Data-driven science, ethics and risk: Building knowledge of key ethics–risk intersections relevant to public sector decision-making

Risk decision-making has evolved from a vernacular focused on risk assessment and management to fully integrated approaches designed to inform risk acumen. Consequently, there has been a renewed interest, particularly in areas with significant paradigm shifts, to understand the complex nature of the underlying intersections between data, ethics and risk. For example, building more awareness of the risk and ethical implications for applying artificial intelligence for generative (content creation) and agentic (decision-making) purposes or relying on next generation risk assessments grounded in models reflective of the Three Rs principles (i.e. the replacement , reduction and refinement of animal studies). Global thinkers in risk science and analysis have also developed frameworks and models, such as the Projector Model, to show the complex nature of these intersections relevant to public health and regulatory risk decision-making. This Comment article builds on this work by sharing real-life examples from an expert panel discussion, which occurred during the Chief Data & Analytics Officer (CDAO) Canada Public Sector 2025 meeting. These panel members relied on the Projector Model to navigate the discussion in a session titled ‘Data-driven science — Transforming risk assessment and regulation in the public sector’ . The examples showed how institutional values and norms serve as foundational elements for risk decision-making, and highlighted that data-driven science, especially that based on novel approaches and technologies, needs careful consideration from an ethical and risk perspective.