Artificial Intelligence increasingly pursues large, complex models that perform many tasks within increasingly realistic domains. How, if at all, should these developments in AI influence cognitive science? We argue that progress in AI offers timely opportunities for cognitive science to embrace experiments with increasingly naturalistic stimuli, tasks, and behaviors; and computational models that can accommodate these changes. We first review a growing body of research spanning neuroscience, cognitive science, and AI that suggests that incorporating a broader range of naturalistic experimental paradigms (and models that accommodate them) may be necessary to resolve some aspects of natural intelligence and ensure that our theories generalize. We then suggest that integrating recent progress in AI and cognitive science will enable us to engage with more naturalistic phenomena without giving up experimental control or the pursuit of theoretically grounded understanding. We offer practical guidance on how methodological practices can contribute to cumulative progress in naturalistic computational cognitive science, and illustrate a path towards building computational models that solve the real problems of natural cognition - together with a reductive understanding of the processes and principles by which they do so.

While AI technology has reached important levels of performances in narrow settings, the missing part concerns exactly the study of how to create artificial companions (embodied and disembodied) able to integrate different skills in order to help humans in their everyday activities. Similarly, computational cognitive science is interested in individuating how the brain and the mind works as integrated systems. This renewed convergence is, in my view, a necessity driven by the fact that modern and future AI and CogSci research will be again disciplines interested in the same topic: namely the discovery of the mechanisms enabling multitasking intelligence. In order to advance the scientific knowledge in their respective field, in fact, they need to evolve and become sciences (of the artificial) studying the mysteries of

Project required for graduate credit. This class is suitable for intermediate to advanced undergraduates or graduate students specializing in cognitive science, artificial intelligence, and related fields.