Martin Ciupa¹ and Keith Abney², ¹CTO calvIO Inc., USA and ²Cal Poly, USA

AI advances represent a great technological opportunity, but also possible perils. This paper undertakes an ethical and systematic evaluation of those risks in a pragmatic analytical form of questions, which we term ‘Conceptual AI Risk analysis’. We then look at a topical case example in an actual industrial setting and apply that methodology in outline. The case involves Deep Learning Black-Boxes and their risk issues in an environment that requires compliance with legal rules and industry best practices. We examine a technological means to attempt to solve the Black-box problem for this case, referred to as “Really Useful Machine Learning” ( RUMLSM ). DARPA has identified such cases as being the “Third Wave of AI.” Conclusions to its efficacy are drawn.

AI Risk, Deep Neural Network, Black-box Problem, Really Useful Machine Learning, RUMLSM, DARPA Third Wave of AI.