Appearing Legitimate is Not Enough: Interrogating Synthetic Agents in Representational Processes through a Participatory Design Lens

• URL: http://arxiv.org/abs/2608.17099v1
• Date: Mon, 17 Aug 2026 20:14:34 GMT
• Title: Appearing Legitimate is Not Enough: Interrogating Synthetic Agents in Representational Processes through a Participatory Design Lens
• Abstract summary: We argue that legitimacy and personhood are integral and mutually while identifying the ethical, representational, and methodological risks of using synthetic agents in representational processes.
• Score: 0.7583052519127081
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Synthetic agents built atop LLM-based foundation models are gaining popularity as substitutes for human participants across research contexts, including user-testing, market-research, computational social science, surveys, and qualitative research. We are also witnessing an extension of synthetic agents into experimental implementations of policy consultation, jury deliberation, humanitarian diplomacy, and similar contexts where human participation and representation are central to the perceived legitimacy of the institutional processes. The value of participation extends beyond informational contributions and consensus generation; participation is a necessary, legitimizing condition for democratic political institutions and processes. Treating synthetic agents as human substitutes raises serious political, representational, and ethical concerns. Participatory Design's modes of engagement --- probing, priming, understanding, and generating --- offer helpful tools for engaging with representational questions of personhood. We apply the lens to three case studies of synthetic agents substituting for personhood at varying representational scales: local policy, enterprise jury deliberation, and global diplomacy. We argue that legitimacy and personhood are integral and mutually constitutive while identifying the ethical, representational, and methodological risks of using synthetic agents in representational processes. We conclude by proposing soft and hard boundaries for designing oversight on LLMs and synthetic agents in representational processes.

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