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Despite the recent progress in artificial intelligence (AI), human-centered AI confronts a number of uneasy chal-lenges. This paper sheds light on two of such challenges: safety in the face of unexpected uncertainty and inability to assign meaning to encountered experiences. We showcase the implication of these two issues in the field of driverless cars, introducing the concept of ‘useful knowledge’ as that kind of applicable skills gained over a lifetime from different sources in diverse settings, and highlight its importance in lending AI the ability to generalise across contexts. We also introduce two biological mechanisms: ‘fear behaviour’ and the ‘release of neurotransmitters,’ which enable the human brain to handle situations with unexpected uncertainties. In so doing, this paper stands for a cooperative human-machine coexistence, arguing that resolving the above challenges requires, among other things, aligning the principles of designing AI algorithms with nature-inspired solutions, where humans generate data and algorithms provide solutions.
Oussama H. Hamid (Thu,) studied this question.