Identify a fair configuration for controlled comparisons of multi-agent discussions

Identify a fair configuration of agent participation—including speaking length, speaking speed, and speaking frequency—and use it in controlled comparison studies to isolate the effects of different dimensions of AI participation in multi-human, multi-agent ethical discussions.

Background

The evaluation used a single 3:3 human–AI configuration without a control or comparison group. The authors explain that alternative comparisons would introduce confounds, while different agent behaviors could themselves alter discussion quality and learning outcomes.

Because no established guidelines exist for configuring multi-agent, multi-human discussions, the paper leaves unresolved what constitutes a fair level and form of agent participation. Establishing such a configuration is necessary for controlled studies that can distinguish the effects of AI presence, group size, and specific participation dimensions.

References

Future work should identify a “fair” agent configuration and pursue controlled comparison studies that can better isolate the effect of different dimensions of AI participation from these confounds.

— Ethics Training Agents: Facilitating Group-Based Ethics Education with Role-Playing and Discussion for Ethical Reflection and Exploration  (2609.11529 - Seo et al., 10 Sep 2026) in Section 6.4, “Limitations and Future Work”

Whether the interface should encode this or leave it to the user is open: imposed sequencing risks rigidity, purely user-directed sequencing risks the avoidance patterns the design is meant to counteract.

— Beyond the Monolithic Interface: A Research Agenda for Plural Conversational AI  (2610.12878 - Ghosh et al., 9 Oct 2026) in Section 5.5, “The Design Space of Multi-Persona Interfaces,” p. 17