Special issue on the 11th conference on naturalistic decision making

Abstract

The naturalistic decision-making (NDM) approach deals with how humans make decisions in natural settings, especially professional situations, which can be difficult to reproduce in experimental laboratory studies. NDM explores collaboration and cooperation both between humans, and between humans and systems, as well as situations of diagnosis, planning, supervision, and control processes. Basically, decision researchers focus on the analysis of humans at work and their interactions with systems in context, including both environmental and social dimensions. Since the movement was founded, more than 20 years ago, several models of decision making have been developed, each offering a fresh view on how humans perform complex cognitive functions to accomplish situated activities. This very different way of studying human interactions in modern work environments has given rise to a worldwide research community sharing the same issues and a common theoretical background, and relying on ecological models of decision making (Brehmer 1992; Endsley 1995; Hutchins 1995; Rasmussen et al. 1994); models of intelligence, perception, and action as mental models (Johnson-Laird 1983); and activity theory (Engestrom 1999; Kuutti 1996; Nardi 1996). Looking further back, the field of naturalistic decision making can be seen to have its historical roots in the ground-breaking work of Vygotsky and Leont’ev (Leont’ev 1978; Leont’ev and Luria 1968), and even Piaget’s intelligence theory (Piaget 1972, 1977). The NDM approach, which is predicated upon a strong relationship between application fields, research, and models of complex cognitive tasks, is responsible for a now well-established definition of decision making (Klein et al. 1993): ‘‘eight important factors characterize decision making in naturalistic settings, but frequently are ignored in decision-making research. It is not likely that all eight factors will be at their most difficult levels in any one setting, but often several of these factors will complicate the decision task.