Article ID Journal Published Year Pages File Type
589899 Safety Science 2009 10 Pages PDF
Abstract

Two cases of collective decision making from the pharmaceutical industry were analysed, based on interviews and participant observation. The way safety considerations entered this process was no different from that of other inputs. In the cases no predefined process was foreseen, substantial consensus was required and there was little opportunity for interpersonal tradeoff. The observations from the cases were condensed into a descriptive theory for the natural decision process under similar conditions, the ‘Human Artificial Neural Network Process’ (HANNP) theory. Participants were found to act with bounded rationality conditioned by their knowledge culture, i.e. they elaborated issues within their knowledge culture rationally; they dealt with outside issues by intuition, and some issues they kept tacit. They created within themselves, but also at the group level, a set of incommensurable input variables for both the individual and the collective decision processes. Integration of incommensurable and incomplete input variables into a definite decision was resolved by these HANNPs with ‘relevant personal and collective experience’ as the training of the system. HANNPs designate processes in an individual human brain and in an assembly of multiples thereof, which function like trained so-called “artificial organisms”. Since HANNPs resist conversion into algorithms or heuristics, the descriptive theory has little prescriptive potential, except for encouraging communication sensitive to different knowledge cultures.

Related Topics
Physical Sciences and Engineering Chemical Engineering Chemical Health and Safety
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