Automating assistance for safety critical decisions

Computer systems are increasingly being introduced to assist in decision making, including hazardous decision making. To ensure effective assistance, decision procedures should be theoretically sound, flexible in operation (particularly in unpredictable environments) and effectively accountable to human supervisors and auditors. Strengths and weaknesses of classical statistical decision models are discussed from these perspectives. It is argued that more can be learned from human decision behaviour than has traditionally been assumed, and this motivates the concept of a symbolic decision procedure (SDP). The SDP is defined, described in terms of first-order (predicate) logic, and its use illustrated in a decision support system for medicine. We point out that the classical numerical decision procedure is a special case of a generalized symbolic procedure, and discuss the potential for rigorous formalization of the latter. We conclude that symbolic decision procedures may meet requirements for assisting human operators in hazardous situations more satisfactorily than classical decision procedures.