People routinely attribute mental states such as beliefs, desires, and intentions to explain and predict others' behavior. Prior work shows that such attributions extend to robots, yet it remains unclear what people assume about the reality of the states they attribute to them. Building on recent conceptual work on folk-ontological stances, we report a pilot study measuring realist, anti-realist, and agnostic stances toward robot minds. Using a questionnaire (N = 66), we assessed stances toward today's robots and robots in principle, and examined stance rigidity through a reflection-and-reassessment design. Results show stronger anti-realist tendencies for today's robots than for robots in principle. Stances were largely rigid across reflection. Notably, participants did not hold a uniformly non-realist view but expressed a diversity of folk-ontological stances, including substantial proportions of agnostic and realist responses. This heterogeneity highlights the need for measurement tools that move beyond binary measures and capture nuance in folk-ontological reasoning. Future work will expand stance options to include finer-grained realist and anti-realist variants and recruit cross-cultural samples to assess variation across populations.

Thellman, S., Bergsten, K., Datteri, E., Ziemke, T. (2026). Realist, Anti-realist, or Agnostic? Exploring Folk-Ontological Stances toward Robot Minds. In L. Baillie, W.D. Smart, M. De Graaf, M. Gombolay, I. Torre (a cura di), HRI Companion '26: Companion Proceedings of the 21st ACM/IEEE International Conference on Human-Robot Interaction (pp. 332-335). Association for Computing Machinery (ACM) [10.1145/3776734.3794410].

Realist, Anti-realist, or Agnostic? Exploring Folk-Ontological Stances toward Robot Minds

Datteri, E;
2026

Abstract

People routinely attribute mental states such as beliefs, desires, and intentions to explain and predict others' behavior. Prior work shows that such attributions extend to robots, yet it remains unclear what people assume about the reality of the states they attribute to them. Building on recent conceptual work on folk-ontological stances, we report a pilot study measuring realist, anti-realist, and agnostic stances toward robot minds. Using a questionnaire (N = 66), we assessed stances toward today's robots and robots in principle, and examined stance rigidity through a reflection-and-reassessment design. Results show stronger anti-realist tendencies for today's robots than for robots in principle. Stances were largely rigid across reflection. Notably, participants did not hold a uniformly non-realist view but expressed a diversity of folk-ontological stances, including substantial proportions of agnostic and realist responses. This heterogeneity highlights the need for measurement tools that move beyond binary measures and capture nuance in folk-ontological reasoning. Future work will expand stance options to include finer-grained realist and anti-realist variants and recruit cross-cultural samples to assess variation across populations.
Capitolo o saggio
folk ontology, mental state attribution, belief vs. acceptance
English
HRI Companion '26: Companion Proceedings of the 21st ACM/IEEE International Conference on Human-Robot Interaction
Baillie, L; Smart, WD; De Graaf, M; Gombolay, M; Torre, I
16-mar-2026
2026
9798400723216
Association for Computing Machinery (ACM)
332
335
Thellman, S., Bergsten, K., Datteri, E., Ziemke, T. (2026). Realist, Anti-realist, or Agnostic? Exploring Folk-Ontological Stances toward Robot Minds. In L. Baillie, W.D. Smart, M. De Graaf, M. Gombolay, I. Torre (a cura di), HRI Companion '26: Companion Proceedings of the 21st ACM/IEEE International Conference on Human-Robot Interaction (pp. 332-335). Association for Computing Machinery (ACM) [10.1145/3776734.3794410].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/596961
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