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When people speak about consciousness, they distinguish various types and different levels, and they argue for different concepts of cognition. This complicates the discussion about artificial or machine consciousness. Here we take a bottom-up approach to this question by presenting a family of robot experiments that invite us to think about consciousness in the context of artificial agents. The experiments are based on a computational model of sensorimotor contingencies. It has been suggested that these regularities in the sensorimotor flow of an agent can explain raw feels and perceptual consciousness in biological agents. We discuss the validity of the model with respect to sensorimotor contingency theory and consider whether a robot that is controlled by knowledge of its sensorimotor contingencies could have any form of consciousness. We propose that consciousness does not require higher-order thought or higher-order representations. Rather, we argue that consciousness starts when (i) an agent actively (endogenously triggered) uses its knowledge of sensorimotor contingencies to issue predictions and (ii) when it deploys this capability to structure subsequent action. [ABSTRACT FROM AUTHOR]

In cognitive science, we are currently witnessing a ‘pragmatic turn’, away from the traditional representation-centered framework towards a paradigm that focuses on understanding cognition as ‘enactive’, as skillful activity that involves ongoing interaction with the external world. The key premise of this view is that cognition should not be understood as providing models of the world, but as subserving action and being grounded in sensorimotor coupling. Accordingly, cognitive processes and their underlying neural activity patterns should be studied primarily with respect to their role in action generation. We suggest that such an action-oriented paradigm is not only conceptually viable, but already supported by much experimental evidence. Numerous findings either overtly demonstrate the action-relatedness of cognition or can be re-interpreted in this new framework. We argue that new vistas on the functional relevance and the presumed ‘representational’ nature of neural processes are likely to emerge from this paradigm. [Copyright &y& Elsevier]