Reading Machines: Toward and Algorithmic Criticism

2. Potential Literature

2 POTENTIAL LITERATURE The word “algorithm” is an odd neologism. Most scholars now believe that the word relates back to the word “algorism,” which is in turn a corruption of the name of the Persian mathematician al-Kwārizmī from whose book, Kitāb al-jabr wa’l-muqābala (“Rules for Restoring and Equating”), we get the word “algebra” (Knuth 1). Throughout its varied history, the term has more or less always borne the connotation of a method for solving some problem, and, as the early slide from sibilant to aspirate would imply, that problem was most often considered mathematical in nature. During the twentieth century, however, the word “algorithm” came to be associated with computers—a step-by-step method for solving a problem using a machine. To speak of algorithms is therefore usually to speak of unerring processes and irrefragable answers. If computational methods are to be useful in the context of literary study, however, we must consider the use of algorithms loosed from the strictures of the irrefragable and explore the possibilities of a science that can operate outside of the confines of the denotative. Historically, such ventures have been viewed with deep distrust: The rise of scientific logic seems, indeed, to have had the effect of pushing back the ever-encroaching forces of dialectical invention into the margins of charlatanism and mental tricks. Descartes’s position was clear: he insisted on clarity against quackery. . . . In the new scientific age, rhetoric’s calculating genius seemed antithetical to the search for truth. Rhetoric’s technologies were too random, its underlying ethos too inauthentic and artificial to contribute to a reliable description of man and the world. (Bold 544) Potential Literature 19 The Cartesian legacy, in addition to valorizing science as the sine qua non of human inquiry, had the additional effect of validating the Athenian senate ’s perception of philosophy as “making the weaker argument defeat the stronger” (Plato 5). Today, “rhetoric has been shown to be at the basis of what is called scientific ‘method’ in all but the Cartesian sense of the word,” and yet the separation of these two faculties has persisted, and the trace of this once bitter opposition maintained (Bold 544). The reverberations of this divergence are evident in the computing humanist ’s ironic distrust of inventions borne of algorithmic processes. Few commentators, in fact, have been able to resist framing the movement from data to interpretation as one fraught with peril. Hugh Craig, an expert in stylometry and authorship attribution, is unusually candid in an assessment that bears the subtitle, “If You Can Tell Authors Apart, Have You Learned Anything about Them?” The leap from frequencies to meanings must always be a risky one. The interpreter who is tempted to speculate about the world-view or psychology of a writer, based on quantitative findings, presents an easy target for dismissive critique (Fish, 1973). On the other hand, staying within the safe confines of the statistical results themselves means that one is soon left with only banalities or tautologies. Lower-level features are easy to count but impossible to interpret in terms of style; counting images or other high-level structures brings problems of excessive intervention at the categorization stage, and thus unreliability and circularity (Van Peer, 1989). (Craig 103–4) Thus “quantitative findings” emerge, under the cultural burden of science, as entirely opposed to the imaginative work of speculation and intervention. The age-old charges against inventio reemerge. Without grounding in the language game of denotation, we risk the “circular reasoning” of a discourse that grounds itself in further discourse—the “unreliability” of a claim that has nothing to recommend it but its rhetorical power to persuade. Larger debates are aliased through Craig’s ingenuous observations about risk, and those debates largely ignore the conundrum he identifies. C. P. Snow’s 1959 Rede Lecture, “The Two Cultures and Scientific Revolution”—often cited as having put forth the essential terms of the debate between science and the humanities—figures the dichotomy as a kind of misunderstanding. If literary intellectuals (whom Snow refers to as “natural Luddites”) would learn more about science and scientists would learn more about “imaginative experience ,” we would not only enrich the episteme of academic culture, but we would also go further toward communicating the meaning of that culture to the larger world (23). But what to do with a scholar like Craig, who is as- 20...