of things, from earthquakes to word frequencies. This example makes a strong case against those who argue that cultural artifacts, constructed by human agents within their contextualized interactions, will not aggregate over time into scientifically recognizable patterns.  Granted, this example comes from mathematics, not evolutionary theory, but it makes the point nicely anyway: the creations of human culture are not necessarily free from non-human processes. Is it foolish to look for the effects of these processes through distant reading?

 

4

“Evolution,” “influence,” “gradualism”—whatever we call it in the digital humanities, those of us adopting it on the literary and rhetorical end have a huge advantage over those working in history: we have a well-defined, observable element, an analogue of DNA, to which we can always reduce our objects of study: words. If evolution is going to be a guiding metaphor, we need this observable element because it is through observations of its metamorphoses (in usage, frequency, etc.) that we begin to figure out the mechanisms and dynamics that actually cause or influence those metamorphoses. If we had no well-defined segment to observe and quantify, the evolutionary metaphor could be thrown right out.

To demonstrate its importance, allow me a rhetorical demonstration. First, I’ll write out Piazza’s description of biological evolution found in his afterword to Graphs, Maps, Trees. Then, I’ll reproduce the passage, substituting lexical and rhetorical terms for “genes” but leaving everything else more or less the same. Let’s see how it turns out:

Recognizing the role biological variability plays in the reconstruction of the memory of our (biological) past requires ways to visualize and elaborate data at our disposal on a geographical basis. To this end, let us consider a gene (a segment of DNA possessed of a specific, ascertainable biological function); and for each gene let us analyze its identifiable variants, or alleles. The percentage of individuals who carry a given allele may vary (very widely) from one geographical locality to another. If we can verify the presence or absence of that allele in a sufficient number of individuals living in a circumscribed and uniform geographical area, we can draw maps whose isolines will join all the points with the same proportion of alleles.

The geographical distribution of such genetic frequencies can yield indications and instruments of measurement of the greatest interest for the study of the evolutionary mechanisms that generate genetic differences between human populations. But their interpretation involves quite complex problems. When two human populations are genetically similar, the resemblance may be the result of a common historical origin, but it can also be due to their settlement in similar physical (for example, climactic) environments. Nor should we forget that styles of life and cultural attitudes of an analogous nature (for example, dietary regimes) can favour the increase or decrease to the point of extinction of certain genes.

Why do genes (and hence their frequencies) vary over time and space? They do so because the DNA sequences of which they are composed can change by accident. Such change, or mutations, occurs very rarely, and when it happens, it persists equally rarely in a given population in the long run . . . From an evolutionary point of view, the mechanism of mutation is very important because it introduces innovations . . .

. . . The evolutionary mechanism capable of chancing the genetic structure of a population most swiftly is natural selection, which favours the genetic types best adapted for survival to sexual maturity, or with a higher fertility. Natural selection, whose action is continuous over time, having to eliminate mutations that are injurious in a given habitat, is the mechanism that adapts a population to the environment that surrounds it. (100-101)

Now for the “distant reading” version:

Recognizing the role lexical variability plays in the reconstruction of the memory of our (literary and rhetorical) past requires ways to visualize and elaborate data at our disposal on the basis of cultural space (which often correlates with geography). To this end, let us consider a word (a segment of phonemes and morphemes possessed of a specific, ascertainable grammatical or semantic function); and for each word let us analyze its stylistic variants, or synonyms. The percentage of texts that carry a given stylistic variant may vary from one cultural space to another, or from one genre to the other. If we can verify the presence or absence of that variant in a sufficient number of texts produced in a circumscribed and uniform cultural space we can draw maps whose isolines will join all the points with the same proportion of stylistic variants.

The distribution of such lexical frequencies can yield indications and instruments of measurement of the greatest interest for the study of the evolutionary mechanisms that generate lexical differences between “generic populations.” But their interpretation involves quite complex problems. When two rhetorical forms or genres are lexically similar, the resemblance may be the result of a common historical origin, but it can also be due to their development in similar geographic or political environments. Nor should we forget that styles of life and cultural attitudes of an analogous nature (for example, religious dictates) can favour the increase or decrease to the point of extinction of certain lexical items or clusters of lexical items.

Why do words (and hence their frequencies and “clusterings”) vary over time and space? They do so because of stylistic innovations. Such innovation occurs very rarely, and when it happens, it persists equally rarely in a given generic population in the long run . . . From an evolutionary point of view, the mechanism of innovation is very important because it introduces new rhetorical forms . . .

. . . The evolutionary mechanism capable of changing the lexical structure of a rhetorical form or genre most swiftly is cultural selection, which favours the forms best adapted for survival to publication and circulation, or with a higher degree of influence (meaning a higher likelihood of being reproduced by others without too many changes). Cultural selection, whose action is continuous over time, having to eliminate rhetorical innovations or “mutations” that are injurious in a given cultural habitat, is the mechanism that adapts a rhetorical form to the environment that surrounds it.

