The problem of prediction is a general problem in the philosophy of sci- ence. It is important in every discipline for which prediction concerns the behavior of an artificial or a biological system, such as artificial intelligence or synthetic biology. Synthetic biology shares with artificial intelligence some theoretical issues from the point of view of prediction. My claim is that the problems related to the prediction of system behaviors are analogous because: (a) artificial intelligence and synthetic biology aim at producing autonomous systems; and (b) their products interact with an open-ended and uncertain context. I argue my claim by providing three versions of the prediction problem in artificial intelligence and synthetic biology, to show the analogies between them within this framework and to suggest some useful consequences.

Francesco Bianchini (2018). The Problem of Prediction in Artificial Intelligence and Synthetic Biology. COMPLEX SYSTEMS, 27(3), 249-265 [10.25088/ComplexSystems.27.3.249].

The Problem of Prediction in Artificial Intelligence and Synthetic Biology

Francesco Bianchini
2018

Abstract

The problem of prediction is a general problem in the philosophy of sci- ence. It is important in every discipline for which prediction concerns the behavior of an artificial or a biological system, such as artificial intelligence or synthetic biology. Synthetic biology shares with artificial intelligence some theoretical issues from the point of view of prediction. My claim is that the problems related to the prediction of system behaviors are analogous because: (a) artificial intelligence and synthetic biology aim at producing autonomous systems; and (b) their products interact with an open-ended and uncertain context. I argue my claim by providing three versions of the prediction problem in artificial intelligence and synthetic biology, to show the analogies between them within this framework and to suggest some useful consequences.
2018
Francesco Bianchini (2018). The Problem of Prediction in Artificial Intelligence and Synthetic Biology. COMPLEX SYSTEMS, 27(3), 249-265 [10.25088/ComplexSystems.27.3.249].
Francesco Bianchini
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/676037
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