Arrested decisions: the effects of information latency on high-risk decision-making

This research will evaluate how changes in information latency during computer deployments affect performance of high risk decision makers. High risk decisions and decision-makers, in this case, are police officers deciding whether or not to arrest an individual based on information provided via computer from a distant source. There are three critical research pillars for this research. First, the impact on performance of naturalistic decision-making (NDM) research described for high-risk decision making through the use of a recognition-primed decision (RPD) model (Klein 1998) will be observed. Next, media richness posits richer media has more impact on equivocal tasks. Media of different “richness” was tested for impacts on decision performance. The recognition primed decision model, portions of media richness, and information thresholds are integrated to provide a model to relate information latency effects on high-risk decision-making. This model was evaluated using three wireless computer deployments by a city-county police department. Using archival data, subjects in this research, 406 mobile police officers, were followed over a six year period to evaluate the impact of varying media richness (from radio verbal access to textural computer queries of varying types) using computers of varying access-information retrieval rates. Outcome measures of arrest warrants served and physical arrests based on probable cause (where a reasonable officer would believe that a person had committed a criminal violation of local, state or federal law), were recorded over all interventions. User performance traits are shown to be a major influencing factor in outcomes and processes changes. Finally, this research shows how individual user performance traits impact high-risk decision performance more than latency but only with high performers in the organization. Information latency is shown to have little impact on low performers. User performance traits may explain the productivity paradox1 with computers. 1Brynjolfsson, E. and L. Hitt (1998). “Beyond the Productivity Paradox: Computers are the Catalyst for Bigger Changes.” Communications of the ACM 41(8): 49–55.