A match does not make a sense: on the sufficiency of the comparator model for explaining the sense of agency. Issue 1 (13th May 2019)

• Record Type: Journal Article
• Authors: Zaadnoordijk, Lorijn; Besold, Tarek R; Hunnius, Sabine
• Is Part Of: Neuroscience of consciousness. Issue 1(2019)
• Publication Date: 2019-05-13
• Subjects: sense of agency -- infancy -- developmental cognitive science -- developmental robotics -- comparator model -- artificial intelligence; Consciousness -- Periodicals; Consciousness -- Physiological aspects -- Periodicals; 612.823
• DOI: 10.1093/nc/niz006
• Languages: English
• ISSNs: 2057-2107

Abstract

Abstract: The development of a sense of agency is indispensable for a cognitive entity (biological or artificial) to become a cognitive agent. In developmental psychology, researchers have taken inspiration from adult cognitive psychology and neuroscience literature and use the comparator model to assess the presence of a sense of agency in early infancy. Similarly, robotics researchers have taken components of the proposed mechanism in attempts to build a sense of agency into artificial systems. In this article, we identify an invalidating theoretical flaw in the reasoning underlying this conversion from adult studies to developmental science and cognitive systems research, rooted in an oversight in the conceptualization of the comparator model as currently used in experimental practice. In these experiments, the emphasis has been put solely on testing for a match between predicted and observed sensory consequences. We argue that the match by itself can exclusively generate a simple categorization or a representation of equality between predicted and observed sensory consequences, both of which are insufficient to generate the causal representations required for a sense of agency. Consequently, the comparator model, as it has been described in the context of the sense of agency and as it is commonly used in experimental designs, is insufficient to generate the sense of agency: infants and robots require more than developing the ability to match predicted and observed sensory consequences for a sense of agency. We conclude with outlining possible solutions and future directions for researchers in developmental science and artificial intelligence.