Between You and Me: Ethics of Self-Disclosure in Human-Robot Interaction

As we move toward a future where robots are increasingly part of daily life, the privacy risks associated with interactions, particularly those relying on cloud-based large language models (LLMs), are becoming more pressing. Users may unknowingly share sensitive information in environments, such as homes or hospitals. To explore these risks, we conducted a study with 39 native English speakers using a Furhat robot with an integrated LLM. Participants discussed two moral dilemmas: (i) dishonesty, sharing personal stories of justified lying, and (ii) robot disobedience, discussing whether robots should disobey commands. On average, participants disclosed personal stories 45% of the time when asked in both scenarios. The main reason for non-disclosure was difficulty recalling examples quickly (33.3-56%), rather than reluctance to share (7.2-16%). However, most participants reported a lack of discomfort and concern about sharing personal information with the robot, indicating limited awareness of the privacy risks involved in such disclosures.

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Publication Details

Published
2025-03-04
DOI
https://doi.org/10.1109/hri61500.2025.10974215
Citations
3
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
7.10

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article

Between You and Me: Ethics of Self-Disclosure in Human-Robot Interaction

Gabriel Skantze, Bahar Irfan
3 citations
Ethics and Social Impacts of AI
7.10
article

Between You and Me: Ethics of Self-Disclosure in Human-Robot Interaction

Gabriel Skantze, Bahar Irfan
article en
3 citations

Abstract

As we move toward a future where robots are increasingly part of daily life, the privacy risks associated with interactions, particularly those relying on cloud-based large language models (LLMs), are becoming more pressing. Users may unknowingly share sensitive information in environments, such as homes or hospitals. To explore these risks, we conducted a study with 39 native English speakers using a Furhat robot with an integrated LLM. Participants discussed two moral dilemmas: (i) dishonesty, sharing personal stories of justified lying, and (ii) robot disobedience, discussing whether robots should disobey commands. On average, participants disclosed personal stories 45% of the time when asked in both scenarios. The main reason for non-disclosure was difficulty recalling examples quickly (33.3-56%), rather than reluctance to share (7.2-16%). However, most participants reported a lack of discomfort and concern about sharing personal information with the robot, indicating limited awareness of the privacy risks involved in such disclosures.

KTH Royal Institute of Technology (SE)
Vetenskapsrådet
Gender equality
Openalex Percentile: Top 3%
Ethics and Social Impacts of AI
7.10
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