Research

At AID3, we conduct research on the foundations, impact, and application of artificial intelligence in decision-making processes. Our work integrates computational, statistical, and experimental methods to examine how AI systems are designed, evaluated, and used, with the goal of promoting technologies that are more robust, trustworthy, and aligned with the needs of organizations and society.

Under this broad umbrella, AID3 focuses on three topics:

• Responsible AI and algorithmic governance: We develop methods and frameworks for fairness, accountability, transparency, auditability, and lifecycle control in AI systems used in organizational decision-making.
• Human–AI interaction and decision behavior: We study how people interpret, trust, contest, and act on algorithmic recommendations, and design AI systems that support better human judgment.
• Statistical learning and reproducible AI evaluation: We develop rigorous statistical, experimental and computational methods to make the evidence about AI systems more reliable, auditable, and reproducible.