Abstract
Transparency in the field of human-machine interaction and artificial intelligence has seen a growth of interest in the past few years. Nonetheless, there are still few experimental studies on how transparency affects teamwork, in particular in collaborative situations where the strategies of others, including agents, may seem obscure.
We explored this problem using a collaborative game scenario with a mixed human-agent team. We investigated the role of transparency in the agents’ decisions, by having agents that reveal and tell the strategies they adopt in the game, in a manner that makes their decisions transparent to the other team members. The game embraces a social dilemma where a human player can choose to contribute to the goal of the team (cooperate) or act selfishly in the interest of his or her individual goal (defect). We designed a between-subjects experimental study, with different conditions, manipulating the transparency in a team. The results showed an interaction effect between the agents’ strategy and transparency on trust, group identification and human-likeness. Our results suggest that transparency has a positive effect in terms of people’s perception of trust, group identification and human likeness when the agents use a tit-for-tat or a more individualistic strategy. In fact, adding transparent behaviour to an unconditional cooperator negatively affects the measured dimensions.
This work was supported by national funds through Fundação para a Ciência e a Tecnologia (FCT-UID/CEC/50021/2019), and Silvia Tulli acknowledges the European Union’s Horizon 2020 research and innovation program for grant agreement No. 765955 ANIMATAS project. Filipa Correia also acknowledges an FCT grant (Ref. SFRH/BD/118031/2016).
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Tulli, S., Correia, F., Mascarenhas, S., Gomes, S., Melo, F.S., Paiva, A. (2019). Effects of Agents’ Transparency on Teamwork. In: Calvaresi, D., Najjar, A., Schumacher, M., Främling, K. (eds) Explainable, Transparent Autonomous Agents and Multi-Agent Systems. EXTRAAMAS 2019. Lecture Notes in Computer Science(), vol 11763. Springer, Cham. https://doi.org/10.1007/978-3-030-30391-4_2
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