Creating a Chatbot for and with Migrants: Chatbot Personality Drives Co-Design Activities
Open accessAbstract
Information portals are usually created to support the integration of migrants into a host country. However, the information-seeking process can be exhausting, cumbersome and even confusing for migrants as they must cope with time-consuming information overload while searching desired information from lists of documents. Chatbots are easy-to-use, natural, and intuitive, and thus could support information-seeking. There is a lack of research that engages and empowers migrants and other stakeholders as co-design participants in chatbot development. We explored how migrants can be empowered in designing a chatbot that supports their social integration. Using a co-design approach, we conducted a series of activities with migrants and other stakeholders (i.e., online questionnaires, empathy probes, surveys, and co-design workshops) to first understand their expectations regarding chatbots, and then co-design a personality-driven chatbot. We found that chatbot personality can drive co-designing a chatbot as design goals, design directions, and design criteria.
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Today's chatbot design practice follows a well-established workflow of identifying functionality or persona, creating a dialogue flow template, filling the template with supervised NLP models, and iterating.
“Today's chatbot design practice-i.e., designing multi-turn conversational interactions-follows a well-established workfow [12,13,24,25,39,44].”
From Why Johnny Can’t Prompt: How Non-AI Experts Try (and Fail) to Design LLM Prompts (2023) · cites this paper as [12]
The Participants and Procedure section describes designing a chatbot persona and sketching conversation flows, so the paper supports those elements of the claimed process. It does not establish that this is a well-established workflow across today's chatbot practice or describe filling dialogue templates with supervised NLP models. The Context section describes its implemented prototype as a one-turn question-answering system, rather than a multi-turn implementation. (LLM, conf=0.85)
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Why Johnny Can’t Prompt: How Non-AI Experts Try (and Fail) to Design LLM Prompts
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- Authors
- Chen, Z., Lu, Y., Nieminen, M. P., & Lucero, A.
- Affiliations
- Aalto University (FI)
- Venue
- Proceedings of the 2020 ACM Designing Interactive Systems Conference
- Publisher
- ACM
- Published
- 2020-07-03
- Pages
- 219-230
- OpenAlex
- W3039973605
- Cited by
- 61
- References
- 26
- Citations by year
- 2026: 4 · 2025: 12 · 2024: 14 · 2023: 14 · 2022: 14 · 2021: 3
- FWCI
- 2.96
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Designing Interactive Systems Conference (publishedVersion, cc-by-nc-sa)
- Aaltodoc (Aalto University) (submittedVersion, other-oa)
- Funders
- Technische Universität Berlin
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- chatbots, migrants, social integration, co-design, chatbot personality, information seeking, information overload, information portal, stakeholder engagement, chatbot development
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