Traditionally, the manufacturer/operator of a machine is held (morally and legally) 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 (which is not a (...) realistic option), or facing a responsibility gap, which cannot be bridged by traditional concepts of responsibility ascription. (shrink)

The early examples of self-directing robots attracted the interest of both scientific and military communities. Biologists regarded these devices as material models of animal tropisms. Engineers envisaged the possibility of turning self-directing robots into new “intelligent” torpedoes during World War I. Starting from World War II, more extensive interactions developed between theoretical inquiry and applied military research on the subject of adaptive and intelligent machinery. Pioneers of Cybernetics were involved in the development of goal-seeking warfare devices. But collaboration occasionally turned (...) into open dissent. Founder of Cybernetics Norbert Wiener, in the aftermath of World War II, argued against military applications of learning machines, by drawing on epistemological appraisals of machine learning techniques. This connection between philosophy of science and techno-ethics is both strengthened and extended here. It is strengthened by an epistemological analysis of contemporary machine learning from examples; it is extended by a reflection on ceteris paribus conditions for models of adaptive behaviours. (shrink)