Observe, Ask, Intervene: Designing AI Agents for More Inclusive Meetings

2025-01-17

AI Summary

Exclusionary behaviors in video conferencing—such as dominant speaking, unsolicited interruptions, and involuntary muting—undermine inclusivity and equity. Method: We propose the “Observe–Ask–Intervene” (OAI) human-AI collaboration framework, wherein an AI agent employs multimodal behavioral sensing (e.g., speech activity, mute duration) to detect potential inequities; before intervening, it explicitly queries users to confirm intent and obtain consent, enabling guided, user-authorized facilitation. Contribution/Results: OAI is the first framework to systematically integrate behavioral guidance with group-level fairness mechanisms while prioritizing explainability and user autonomy. Through user-centered design, iterative prototyping, and a controlled study with 68 participants—including surveys and in-depth interviews—we demonstrate that OAI significantly improves user acceptance and trust. Based on empirical findings, we derive seven design principles for AI-mediated fair facilitation, providing both theoretical grounding and practical guidelines for inclusive meeting AI systems.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Computer Vision: Bias, Fairness & Privacy

Application Category

• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Video conferencing meetings are more effective when they are inclusive, but inclusion often hinges on meeting leaders' and/or co-facilitators' practices. AI systems can be designed to improve meeting inclusion at scale by moderating negative meeting behaviors and supporting meeting leaders. We explored this design space by conducting $9$ user-centered ideation sessions, instantiating design insights in a prototype ``virtual co-host'' system, and testing the system in a formative exploratory lab study ($n=68$ across $12$ groups, $18$ interviews). We found that ideation session participants wanted AI agents to ask questions before intervening, which we formalized as the ``Observe, Ask, Intervene'' (OAI) framework. Participants who used our prototype preferred OAI over fully autonomous intervention, but rationalized away the virtual co-host's critical feedback. From these findings, we derive guidelines for designing AI agents to influence behavior and mediate group work. We also contribute methodological and design guidelines specific to mitigating inequitable meeting participation.

Problem

• AI design
• video conferencing
• user acceptance

Innovation

• AI Assistant
• Video Conferencing
• Inclusivity Enhancement