What Does Success Look Like? Catalyzing Meeting Intentionality with AI-Assisted Prospective Reflection

TL;DR

This paper introduces a novel AI-powered tool called Meeting Purpose Assistant (MPA) that encourages users to reflect on and articulate the purpose and challenges of upcoming meetings, aiming to improve meeting effectiveness.

Contribution

The paper presents the design and evaluation of the MPA, a generative AI-based system that supports personalized prospective reflection in meetings, addressing a gap in existing meeting technologies.

Findings

Clarified meeting purposes and challenges

Enhanced preparation and communication among participants

Proposed design considerations for AI-assisted meeting reflection

Abstract

Despite decades of HCI and Meeting Science research, complaints about ineffective meetings are still pervasive. We argue that meeting technologies lack support for prospective reflection, that is, thinking about why a meeting is needed and what might happen. To explore this, we designed a Meeting Purpose Assistant (MPA) technology probe to coach users to articulate their meeting's purpose and challenges, and act accordingly. The MPA used Generative AI to support personalized and actionable prospective reflection across the diversity of meeting contexts. Using a participatory prompting methodology, 18 employees of a global technology company reflected with the MPA on upcoming meetings. Observed impacts were: clarifying meeting purposes, challenges, and success conditions; changing perspectives and flexibility; improving preparation and communication; and proposing changed plans. We also identify perceived social, temporal, and technological barriers to using the MPA. We present system and workflow design considerations for developing AI-assisted reflection support for meetings.