Human versus automation in responding to failures: an expected-value analysis.
A simple analytical criterion is provided for deciding whether a human or automation is best for a failure detection task. The method is based on expected-value decision theory in much the same way as is signal detection. It requires specification of the probabilities of misses (false negatives) and false alarms (false positives) for both human and automation being considered, as well as factors independent of the choice--namely, costs and benefits of incorrect and correct decisions as well as the prior probability of failure. The method can also serve as a basis for comparing different modes of automation. Some limiting cases of application are discussed, as are some decision criteria other than expected value. Actual or potential applications include the design and evaluation of any system in which either humans or automation are being considered.
Sheridan
T B
TB
Massachusetts Institute of Technology, Cambridge, USA. sheridan@mit.edu
Parasuraman
R
R
D001331:Automation; D003657:Decision Making; D019544:Equipment Failure Analysis / Q000379:methods*; D005189:False Positive Reactions; D006801:Humans; D008962:Models, Theoretical; D011237:Predictive Value of Tests; D013223:Statistics as Topic; D013647:Task Performance and Analysis