Helena A. Haxvig, Vincenzo D’Andrea, Maurizio Teli
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(https://doi.org/10.55612/s-5002-068-001)
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Abstract
In this conceptual paper, we synthesize findings from four studies at the intersection of Participatory Design (PD) and generative AI to articulate a coupled path: PD is suited for evaluating AI through lived experience; insights inform AI-supported co-creation (e.g., enacted/synthetic personas); and PD, in turn, designs and validates these tools. We show that AI-generated and -enacted personas can widen perspective but are not recommended as substitutes for people. Based on the cross-cutting lessons learned from the four studies we outline strategies and care practices for responsible use of synthetic personas, introducing a layered bidirectional model illustrating how PD values should form use of these instruments while knowledge acquired from use can in turn inform reconfigurations of PD practices and values. This strategy positions PD as both shaper and steward of generative AI in design.
Keywords: Participatory Design, AI, Generative AI, Synthetic Personas, Co-Creation, Evaluation, Ethics, Interactive Personas, Bias.
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Summary generated by AI
The paper argues that Participatory Design (PD) must evolve from simply using or avoiding Generative AI to becoming its shaper and steward. It proposes a “coupled path” where PD is used to evaluate AI bias through lived experience, while GenAI-supported tools (like synthetic personas) are used to augment—but never replace—human co-creation. The goal is to move beyond the “AI versus human” debate toward a model of human-centered augmentation governed by strict ethical care practices.
1. The risk of “user research without the user”:
The authors highlight a growing industry trend of using Large Language Models (LLMs) to generate “synthetic users” for speed and convenience.
• The Problem: Commercial tools often pitch these AI proxies as a way to conduct research without involving real people.
• The Critique: Relying on these error-prone proxies risks displacing real human participation and silencing marginalized voices.
2. What is a “Coupled Path” for PD and AI?
The paper defines a recursive relationship between these two fields:
• PD evaluating AI: Designers and users use their lived experiences to identify the deep-seated biases and political categories embedded in AI models.
• AI supporting PD: These insights inform the creation of AI tools (like interactive personas) that can help designers “think” and speculate.
• PD validating tools: PD must then design the safeguards to ensure these AI tools do not lead to over-reliance or stereotyping.
3. Lessons from Four Studies:
Through four experimental studies, the authors identified how Large Language Models actually behaves when it comes to the generation and enactment of synthetic personas:
• Bias and stereotypes: AI often defaults to traditional gender roles (e.g., men as ambitious leaders, women as caregivers) and struggles with non-Western cultural nuances.
• Provocative Boundary Objects: When personas were “enacted” live by AI, they served as powerful “thinking partners” that helped designers notice perspectives they had overlooked.
• Inclusive Speculation: By co-creating synthetic queer personas with the LGBTQ+ community, and bringing them into an interactive sessions with a tech CEO, researchers supported the examination of how their systems might fail non-normative users.
4. Proposed Layered Bidirectional Model:
The paper introduces a structured framework to integrate AI into design responsibly:
• PD Values (The Foundation): High-level commitments to inclusion, equity, agency, and accountability.
• Care Practices (The Governance): Operational rules like non-substitution, co-creation/validation with real communities, and provenance.
• Instruments (The Tools): The actual activities, such as bias evaluation workshops or interacting with LLM-enacted synthetic personas.
5. Critical Warnings: The “Believability Hazard”:
The authors warn against the “fluency-authority” trap:
• Fluent but unfounded: LLMs are so good at producing believable, polished text that designers may accept a convincing simulation as substitute for actual lived experience.
• Non-substitution Principle: Synthetic personas should be considered “governed adjuncts”—they are useful for rehearsing workshops or opening dialogue, but they can never justify a final design decision.
Main takeaway
Future design processes should not choose between humans or AI, but rather use community-validated AI tools as speculative provocations that remain strictly under the governance of participatory values.
In one sentence:
We urge a move from “AI as a user replacement” to “AI as a governed provocation” where real people, not proxies, remain the true locus of legitimacy.
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