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The deployment of artificial intelligence from experimental settings to concrete applications implies to consider the social aspects of the environment and consequently to conceive the interaction between humans and computers endowed with the aim of being partners in action. This article proposes a review of the research initiatives regarding human-artificial agents interaction, including eXplainable Artificial Intelligence (XAI) and HRI/HCI. We argue that even if vocabulary and approaches are different, the concepts converge on the necessity for the artificial agents to provide an accurate mental model of their behavior to the humans they are interacting with. This has different implications depending on whether we consider a tool/user interaction or a cooperation interaction—which is far less documented despite being at the heart of the future concepts of autonomous vehicles. From this observation, the article uses the cognitive science corpus on joint-action to raise finer cognitive mechanisms proved to be essential for human joint-action which could be considered as cognitive requirements for future artificial agents, including shared task representation and mentalization. Finally, interactions content hypotheses are arisen to satisfy the identified mechanisms, including the ability for the artificial agent to elicit its intentions and to trigger mentalization toward them from the human cooperators.
Guillou et al. (Wed,) studied this question.