Designing a Conversational Agent for Sexual Assault Survivors: Defining Burden of Self-Disclosure and Envisioning Survivor-Centered Solutions
Abstract
Sexual assault survivors hesitate to disclose their stories to others and even avoid case-reporting because of psychological, social, and cultural reasons. Thus, conversational agents (CAs) have gained much attention as a potential counselor because CAs’ characteristics (e.g., anonymity) could mitigate various difficulties of human-human interaction (HHI). Despite the potentials, it is difficult to design a CA for survivors because various aspects should be considered. Especially, with traditional HCI approaches only (e.g., need-finding and usability tests), designers could easily miss psychological and subjective burdens that survivors feel toward a new system. Hence, while envisioning a burden-free CA for survivors, we agilely designed and implemented an initial prototype CA (NamuBot) with professionals (the police and counselors). We then conducted a qualitative user study to identify and compare burdens caused by the CA vs. humans. Lastly, we codesigned design features that could reduce the CA-bound burdens with 36 participants (19 survivors and 17 professionals). Notably, our findings showed that 17 survivors preferred reporting their case to NamuBot over humans, expressing far less burden. Although CAs could also place burdens on survivors, the burdens could be alleviated by the features that the survivors and professionals designed. Finally, we present design implications and strategies to develop burden-mitigating CAs for survivors.
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The authors did not measure intercoder reliability in line with similar qualitative and participatory design papers, following justification in [9].
“We did not measure intercoder reliability in line with similar qualitative and participatory design papers [25, 69, 99], following the justification presented in [9].”
From The Promise and Peril of ChatGPT in Higher Education: Opportunities, Challenges, and Design Implications (2024) · cites this paper as [69]
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- Authors
- Park, H., & Lee, J.
- Affiliations
- Seoul National University (KR)
- Venue
- Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2021-05-06
- Pages
- 1-17
- OpenAlex
- W3163773730
- Cited by
- 44
- References
- 17
- Citations by year
- 2026: 5 · 2025: 16 · 2024: 10 · 2023: 5 · 2022: 8
- FWCI
- 9.81
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- chatbots, sexual assault survivors, case notification, burden reduction, anonymity, human-human interaction
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