Politics as statistical learner

January 31, 2022 — February 17, 2022

collective knowledge
ethics
institutions
learning
life
mind
probability
statistics
statmech
Figure 1: A Centrifugal Governor, the origin point both of cybernetic theory and signal processing thanks to James Clerk Maxwell’s analysis.

In mind-as-ml I wondered whether statistical learning models can give us insight into the individual human mind. Here I wonder if we can learn anything about humans en masse from statistical analogies. Probably, since this spans Herbert Simon’s interests, I should be ransacking his work more thoroughly.

1 Greedy algorithms as pragmatism

Contrast with utopian ideals as analytic solutions.

2 Game theory

Institutions and adversarial robustness.

3 Learning agents

See sociology of information.

4 Federated learning

5 Machines of loving grace

The cybernetics folks. Politics as operations research. Insert Adam Curtis documentary here, and a brief history of Operations Research.

TODO: Mention Pigs for the Ancestors, and the Water Temples (Lansing 2000; Rappaport 1967; Sage 2013).

6 Loss functions and public risk aversion

Which experiments do we permit the state to do?

Figure 2

7 Legibility and labelled data sets

Which census category do you fit in and which benefits do you reap thereby? Affirmative action, Trans-exclusionary Radical Feminists etc.

8 Evolutionary learning in institutions

9 Dimension reduction of politics

See political axes

10 References

Apicella, and Silk. 2019. The Evolution of Human Cooperation.” Current Biology.
Barkow, Cosmides, and Tooby. 1995. The adapted mind: evolutionary psychology and the generation of culture.
Bieniawski, and Wolpert. 2004. Adaptive, Distributed Control of Constrained Multi-Agent Systems.” In Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems-Volume 3.
Lansing. 2000. Foucault and the Water Temples: A Reply to Helmreich.” Critique of Anthropology.
Leibon, Pauls, Rockmore, et al. 2010. “Statistical Learning for Complex Systems an Example-Driven Introduction.”
Newell, and Wasson. 2002. “Social System Vs Solar System: Why Policy Makers Need History.” In.
Rappaport. 1967. Pigs for the Ancestors : Ritual in the Ecology of a New Guinea People.
Rosicky. 2001. “Information and Social Systems Evolution.” In.
Sage. 2013. Cybernetics and Complex Adaptive Systems.” In Encyclopedia of Operations Research and Management Science.
Simon. 1962. “The Architecture of Complexity.” Proceedings of the American Philosophical Society.
———. 1996. The Sciences of the Artificial.
Sornette. 2009. Dragon-Kings, Black Swans and the Prediction of Crises.” arXiv:0907.4290 [Physics].
Sornette, and Cauwels. 2015. Managing Risk in a Creepy World.” Journal of Risk Management in Financial Institutions.
Sterman. 2009. Business dynamics: systems thinking and modeling for a complex world.
Walker, and Janssen. 2002. Rangelands, Pastoralists and Governments: Interlinked Systems of People and Nature.” Philosophical Transactions of the Royal Society B: Biological Sciences.