AI in the Backseat

Artificial intelligence is advancing at a velocity that challenges not only how organizations adopt technology, but how they preserve scientific rigor, decision ownership, and human judgment. CLAIR was established in response to this widening gap — not as a technology showcase, but as a cross-industry forum to examine how AI reshapes research-intensive work through four interconnected perspectives: AI and the Scientific & Engineering Method; Leadership, Governance, and Accountability; Critical Thinking in Algorithmic Environments; and Organizational and Cultural Transformation in R&D.

Drawing on insights from the 2023–2024 research project on AI in life sciences and healthcare, this opening keynote presents a pragmatic view of both measurable gains and less visible risks emerging from rapid AI implementation. While efficiency and analytical scale have improved, subtle erosion of methodological discipline, accountability clarity, and reflective practice has also been observed. Although grounded in life sciences, these patterns proved highly recognizable across other research-intensive organizations, indicating broader relevance beyond a single sector.

A central metaphor frames the discussion: if accountability matters, AI must remain a backseat research assistant rather than the driver. CLAIR is not only a forum for reflection, but a space where academics and practitioners jointly shape a forward-looking CLAIR Research Agenda, highlighting critical questions that are often visible in rapid AI adoption yet insufficiently examined across industries. The keynote sets the tone for the conference by inviting participants to consider how speed, science, and stewardship can coexist — and how thoughtful leadership can transform rapid acceleration into sustainable progress.