Generalized probabilistic learning takes place in a black-box where present probabilities lead to future probabilities by way of a hidden learning process. The idea that generalized learning can be partially characterized by saying that it doesn�t foreseeably lead to harmful decisions is explored. It is shown that a martingale principle follows for finite probability spaces.
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