Obviously, it’s not perfect. I leave it to the reader to decide its persuasive potential.

I think the biggest problem is in the handling of mutations. In biological evolution, genes mutate via chance variations during replication of their segments; these mutations can introduce innovations in an organism’s form or function. In literary evolution, however, no sharp distinction exists between a lower-scale “mutation” and the innovation it introduces. The innovation is the formal mutation. This issue arises because, in literary evolution, as in linguistic evolution, the genotype/phenotype distinction is not as obvious or strictly scaled as it is in evolutionary theory. Words are more phenotype than genotype, unless we want to get lost in an overly complex evocation of morphology and phonology.

The metaphor always breaks down somewhere, but where it works, it is, I think, highly suggestive: the idea is that we track rhetorical forms—constellations of words and their stylistic variants—across time and space, in order to see where the forms replicate and where they disappear. Attach meta-data to the texts that constitute those forms, and we will have what it takes to begin making data-driven arguments about how cultural ecology affects or does not affect cultural form.

It’s an interesting framework in which distant reading might go forward, even if explicit uses of the word “evolution” are abandoned.

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Historical Linguistics and Population Genetics

Reich et al.  provide a model of two ancient populations in India that are ancestral to modern populations—Ancestral North Indians (ANI) and Ancestral South Indians (ASI). According to Reich et al, ANI is, on average, more genetically similar to Middle Easterners, Central Asians, and Europeans. ASI, on the other hand, is distinct from ANI as well as from East Asian populations. This same study found that “ANI ancestry ranges from 39–71% in most Indian groups, and is higher in traditionally upper caste and Indo-European speakers.” Furthermore, Reich et al. showed that the Indian caste system is old and historically implacable—high FST values indicate that “strong endogamy must have shaped marriage patterns in India for thousands of years.” This seriously contradicts the claims of Edward Said, Nicholas Dirks, and others who have argued that caste in India was more fluid and less systematized before British imperial rule.

However, a recent paper (Moorjani et al. 2013) does show fluid population admixture between Indian groups somewhere between 1,900 and 4,200 years ago.

Our analysis documents major mixture between populations in India that occurred 1,900 – 4,200 years BP, well after the establishment of agriculture in the subcontinent. We have further shown that groups with umixed ANI and ASI ancestry were plausibly living in India until this time. This contrasts with the situation today in which all groups in mainland India are admixed. These results are striking in light of the endogamy that has characterized many groups in India since the time of admixture. For example, genetic analysis suggests that the Vysya from Andhra Pradesh have experienced negligible gene flow from neighboring groups in India for an estimated 3,000 years. Thus, India experienced a demographic transformation during this time, shifting from a region where major mixture between groups was common and affected even isolated tribes such as the Palliyar and Bhil to a region in which mixture was rare.

As the researchers go on to indicate, ~2,000 to 3,000 years ago corresponds to the major transitions attendant to the end of the Harappan civilization and the influx of the Indo-Aryans. Can these genetic studies shed any light on the controversies of Indian language history?

Emeneau’s famous 1956 paper, “India as a Linguistic Area,” holds up reasonably well to contemporary scrutiny. The Indo-Aryan, Dravidian, and Munda language families have obviously influenced one another. Dravidian influence on Indo-Aryan is well attested. But this seems odd given the correlation, discovered by Reich et al. and others, between Indo-European speaking ancestry and upper caste status in India. Another population genetics study (Bamshad et al. 2001) puts it this way:

Indo-European-speaking people from West Eurasia entered India from the Northwest and diffused throughout the subcontinent. They purportedly admixed with or displaced indigenous Dravidic-speaking populations. Subsequently they may have established the Hindu caste system and placed themselves primarily in castes of higher rank.

These “Indo-European-speaking people” probably have something to do with Reich et al.’s Ancestral North Indians. But if these “invaders” were strong enough to admix with and displace the indigenous Dravidic-speaking populations, why does Emeneau find Dravidian influence on Indo-Aryan? Imagine Cherokee influencing English on the scale of 5%. It’s just not going to happen. Most linguistic history shows that dominant languages influence less dominant languages; the opposite rarely occurs, and if it does, its influence on the dominant language is minimal.  In another paper, Emeneau has this to say:

[There has long been the assumption] that the Sanskrit-speaking invaders of Northwest India were people of a high, or better, a virile, culture, who found in India only culturally feeble barbarians, and that consequently the borrowings that patently took place from Sanskrit and later Indo-Aryan languages into Dravidian were necessarily the only borrowings that could have occurred . . . It was but natural to operate with the hidden, but anachronistic, assumption that the earliest speakers of Indo-European languages were like the classical Greeks or Romans—prosperous, urbanized bearers of a high civilization destined in its later phases to conquer all Europe and then a great part of the earth—rather than to recognize them for what they doubtless were–nomadic, barbarous looters and cattle-reivers whose fate it was through the centuries to disrupt older civilizations but to be civilized by them.

