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There is an analogy between machine learning systems and economic entities inthat they are both adaptive, and their behaviour is specified in a more-or-lessexplicit way. It appears that the area of AI that is most analogous to thebehaviour of economic entities is that of morally good decision-making, but itis an open question as to how precisely moral behaviour can be achieved in anAI system. This paper explores the analogy between these two complex systems,and we suggest that a clearer understanding of this apparent analogy may helpus forward in both the socio-economic domain and the AI domain: known resultsin economics may help inform feasible solutions in AI safety, but also knownresults in AI may inform economic policy. If this claim is correct, then therecent successes of deep learning for AI suggest that more implicitspecifications work better than explicit ones for solving such problems.

Learning from Learning Machines: Optimisation, Rules, and Social Norms