0.4 What is cultural economy?  (Page 6/6)

While Poon and I would surely disagree about many things —she is interested in the formal properties of technical systems, not “grander” themes like liberalism—Poon and I are engaged in projects more alike than different. Both of us, for example, want to understand how elements of the financial infrastructure have been naturalized—how they have been built into the financial system in ways that make it impossible for individual actions to counteract them. No individual’s actions can be either “heroic” or decisively “villainous” because no individual can act outside the system that is increasingly tightly organized by both the (economic) assumption that financial interconnectedness is algorithmically rational and the tools (like the FICO scores) that make it so.

Integrating projects like Poon’s and mine into the existing array of academic disciplines will be difficult. As I suggested above, method poses an enormous challenge. Typically, the social sciences take their methodological clues from the sciences, and, even when social scientists like Poon focus on the social construction of entities such as the calculative apparatus of credit scores, the goal is to produce a description that is as accurate—and, by implication, as objective—as possible. In the humanities, which have long emphasized interpretation, objectivity is rarely embraced as the primary outcome. Because most humanists’ objects of analysis derive their identity from a degree of indeterminacy, moreover—they cultivate ambiguity as part of their identity as aesthetic objects—an analyst’s ability to generate an accurate description is either merely a first step toward interpretation or entirely beside the point. As long as social scientific and humanities disciplines define their enterprises in opposition to each other, their methodologies will continue to pull in opposite directions; and, as long as this is the case, it will be difficult for disciplinary curricula to absorb more than a few outlying courses that depart so radically from the disciplinary norm.

But the greatest challenge to any effort to incorporate cultural economy into existing academic curricula emanates from the role mathematics now plays in the discipline of economics. Even though economists did not embrace mathematics until the 1970s, mathematics is now central to economics and to the subdiscipline of financial economics. Pick up any advanced textbook on finance or investing, and the first thing you will see are mathematical equations. The problem posed by the centrality mathematics now assumed in financial economics is not that people who are good at description and interpretation are rarely good at math. The problem is that a deterministic mathematical model, which is what equations are, has to make several assumptions in order to claim that equations are relevant to the real world of finance. The first assumption of mathematical modelling is that real-world examples can be captured by a financial type (x); this removes any anomalies that might make the real-world instance unpredictable. Second, mathematical modelling assumes that future events will repeat past events and that any event that does vary from past events is a one-off (thus irrelevant) departure from the norm. Third, it assumes that markets are rule-governed—that is, efficient (that they enjoy perfect liquidity, infinite credit, and no counterparty risks). All of these assumptions can be summarized thus: mathematical models assume—and produce—abstract space, not the complex, probabilistic, socio-historical, and self-reflexive world where real-life events, including financial events, occur. Thanks to Edward LiPuma for formulating these points about mathematics. Private electronic correspondence. It is difficult to see how a discipline that embraces mathematics in order to gain legitimacy as a science can ever be incorporated into any other discipline that seeks to understand—whether through description or interpretation—the anomalies that socio-historical conditions generate. As one Wall Street trader put it when home foreclosures began to mount: “You cannot model human behavior with mathematics. There’s no computer model that will ever tell you whether someone will pay their mortgage. And there never will be. The risk will always be there. You cannot calculate it. Risk and reward are beyond the intellectual limits of a computer.” Lawrence G. McDonald, A Colossal Failure of Common Sense: The Inside Story of the Collapse of Lehman Brothers (New York: Crown, 2009), 134.

At most, I think, any instances of cultural economy, the social study of finance, or whatever we decide to call it will appear at the boundary that separates the humanities and the social sciences. As long as the present configuration of the disciplines obtains, individuals who practice economics (most of whom aspire to be called scientists, not social scientists and certainly not humanists) will have little respect for this emergent enterprise—even if it helps humanists, social scientists, and the larger population understand the complex ways that financial systems affect our lives.