ORIGINAL RESEARCH article
Front. Polit. Sci.
Sec. Politics of Technology
Volume 7 - 2025 | doi: 10.3389/fpos.2025.1631881
This article is part of the Research TopicHuman Rights and Artificial IntelligenceView all 4 articles
Empathy, bias, and data responsibility: Evaluating AI chatbots for gender-based violence support
Provisionally accepted
- University of Deusto, Bilbao, Spain
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Artificial Intelligence (AI) chatbots are increasingly deployed as support tools in sensitive domains such as gender-based violence (GBV). This study evaluates the performance of three conversational AI models—including a general-purpose Large Language Model (ChatGPT), an open-source model (LLaMA), and a specialised chatbot (AinoAid)—in providing first-line assistance to women affected by GBV. Drawing on findings from the European IMPROVE project, the research uses a mixed-methods design combining qualitative narrative interviews with 30 survivors in Spain and quantitative natural language processing metrics. Chatbots were assessed through scenario-based simulations across the GBV cycle, with prompts designed via the Systematic Context Construction and Behavior Specification method to ensure ethical and empathetic alignment. Results reveal significant differences in emotional resonance, response quality, and gender bias handling, with ChatGPT showing the most empathetic engagement and AinoAid offering contextually precise guidance. However, all models lacked intersectional sensitivity and proactive attention to privacy. These findings highlight the importance of trauma-informed design and qualitative grounding in developing responsible AI for GBV support.
Keywords: Artificial intelligence (AI), Chatbots, Gender-based violence (GBV), AI biases, quality of empathic responses, Model evaluation, Prompt design, IMPROVE European project
Received: 20 May 2025; Accepted: 07 Jul 2025.
Copyright: © 2025 Sanz, Lopez-Belloso and Izaguirre Choperena. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Borja Sanz, University of Deusto, Bilbao, Spain
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