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Abstract
Home assistant chat-bots, self-driving cars, drones or automated negotiation systems are some of the several examples of autonomous (artificial) agents that have pervaded our society. These agents enable the automation of multiple tasks, saving time and (human) effort. However, their presence in social settings raises the need for a better understanding of their effect on social interactions and how they may be used to enhance cooperation towards the public good, instead of hindering it. To this end, we present an experimental study of human delegation to autonomous agents and hybrid human-agent interactions centered on a non-linear public goods dilemma with uncertain returns in which participants face a collective risk. Our aim is to understand experimentally whether the presence of autonomous agents has a positive or negative impact on social behaviour, equality and cooperation in such a dilemma. Our results show that cooperation and group success increases when participants delegate their actions to an artificial agent that plays on their behalf. Yet, this positive effect is less pronounced when humans interact in hybrid human-agent groups, where we mostly observe that humans in successful hybrid groups make higher contributions earlier in the game. Also, we show that participants wrongly believe that artificial agents will contribute less to the collective effort. In general, our results suggest that delegation to autonomous agents has the potential to work as commitment devices, which prevent both the temptation to deviate to an alternate (less collectively good) course of action, as well as limiting responses based on betrayal aversion.
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Details
1 Université Libre de Bruxelles, Machine Learning Group, Computer Science Department, Brussels, Belgium (GRID:grid.4989.c) (ISNI:0000 0001 2348 0746); Vrije Universiteit Brussel, Artificial Intelligence Lab, Computer Science Department, Brussels, Belgium (GRID:grid.8767.e) (ISNI:0000 0001 2290 8069); Université Libre de Bruxelles-Vrije Universiteit Brussel, FARI Institute, Brussels, Belgium (GRID:grid.4989.c) (ISNI:0000 0001 2348 0746)
2 Vrije Universiteit Brussel, Artificial Intelligence Lab, Computer Science Department, Brussels, Belgium (GRID:grid.8767.e) (ISNI:0000 0001 2290 8069); Ghent University - imec, IDLab, Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798)
3 Université Libre de Bruxelles, Machine Learning Group, Computer Science Department, Brussels, Belgium (GRID:grid.4989.c) (ISNI:0000 0001 2348 0746); ETHICS - EA 7446, Université Catholique de Lille, Lille, France (GRID:grid.417666.4) (ISNI:0000 0001 2165 6146)
4 Université Libre de Bruxelles, Machine Learning Group, Computer Science Department, Brussels, Belgium (GRID:grid.4989.c) (ISNI:0000 0001 2348 0746); Vrije Universiteit Brussel, Artificial Intelligence Lab, Computer Science Department, Brussels, Belgium (GRID:grid.8767.e) (ISNI:0000 0001 2290 8069)
5 Universidade de Vigo, atlanTTic Research Center, E.E. Telecom., Vigo, Spain (GRID:grid.6312.6) (ISNI:0000 0001 2097 6738)
6 Universidade de Lisboa, INESC-ID and Instituto Superior Técnico, Porto Salvo, Portugal (GRID:grid.9983.b) (ISNI:0000 0001 2181 4263)
7 Université Libre de Bruxelles, Machine Learning Group, Computer Science Department, Brussels, Belgium (GRID:grid.4989.c) (ISNI:0000 0001 2348 0746); Vrije Universiteit Brussel, Artificial Intelligence Lab, Computer Science Department, Brussels, Belgium (GRID:grid.8767.e) (ISNI:0000 0001 2290 8069); UC Berkeley, Center for Human-Compatible AI, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878); Université Libre de Bruxelles-Vrije Universiteit Brussel, FARI Institute, Brussels, Belgium (GRID:grid.4989.c) (ISNI:0000 0001 2348 0746)