Felix Stalder on Mon, 1 Apr 2019 12:29:53 +0200 (CEST) |
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Re: <nettime> Managing complexity? |
On 30.03.19 21:19, Brian Holmes wrote: > However, the surging sense of intellectual mastery brought by the > phrase, "managing complexity," declines precipitously when you try to > define either "management" or "complexity." Complexity is relatively easy to define. As Jospeh Rabie already did, the number of actors and the number of ways in which they can interact with, and adapt to, one another defines the complexity of a "system". This, of course, leads to the question how to determine the size of the system. The first generation of cybernetics gave another answer to that question than the second, as Ted pointed out. Prem's suggestion that we are dealing with polycentric systems is certainly right and makes it both easier and harder to define the number of actors that make them up. Easier in the sense that it puts the focus on densities and rates of interaction (higher at the center, lower at the periphery) rather than on precise, yet elusive boundaries. Harder in the sense that it stresses that each system contains numerous such centers, shifting the problem from drawing boundaries to deciding the inclusion/exclusion of centers. Be that as it may. Let's assume that the number of actors and the ways of interacting have increased over the last, say, last 70 years. More important than the simple number of actors (which is hard to ascertain anyway) is that the ways in which they are interacting has increased, leading to an exponential, rather than linear rise on complexity. In my view, there are a number of reasons for this. * The chains of interactions have grown longer. Many (social and ecological) systems used to be relatively local phenomena have become global ones (as a consequence of the expansion of capitalism as globalization). * The intensity of interaction has been increasing (as a consequence of the intensification of capitalism), taking many systems away from "steady states" closer to the edge of "phase-transitions" (to use the terminology from complexity theory). In this process, these systems become more and more non-linear, increasing the need to understand their internal dynamics (e.g who are the actors and how are they interacting) while at the same time, making them less predictable. * The social institutions that have traditionally limited the ways of interaction by providing and enforcing rules and norms have weakened, further increasing the leeway for agency (which, of course, not all bad). Not knowing where to draw boundaries, or which centers are relevant to the understanding of the system, is a part of the problem of not being able to "manage" the many actors and their increasing ranges of interaction and the predictable effects of their interactions. By "managing" I initially simply meant the ability to track the actors that make up the system and the ability to intervene in the system to move it towards desired states. This is a somewhat technocratic view, I admit. Joseph Weizenbaum argued in the 1970sthat the computer was introduced as an answer to the social pressures which large corporations and government agencies faced. Rather than accept social change, the new computing infrastructure was putting central management on a new footing. It could now keep track of many more elements and react much faster to changes in the environment by reorganizing quickly the relation of the elements to one another. This was, basically, the shift from Fordism to Post-Fordism and by definition an increase in complexity that came, as it always comes, at the price of an higher rate of abstraction as a way of limiting that increase of complexity (a lower number of variables per element are taken into account). For similar reasons, I think, the shift towards markets and quantitative signals (prices, ranking, indices etc) was so successful. It allowed to manage the increase in social complexity by abstracting it away. I think both systems (computers and markets) as ways of managing complexity are reaching an upper limit, mainly because an ever increasing number of actors are no longer conforming to their abstractions (by exhibiting dimensions that we deemed irrelevant in the process of abstraction, or by not behaving according to the models etc.). These are not problems of implementation for technical limits to be overcome by progress, but fundamental limitation of the these two systems of abstraction/management. Not everything can be expressed as a price. Even economists are now arguing again about the difference between value and price. For neo-liberals, is the same: the value of a thing is whatever somebody is willing to pay for it, and therefor it cannot be too high or too low. On 31.03.19 15:50, Prem Chandavarkar wrote: > AI systems do not sit well with consciousness, for AI makes its > decisions on the basis of statistical correlations derived from > computing power, and not on the basis of consciousness. AI systems run > into problems difficult to foresee or comprehend once the decision > process gets detached from sentient consciousness, especially when the > AI system encounters non-linear contexts. Exactly! And this is a good indicator as to way the systemic crisis is now. Which leads back to the "management" question. Management, with its bureaucratic/cybernetic control approach is probably the wrong way to think this anyway. Because this is already getting way too long, I simply paste more of Prem's excellent bullets here, not the least as a reminder to myself to think more in this direction. On 31.03.19 15:50, Prem Chandavarkar wrote: > ‘Management’ and ‘complexity’ do not fit well in a polycentric system, > for management is an activity where one intervenes in order to control > output, and in a polycentric system, it is almost impossible to > ascertain with precision the impact of any intervention. > To live with complex systems we must allow them to be > self-organising. This is the argument used in the argument for free > markets, falling back on Adam Smith’s metaphor of the ‘invisible > hand’. > However, self-organising systems are emergent - they can > exhibit fundamental properties that did not exist at all in an > earlier state of the system. As humans, we cannot be blind to what > properties may emerge, unless we say we have no ethical concerns at > all if the system throws up properties such as unfair and degrading > exploitation of others or ecological imbalances. All the best. Felix -- |||||||||||||||||||||||||||||||||||||||| http://felix.openflows.com |Open PGP http://pgp.mit.edu/pks/lookup?search=0x0bbb5b950c9ff2ac
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