Studies of technical practices have done much to show the human labor and decision making that is involved in making financial models.  Human beings as sense makers participate in making science and technology.  In so doing, scientific and technological things take on a local flavor – they are made by and adapted to the specific circumstances of their makers. [Human factor A]

There is, however, another ‘Human Factor’ that matters in model making, one that is never far from, but has been less discussed in our field.  This NYTimes article suggest that recent economic events are “an implicit indictment of the arcane field of financial engineering” for not recognizing that human behavior is intrinsically (or so the argument goes) difficult to model. [Human Factor B]

This proposition strikes at the heart of an epistemological question that the social sciences share:  Is it possible to model human activity, and if so, how?  The question is biting.  It means that the plausibility of quantitative finance is the same as that of the sciences of the social.

For all intents and purposes the article concludes that the solution to the failure of models is to make them better.  This has also been the solution of the traditional social sciences, who express their attentiveness to the issue of the Human Factor [B] through a constant concern over methodology.

The Human Factor [B] seems to naturalize the qualities of humans and make them somewhat rigid.  Yet, it is noteworthy that arguments about engineering and performativity would suggest just as the properties of the physical world can change depending on where and how science is done, so can human beings.  Here, we are back to a softer version of the human as a mutable creature that can be designed and changed.

Indeed, as much activity economic or otherwise shows there are clear patterns in the world that emerge through the interlocking of humans and apparatuses – i.e. we may not know the outcome of the election in advance but the winner will be either Obama or McCain; i.e. the markets may be volatile but they only respond in two ways, up or down.  These patterns are not deterministic, yet, even though the outcome of contingent processes, they are nevertheless, real.

The question then is: Is it possible that quantitative financial models of consumer default risk participated in building a marketplace in which human agents with an increased likelihood of default on their loans were created, even if these models were not themselves able to predict this behavior as an outcome…? Hmmm. I wonder.

See this NYtimes article for an example of emerging and ongoing construction of justifications for the AIG bailout.  The content of the claims for why AIG and not Lehman?  Goldman Sachs and the London unit.

Note the different qualities of the arguments mixed in the same piece.

With regards to Goldman, there is more than a whiff of the classic accusation – powerful interests with ties to important people.

  • “The only Wall Street chief executive participating in the meeting was Lloyd C. Blankfein of Goldman Sachs, Mr. Paulson’s former firm. Mr. Blankfein had particular reason for concern. / Although it was not widely known, Goldman, a Wall Street stalwart that had seemed immune to its rivals’ woes, was A.I.G.’s largest trading partner, according to six people close to the insurer who requested anonymity because of confidentiality agreements. A collapse of the insurer threatened to leave a hole of as much as $20 billion in Goldman’s side, several of these people said.”

The involvement of the London unit takes on a technical flavor, having to do with dynamics of financial contracts, accounting and the firm’s organization.

  • “Because the London unit was set up as a bank and not an insurer, and because of the way its derivatives contracts were written, it had to put up collateral to its trading partners when the value of the underlying securities they had insured declined. Any obligations that the unit could not pay had to be met by its corporate parent. / So began A.I.G.’s downward spiral as it, its clients, its trading partners and other companies were swept into the drowning pool set in motion by the housing downturn.”

Powerful interests or systemic risk?  The article explores the tension but gives no verdict.  If anything it tends towards a hybrid justification where the two are interrelated.

  • “Yet an exploration of A.I.G.’s demise and its relationships with firms like Goldman offers important insights into the mystifying, virally connected — and astonishingly fragile — financial world that began to implode in recent weeks.”

Check out this article  by the NYTimes featuring an Implode-O-Meter set up by a former computer scientists and mathematician at Emory University.  The site is designed to measure and make visible the ‘misery in the housing market’.  According to the article: 

“The Implode-O-Meter is just the latest iteration of online death-watch lists. When the dot-com bubble burst, a slew of similar sites popped up, most notably one with an obscene name playing off the title of Fast Company, the magazine. That site and others like it faded when the technology company blowups were no longer front-page news.”

Is this an example of what Callon means when he says that all types of scientists (not just economists) can and do build tools that participate in the constitution of market events…?