Research, Data and Responsibility in the Age of AI

CLAIR 2026 opens with a moderated dialogue between Dipak Kalra and Iain Buchan, two internationally respected leaders in health data science and AI-enabled research. Rather than conventional keynote presentations, the session unfolds as a structured conversation designed to set the intellectual direction of the conference.

The dialogue is framed around CLAIR’s four core perspectives: AI and the scientific & engineering method; leadership, governance and accountability; critical thinking in algorithmic environments; and organizational transformation in R&D. 

As AI transitions from analytical support to generative and predictive influence, research-intensive organizations must confront difficult questions. If algorithms increasingly propose hypotheses and shape research pathways, is the scientific method evolving, or being subtly reconfigured? When machine-generated insight informs high-stakes decisions, does accountability become clearer or more complex? Can acceleration coexist with rigor, and can scale coexist with trust? And as AI becomes embedded in everyday research practice, how do leaders preserve critical thinking and creative judgment rather than delegating them?

Drawing on decades of experience bridging academia, healthcare systems, industry, and public infrastructure, Kalra and Buchan will explore how governance, data ecosystems, and organizational leadership must mature alongside technological capability. This opening dialogue invites both researchers and practitioners into a shared examination of responsibility, evidence, and transformation  setting a reflective yet forward-looking tone for CLAIR.