Rather than the image of Indo-European “invaders” whose civilized power subjugated indigenous Indian populations, Emeneau instead imagines barbarians at the gates. Certainly, the language of nomads would be more socially susceptible to indigenous Dravidian, but how does this picture fit with the recent discovery of early population admixture? Would indigenous Dravidians have been more likely to breed freely with uncivilized nomads roaming and slowly penetrating the borderlands? Possibly.

Michael Witzel might have a different solution. The oldest Indian text following the actual Harappan script itself is the Rigveda, a collection of sacred Vedic Sanskrit hymns. Witzel finds in the earliest sections of the Rigveda several hundred lexical items and a few morphological features that are clearly not of Sanskrit (and therefore, not of Indo-European) origin. His analysis of these features leads him to believe that the language spoken before the arrival of Indo-Europeans—i.e., spoken in the Harappan civilization—was more closely related to the Munda languages and the Austroasiatic language family. In other words, Witzel’s analysis suggests that an Indo-European “invasion” and domination of indigenous Dravidian speakers is probably not an accurate historical picture. A sacred Indo-European text like the Rigveda would not contain so many non-IE loanwords if its speakers had entered the scene as dominant bringers of hierarchy. And given that the non-IE loanwords and morphological features are more likely Austroasiatic than Dravidian, Witzel envisions a time when Indo-European speakers and Dravidian speakers immigrated slowly into Harappan civilization, neither dominant invaders nor barbarous raiders. This would explain the cross-linguistic influence in the Indian subcontinent. It would also explain Moorjani et al.’s recent paper showing major mixture between groups in India prior to the rise of the caste system several thousand years ago.

Or maybe not. Witzel’s theory is not well accepted among historical linguists. And if Indo-Aryan and Dravidian immigration was so gradual and perhaps even egalitarian (Witzel imagines that Harappan urban centers may have been trilingual), from whence came a caste system that so clearly favors one ancestral group over the others? And there’s a nagging question about timing: one study suggests that Reich’s ANI might not fit within the purported timeline of Indo-European speakers’ migration. There’s also the issue of linguistic distribution. Razib Khan notes:

It seems an almost default position by many that the Austro-Asiatics are the most ancient South Asians, marginalized by Dravidians, and later Indo-Europeans. I would not be surprised if it was actually first Dravidians, then Austro-Asiatics and finally Indo-Europeans. Dravidians are found in every corner of the subcontinent (Brahui in Pakistan, a few groups in Bengal, and scattered through the center) while the Austro-Asiatics exhibit a more restricted northeastern range.

It’s all quite messy, but my point is that linguists interested in language contact and linguistic evolution should be reading work in population genetics, too. Papers on population genetics often reference work in historical linguistics; however, I rarely see historical linguists citing population genetics.

Humane/Anti-Humane

Though he doesn’t state it directly, Timothy Burke recognizes that humanistic inquiry circa 2013 is at risk of being subsumed—enfolded into—techno-scientific discourse and scrutiny. In many venues, as he notes, it has already been subsumed:

I would not call such views inhumane: more anti-humane: they do not believe that a humane approach to the problems of a technologically advanced global society is effective or fair, that we need rules and instruments and systems of knowing that overrule intersubjective, experiential perspectives and slippery rhetorical and cultural ways of communicating what we know about the world.

The anti-humane is in play:

–When someone works to make an algorithm to grade essays

–When an IRB adopts inflexible rules derived from the governance of biomedical research and applies them to cultural anthropology

–When law enforcement and public culture work together to create a highly typified, abstracted profile of a psychological type prone to commit certain crimes and then attempt to surveil or control everyone falling within that parameter

–When quantitative social science pursues elaborate methodologies to isolate a single causal variable as having slightly more statistically significant weight than thousands of other variables rather than just craft a rhetorically persuasive interpretation of the importance of that factor

–When public officials build testing and evaluation systems intended to automate and massify the work of assessing the performance of employees or students

At these and many other moments across a wide scale of contemporary societies we set out to bracket off or excise the human element , to eliminate our reliance on intersubjective judgment. We are in these moments, as James Scott has put it of “high modernism”, working to make human beings legible and fixed for the sake of systems that require them to be so.

That humans can be quantified and their behaviors inserted into mechanistic or, more recently, statistical models is an idea as old as Comte and Spencer. Humanists of all stripes, religious and secular, have long denounced this idea, but with each passing decade, their denunciations have been met with more and more techno-scientific intrusions into the venues of humanistic inquiry. Researchers in China are currently attempting to map the genetic architecture of human intelligence itself; natural language processors are attempting to teach computers to learn human languages; and researchers across a wide array of disciplines continue to produce research which suggests that all life—human life included—is essentially “a mixture of genes, environment, and the accidents of history.

