AI supported decision making

Artificial intelligence (AI) has become a transformative force in decision-making across sectors ranging from healthcare and finance to energy, transportation, and regulation. The promise of AI lies in its ability to process vast amounts of data quickly, uncover hidden patterns, and support evidence-informed decisions in ways that humans alone cannot easily achieve. Yet the risks are substantial: algorithmic bias, lack of transparency, data quality issues, and the potential for overreliance on automated systems can undermine both trust and outcomes.

Decision-makers face the challenge of balancing innovation with accountability. Governments are under pressure to regulate AI systems in a way that ensures fairness, protects privacy, and safeguards against unintended harms, while private sector actors must integrate AI responsibly to maintain public confidence and regulatory compliance. Civil society advocates and media voices further amplify concerns about equity, explainability, and the ethical boundaries of AI.

Risk sciences play an essential role in navigating this landscape. Through structured risk assessment, sensitivity analysis, and transparency frameworks, risk science provides tools to evaluate the reliability and limitations of AI systems. By embedding scientific rigor into the development and deployment of AI, stakeholders can better understand system vulnerabilities, identify where human oversight is indispensable, and ensure that decisions remain aligned with societal values.

RSI is dedicated to supporting the responsible integration of AI into decision-making, offering the experience and expertise necessary to guide this rapidly evolving sector.