Overview:
The acceleration of change and interdependency, plus the proliferation of choices and the growing number of people and cultures involved in decisions, all increase uncertainty, unpredictability, ambiguity, and surprise. This increasing complexity of everything from world affairs to individual career choices is forcing humans to rely more and more on expert advice and computers. Just as the autonomic nervous system runs most biological decision making, so too are computer systems increasingly making the day-to-day decisions of civilization. We have far more data, evidence, and computer models to make decisions today, but that also means we have far more information overload and excessive choice proliferation, leading many to seek external experts. The number and complexity of choices seem to be growing beyond our abilities to analyze, synthesize, and make decisions. The acceleration of change reduces the time from recognition of the need to make a decision to completion of all the steps to make the right decision.
Decision Making Facts
Alternative approaches use diverse input and rules-based models to help anticipate outliers and surprise. Adaptive learning models such as cellular automata, genetic algorithms, and neural networks are growing in capability and accuracy, and databases describing individual behavior are becoming even more massive. Using leading indicators instead of lagging indicators can make analytics more useful to anticipate the need for decisions, rather than reacting to surprises. An organization’s strategic consciousness could become more important than static strategic plans, allowing for management by understanding instead of just fixed objectives. This can help an organization act more like a complex anticipatory adaptive system.
Decision Making can be used
In social sciences it has been difficult to develop “laws” to forecast social behavior and, hence, make good decisions based on forecasted consequences. With the advent of massive digital databases and new software, we can let the computer make more empirically based forecasts of the plausible range of how people will react to various decisions. At the same time, increasing democratization and interactive media are involving more people in decision making, which further increases complexity and surprise. This can reinforce the principle of subsidiarity—decisions made by the smallest number of people possible at the level closest to the impact of a decision. Fortunately, the world is moving toward ubiquitous computing with institutional and individual collective intelligence (emergent properties from synergies among brains, software, and information) for “just-in-time” knowledge to inform decisions. Ubiquitous computing will increase the number of decisions per day, constantly changing schedules and priorities. Decision making will be increasingly augmented by the integration of sensors imbedded in products, in buildings, and in living bodies with a more intelligent Web and with institutional and personal collective intelligence software that helps us select experts, information, and decision support software to receive and respond to feedback for improving decisions.
Recent Work