The responsibility gap: Ascribing responsibility for the actions of learning automata

Abstract

Traditionally, the manufacturer/operator of a machine is held responsible for the consequences of its operation. Autonomous, learning machines, based on neural networks, genetic algorithms and agent architectures, create a new situation, where the manufacturer/operator of the machine is in principle not capable of predicting the future machine behaviour any more, and thus cannot be held morally responsible or liable for it. The society must decide between not using this kind of machine any more, or facing a responsibility gap, which cannot be bridged by traditional concepts of responsibility ascription.

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