Prophecy and Computation
Rachel Baker has tuned me into an interesting vein of thought with one of her points made during her “Prophecy Workshop” (which prefaced the ‘Three Keys’ game in Furtherfield), one which I will attempt to unpick here.
The Omen movement of ‘Moving Forest’ and indeed the Macbeth play presents fertile ground for speculation. Rachel’s take, as she has ventured to me thus far is that the Witches were engaged in advanced social engineering, and that they leveraging the informal knowledge networks that circulated within the castle to ‘game’ Macbeth’s personality flaws. This is an interesting take if one leaves aside the accuracy of their predictions, which I’m content to do given my recent conclusions that prophetic directions delivered face to face are likely to be as potent as hypnotic suggestion.
Rachel and I met at AND Festival 2011, which had belief as it’s overarching theme, and we both had something to offer when considering how belief worked among the stock traders of the Market. There’s a great, in depth, article written on affect (understood as powerful intensities inhering between bodies and evincing effects on an a-conscious level) by Couze Venn which includes an exposition on the efficacy of brokers understood on an affectual scale: they speak of a feel for the market, something more akin to gut instinct and intuition, a skill which is bootstrapped onto the algo-trading algorithms which are the tools of the trade. This meeting is a potent, and dangerous, mix.
So it piqued my interest to see the fruit of Rachel (and her collaborator Kayle Brandon)’s work on Prophecy and Omen, manifest in the Three Keys game work over the weekend, and to see that among the domains by which one could stage a siege of their personal castle was the ‘feral’ realm.
Feral is defined within “Three Keys” as “children, escaped, reverted, regression, revolt, descended, detach, semi-wild, pest, stray, return, instinct, non-status, waste-land, ruin, deserter”
Feral stood apart from the two related domains of ‘domestic’ and ‘wild’, carrying with it the suggestion of something domesticated returning to nature, red in tooth and claw. Feral as a buzzword acquired a great deal of currency this year, being used to describe the rioters who tore London asunder in August and also used as a moniker for the risk-taking bankers (and those in power who shield them). Similarly this year we saw Kevin Slavin pronounce that algorithms are nature, and thankfully James Bridle highlighted the concept beyond a zippy way of concluding a TED Talk via reference to a Next Nature article.
Intentionality separates culture from nature. A dog is intentional, a fox is not; a park is intentional, a forest is not. Since trash, ruined buildings, and automated computer programs are unintentional, they are also a type of nature
It’s always notable when language spirals around topics, sticking to certain concepts and not others. What are we to make of ‘Feral Bankers’ and algorithms as force of nature? At the very least our entanglement with them is causing effects that noone can ignore.
It’s here that one of the well worn tropes by which Macbeth is understood is quite useful, a trope noted by Kayle. One can consider the conclusion of Macbeth, where a forest moves against an usurper as indicative of the natural order reversing itself to rid itself of an abberation. I’m going to avoid treading too far down that path as it lends itself to a problematic idea of self regulating systems righting themselves. Let’s instead look to Macbeth’s perspective. He placed his belief in a system (prophecy) that seemed utterly watertight: within the limits of what he could comprehend there was NO WAI a forest could move, much less a ‘man not of woman born’ could slay him. (He wasn’t to know how much prophecy loved irony). But the important point is that Macbeth acted in the same way as all humans do when faced with a system, which when understood in terms of it’s output seems clear cut and transparent in terms of what it will afford them.
Which brings me close to a theory which I gather is prevalent but also unpopular: that globalization (and the attendant increase in complexity) and the increased reliance on automated trading in the aforementioned deregulated market meant that no one set of actors was really to blame in the 2008 Credit Crunch. That ultimately it was human arrogance, or more kindly blind spots, in the face of significant non-human agencies that was our undoing. And what’s even better is that the answer to this is most certainly not less entanglement with non-human agencies, see this forecast on the four imminent grand challenges of computation:
The complexity of many human endeavors, – including medical diagnoses, financial advice, formulating business strategy or setting government policies, – has outgrown our ability to make good decisions on our own. (Cognitive Computing) represents a natural next step in the history of human progress: the development of better and better tools to help us deal with the increasingly complex world around us.