Quite simply, if we cannot count on our AI to behave reliably, we should not trust it.1 

One might contrast robust AI with, for example, narrow intelligence, systems that 
perform a single narrow goal extremely well (eg chess playing or identifying dog 
breeds) but often in ways that are extremely centered around a single task and not 
robust and transferable to even modestly different circumstances (eg to a board of 
different size, or from one video game to another with the same logic but different 
characters and settings) without extensive retraining. Such systems often work 
impressively well when applied to the exact environments on which they are trained, 

 

1 Of course, the converse is not true: reliability doesn't guarantee trustworthiness; it's just one prerequisite 
among many, including values and good engineering practice; see Marcus and Davis (Marcus & Davis, 
2019) for further discussion. 

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THE NEXT DECADE IN AI / GARY MARCUS
The Next Decade in AI-