  In this paper we examine historical failures of artificial intelligence (AI)
and propose a classification scheme for categorizing future failures. By doing
so we hope that (a) the responses to future failures can be improved through
applying a systematic classification that can be used to simplify the choice of
response and (b) future failures can be reduced through augmenting development
lifecycles with targeted risk assessments.
