Naturalistic Decision Making

The unorthodox question is: “What do expert decision makers do naturally?”

Naturalistic approaches to psychological phenomena1,2 work to model decision making and situation awareness in real-world, as contrasted with theoretically-conceived, activities. Traditional research has long found human decision making inferior to formalized rational decision models such as Bayesian analysis or multi-attribute utility theory. Then we are urged to be rational creatures, which we very basically are not.

NDM’s (Naturalistic Decision Making) position is that real experts, working under time pressure and unreliable information, with changing goals and situations, are simply not represented by traditional laboratory models. “In the Wild”, they tend to make no comparisons of alternatives, quickly generating a workable first option based on similarity to prior situations (the experience factor), fixing or replacing it only if quick mental simulation shows significant flaws.

Experts recognize prototypical situations using cues3 and patterns that simplified laboratory experiments remove from simplified laboratory testing. Drillings and Serfaty3 refer to Daniel’s 1979 work demonstrating individual expertise as being at least as important as quantity of information, in that “the best players made as good decisions with 20% of the ground truth as did the worst players with 80%…” (p. 78). Endsley, who specializes in Situation Awareness had similar findings.

Klein’s Recognition-Primed Decision (RPD) model began with fire-ground commanders at fires4 , and developed further with military field commanders. This model has been tested in activities ranging from anesthesiology, nuclear power plant operation, software design, offshore drilling and jury deliberations to highway design. This diversification is important in showing that the process is universally human rather than domain-specific.

The NDM approach has generated more than 7 world conferences. The first one5 listed 8 factors of interest:

  1. Ill-structured problems
  2. Uncertain dynamic environments
  3. Shifting, ill-defined, or competing goals
  4. Action/feedback loops
  5. Time stress
  6. High stakes
  7. Multiple players
  8. Organizational goals and norms.

This list shows that uncertainty is the most general factor, since most of the factors contribute to it. It is this uncertainty, and its impact on individual interpretations of the problem they face that link NDM to Adult Learning, and also motivates simplification of a problem in most laboratory research.

A major point contributed by NDM is the argument that psychological research cannot approach real-world problems without incorporating options, uncertainty, real stakes, and change. It also strongly argues that starting from theory without first observing what naturally occurs, and trying to describe it, is fruitless.

We agree.

The training model developed at TactiCog(sm) does not start from abstract theory—it is drawn from combat-proven real-world training procedures with a combat-proven history. Our model exhibits points 3-8 of this list, and generates points 1 & 2 at the level of the participants’ experience of it.

1 Klein, G. A., Orasanu, J., Calderwood, R., & Zsambook, C. E. (Eds.). (1993). Decision Making in Action: Models and Methods. Norwood, NJ: Ablex Publishing Corporation.

2 Endsley, M. R., & Bolstad, C. A. (1994). Individual differences in pilot situation awareness. International Journal of Aviation Psychology, 4(3), 241-264.

3 Drillings, M., & Serfaty, D. (1997). Naturalistic decision making in command and control. In C. E. Zsambok & G. Klein (Eds.), Naturalistic Decision Making (pp. 71-80). Mahwah, NJ:LawrenceErlbaum Associates.

4 Klein, G. (1997). Making Decisions in Natural Environments (Special Report 31): Research and Advanced Concepts Office, U.S. Army Research Institute for the Behavioral and Social Sciences.

5 Orasanu, J., & Connolly, T. (1993). The reinvention of decision making. In G. A. Klein & J. Orasanu & R. Calderwood & C. E. Zsambook (Eds.), Decision Making in Action: Models and Methods (pp. 3-20).Norwood, NJ: Ablex Publishing Corporation.

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