Reviewing tests for machine consciousness

Aïda Elamrani, University of Louisville
Roman V. Yampolskiy, University of Louisville

Abstract

The accelerating advances in the fields of neuroscience, artificial intelligence, and robotics have been garnering interest and raising new philosophical, ethical, or practical questions that depend on whether or not there may exist a scientific method of probing consciousness in machines. This paper provides an analytic review of the existing tests for machine consciousness proposed in the academic literature over the past decade, and an overview of the diverse scientific communities involved in this enterprise. The tests put forward in their work typically fall under one of two grand categories: Architecture (the presence of consciousness is inferred from the correct implementation of a relevant architecture) and behaviour (the presence of consciousness is deduced by observing a specific behaviour). Each category has its strengths and weaknesses. Architecture tests’ main advantage is that they could apparently test for qualia, a feature that has been receiving increasing attention in recent years. Behaviour tests are more synthetic and more practicable, but give a stronger role to ex post human interpretation of behaviour. We show how some disciplines and places have affinities towards certain type of tests, and which tests are more influential according to scientometric indicators.