"But the computer said!" - Credible uses of computational modeling in public sector decision making
There has been a continued expansion of the uses of computer-based tools and techniques in public sector endeavors: from traditional notions of data collection and management (bean counting) to the processing of data into information that supports managerial activities. Advances in technology based on emerging work in decision theory, information science, and cognitive science will allow for use of these computational models in more expansive "advisory" roles to decision makers of all types. To what degree can public sector decision makers use computational models to support or advise decision making? As these new technologies become a routine part of the policy process, will a belief in computer omnipotence tempt public sector decision makers to abdicate personal responsibility for poor choices? The authors explore the choice-related implications associated with the increased use of computer-based models, define possible computer-based decision support models (CBDSMs), and present a typology of credible uses of CBDSMs.
computational models policy analysis machine learning decision support systems