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Expectations in the fitness landscape

Lebanese-American scholar Nassim Taleb has developed the concept of a Black Swan to describe events that lie outside the realm of regular expectations. For Taleb, these events are disruptive, as they could not have been predicted prior to their occurrence. He presents such events as outliers. Only after their unexpected occurrence are we able to post-rationalize and define a new system of expectations that includes them. When describing a Black Swan event,Taleb writes;

First, it is an outlier, as it lies outside the realm of regular expectations, because nothing in the past can convincingly point to its possibility. Second, it carries an extreme impact.Third, in spite of its outlier status, human nature makes us concoct explanations for its occurrence after the fact, making it explainable and predictable.21

Building upon Taleb’s ideas, philosopher Elie Ayache has further developed three different understandings of the Black Swan concept defined by Taleb. As he explains:

Of the three different sources of Black Swans that Taleb describes in his book:

  • (1) the Black Swan that is inherent in our genes and in our evolutionary blindness to extreme events (I have always disliked naturalized epistemology),
  • (2) the Black Swan, or rather the Gray Swan, that is the result of mistaking the Gaussian probability distribution of Mediocristan for what should be, “in reality,” the scalable laws of Extremistan (I will come to that below) and
  • (3) the Black Swan that cannot possibly be predicted because it falls beyond knowledge and probability (that is to say, it falls beyond the given range of possibility), I retain the third as the philosophical one (therefore worthy of my attention). The other two are either merely anthropological or disappointingly metaphysical.22

From a parametric perspective, design could be understood as a Black Swan event that exists within a fitness landscape. The parametric interpretation of form finding follows Ayache’s first model: an optimistic expectation that a Black Swan (equated to an optimal design) is a highly improbable combination of parameters yet perfectly possible within the fitness landscape. Design, from this perspective, could be seen as a search protocol that seeks for performative data configurations within a large universe of possibilities. The ability to intuitively navigate such a landscape is regarded as talent in designers, but this also opens the door for algorithmic processes such as artificial intelligence which in recent years has become increasingly good at mimicking humans at the moment of selecting data patterns.

Ayache’s third approach offers a radically different model: he suggests that a Black Swan lives in a completely different plane, one oblique to the system of expectations defined in the possibility space parameters.23 This model suggest that a parametric model should always be considered potentially incomplete, unable to register the true domain of the problem. Taking this idea further, it is possible to understand these parametric models as a form of rhetoric that persuasively defines a domain as a justification of outcomes. The problem of the Black Swan in design offers a window into the value proposition of architects, where the rhetoric of a vast (yet incomplete) possibility space is systematically explored in order to find heroic outliers. The brilliance of the parametric model, as a rhetoric device, has been the construction of a possibility space constituted by 99% of virtual waste that only serves as an alibi for final proposals.

A productive understanding of the notion of Black Swans in design relies on understanding inherited blind spots in our system of expectations and advocates for reinvigorating our skepticism over rhetorical models such as parametric optimization. For Ayache, the third form of Black Swan he describes should follow a different name; he calls it a “Blank Swan.” As he explains:

The Black Swan is the perfectly unexpected event; the White Swan is the perfectly expected event. Underlying both is the category of prediction and prevision, which is the real object of my criticism. The Black Swan refers to something we cannot see or foresee (it is black) and the White Swan to something evident and clear. Although opposed, the two are predicated on the idea of content of vision, or content of mind, or content of expectation.

What if we completely eliminated the content of vision, i.e. both the colours White and Black? What if we eliminated the whole context of colour and of content? Hence the BLANK Swan.24

For Ayache, the Black Swan is an outlier but still bound to the solution space; the Blank Swan, on the other hand, defies such a system altogether. It is possible to interpret this as just some missing parameter in a parametric model; the unexpected event provides an update of new variables that need to be considered in order to develop a prediction. This misses the point. Ayache develops the notion of contingent claims to argue for events that acquire meaning and value only once they are written or committed into operation. This means that no post-rationalization of the Blank Swan will be able to conform it back to the parametrized solution space and conform it to a fitness landscape. Ayache argues that events such as writing or the process of pricing the market are events that do not emerge from a probability.2’ This also applies to architectural design, and particularly to a critical analysis of how computational tools embed an attempt to anticipate and deny the expression of contingent cultural values.

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