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Predicting CAS

Predicting the future is the dream and one of the "ultimate superpowers". The rise of AI everywhere is a major trend of the next 20 years, but this does not mean that decision making will be rendered fully to the machines. Practically, most important decisions will continue to be made by few people. Paradoxically, even more important decisions, due to the concentration of power helped by AI and other technologies, will be made by very few individuals.

Many, almost all, areas of human activity require complex, strategic, and adaptive decision making. Geopolitics and finance (during crises and to lesser extent during peaceful times) are particularly important areas where good decision making under uncertainty is critical. We can classify decision making processes into several classes so that the decision is made by

A) a single human.

From simple to complex decisions - from how to slice bread to how to rule a country. A vast amount of literature is devoted to good human decision making. From Ray Dalio on Making Better Decisions to Farnam Street. One review book is Strategy and Choice by Richard Zeckhauser.

B) a single computer/machine/AI.

The machine - how to store and execute a code, how to play chess,etc.

C) a collective of humans.

Example - a board of a company, top politicians of a government, etc. How to build a company where the best ideas win by Dalio.

The public markets itself is the best example of a predictive tool and "a decision maker". More explicitly, prediction markets and reputation systems are smart collective decision makers.

D) a combination of AI and a human(s).

This class is superior than other classes by construction that, at least in principle, this approach can combine the best of all worlds. Implicitly or explicitly, intelligent tools and predictive analytics is what all finance companies are doing in the conventional area of financial markets with abundant data. Not only Dalio of Bridgewater and Lary Fink of Blackrock but many others in various forms. Larry Fink’s ambitions to turn Blackrock into something more like Google utilizing its ‘Android of finance’ ALADDIN Collective Intelligence. Palantir is another example.

  • a challenge

All involved human players and their collective activities (geopolitics, finance,etc.) are CAS (complex adaptive systems). The challenge is then how decision-maker CAS (DM-CAS) can map abundant-data CAS (AD-CAS), so that DM-CAS can predict probabilistically the future actions of AD-CAS. In our context of interest, DM-CAS,the decision maker,is AI, a human, and a group of people. AD-CAS, the black box system, is the collective human activities like geopolitics and finance.

Important condition for human training and effectiveness of a personal tool is BIG data. One obvious area is financial data and players, which have high(er) frequency decisions. Geopolitics look as less frequent but more strategic area for the decisions (unless expanded into various "noisy news").

  • conclusion

"Personal GPS" for personal decision making and "Interactive GPS" for the judgment about other person's decision making are the powerful technology, which is worth exploring.