Conference Agenda

As design researchers increasingly adopt generative AI tools across the research lifecycle, questions about when and how to trust these tools have become increasingly urgent to explore and address. From planning studies and generating tasks to analysing qualitative data and communicating findings, AI systems are now integrated into many aspects of design research work. However, these tools are frequently used based more on institutional demands, tool availability, and efficiency perceptions rather than on clear methodological or ethical considerations. This Conversation explores trust as a context-dependent judgment influenced by specific situations, tasks, and associated risks.

Although concerns about AI's reliability and ethics are valid, the increasing interest in these tools is understandable. Many researchers are drawn to AI for its ability to streamline labour-intensive tasks, accelerate workflows, generate new insights, or support accessibility. For instance, transcription tools, automated tagging, and language generation systems are already embedded in research workflows and often seen as low-risk or beneficial. These perceived strengths raise important questions: What value do these tools offer? Under what conditions are they helpful? And when might apparent benefits obscure potential risks?

This Conversation invites participants to examine how trust in AI is experienced, questioned, or withheld across the design research process. Rather than assuming AI tools either clearly belong in research practice or should be rejected outright, we ask where, when, and under what conditions they can play a role, and where they should not.