E.O. Wilson’s Sociobiology may have been problematic in tone and too over-confident, but its underlying idea—that everything human and humane will eventually be describable in techno-scientific terms—is as valid as ever. Kurzweil is far too optimistic about the speed of transhuman advancement, but if history has shown us one thing, it’s not to bet against scientific advancement. And if we do build a sentient machine or use machines to amplify the abilities of humans (aren’t we doing this already?), then what else can we conclude but that humanity can be meaningfully reduced to techno-scientific terms?

Timothy Burke writes that “a humane knowledge accepts that human beings and their works are contingent to interpretation,” but some interpretations are more productive than others. Western science may be a reductive way-of-knowing, and techno-scientific reductionism may be a tough interpretation for humanists to find value in, but in the post-Enlightenment marketplace of ideas, anti-humane knowledge has always been and will continue to be the driver of discourse. Why? It produces. Its material applications are powerful.

Most of Burke’s essay is nuanced and generative, but he concludes with a bit of a rhetorical flourish that undermines the continuing material productivity of science:

We might, in fact, begin to argue that most academic disciplines need to move towards what I’ve described as humane because all of the problems and phenomena best described or managed in other approaches have already been understood and managed. The 20th Century picked all the low-hanging fruit. All the problems that could be solved by anti-humane thinking, all the solutions that could be achieved through technocratic management, are complete.

If by “anti-humane thinking” Burke means a purely mechanistic view of humanity, then he’s probably right. However, no one holds such a view anymore, if they ever did. For example, machine learning is modeled on statistical probabilities, and genetic research is looking at complex polygenic and epigenetic effects that are not reducible to single gene tinkering. The techno-scientific lens is no longer mechanistic or averse to complexity, but I still get the feeling that it remains “anti-humane” in the eyes of many humanists.

The worst thing the humanities can do is to continue theorizing about how its subject matter simply cannot be subsumed by techno-scientific practice while its subject matter continues to be subsumed by techno-scientific practice. We need to stop talking about, say, “the social construction of gender and sexuality” as though representation and discourse were more important for understanding gender and sexuality than hormone therapy or the biology of same-sex reproduction. Too often, humanists confuse ethical critique with epistemology. In my opinion, instead of assuming that our areas of inquiry are by definition off-limits to the techno-scientific lens, we need to recognize that the humanities are indeed “incomplete” without recourse to the knowledge of science. We should cross the border into the Land of Techno-Science more often . . . . for this sets up an encounter in which the sciences will recognize that they, too, are “incomplete” without recourse to the knowledge of humane inquiry. Every discipline has its deflections.

True incommensurability is rare. I’m confident that reading, e.g., E.O. Wilson and Donna Haraway together could be productive—so long as neither work remains unchanged in the encounter. The encounter would not be about whose knowledge gets to be the base of the other’s, or whose knowledge anchors the other’s. Rather, the point of such a humane/anti-humane encounter would be to give birth to an epistemological offspring comprised of elements from both but resembling neither.

Building a Chinese Room

Chomsky isn’t a fan of statistical machine learning. However, this video (via Steve Hsu) suggests that using Really Big Corpora is the best way to get machines to figure out how language works, both structurally and–as the video shows–phonetically and acoustically.

Around six minutes in, the demonstration begins. The speaker’s words are translated almost instantaneously into Chinese, and the auditory output sounds somewhat similar to the speaker’s actual voice. There are obviously Chinese speakers in the audience, and their response suggests that the demo was successful.

This video is a good example of the ways that computer scientists (and I include researchers in natural language processing in that category) are operating squarely in the realm of the humanities–what’s more humanistic than language translation? There have been tomes and manifestos written unto its spiritual, social, epistemological, and theoretical nature. And now computers are getting the hang of it. We humanists ignore their successes at our peril.

The Pareto distribution of native American language speakers

My post about native American language health gets the most hits on this blog, so I decided to do some minor editorial housekeeping on it last night. While I was fixing awkward syntax, however, I noticed something blatantly obvious about the first graph, which ranks living native languages according to most speakers:

LangRank1

It’s essentially a Pareto distribution, a long tail. I don’t know much about the mathematics underlying it. I only know that it arises naturally across an array of social, geographic, economic, and scientific phenomena. Derek Mueller recently wrote an article about this exact distribution amongst scholarly citations in the field of rhetoric and writing. “Conceptually,” he writes, “the long tail comes from statistics and graphing; it is a feature of a power law or Pareto distribution—graphed patterns that underscore the uneven distribution of some activity or phenomenon” (207). And yet this unequal distribution exists in phenomena as disparate as citations in academic journals and numbers of language speakers.

A power law writ deep in the mathematical fabric of things?