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We ask whether there cannot also be ‘artificial’ science—knowledge about artificial objects and phenomena.” In line with Simon’s vision, we describe the emergence of an interdisciplinary field of scientific study.This field is concerned with the scientific study of intelligent machines, not as engineering artefacts, but as a class of actors with particular behavioural patterns and ecology.We start by providing background on the study of machine behaviour and the necessarily interdisciplinary nature of this science.We then provide a framework for the conceptualization of studies of machine behaviour.The complexity of individual AI agents is currently high and rapidly increasing.Although the code for specifying the architecture and training of a model can be simple, the results can be very complex, oftentimes effectively resulting in ‘black boxes’.
Industrial secrecy and legal protection of intellectual property often surround source code and model structure.
We close with a call for the scientific study of machine and human–machine ecologies and discuss some of the technical, legal and institutional barriers that are faced by researchers in this field.
There are three primary motivations for the scientific discipline of machine behaviour.
AI agents can also demonstrate novel behaviours through their interaction with the world and other agents that are impossible to predict with precision.
Furthermore, when the environment is changing—perhaps as a result of the algorithm itself—anticipating and analysing behaviour is made much harder.