Rethinking User Experience in Human-Centered AI: Designing for Reflective Decision-Making

As artificial intelligence (AI) systems become increasingly integrated into professional environments, they are reshaping human interaction with information systems and transforming decision-making processes. While AI technologies offer significant potential to enhance performance and efficiency, they also introduce cognitive and ethical challenges. A key concern is the tendency of users to adopt AI recommendations uncritically—particularly when interface designs emphasize automation, simplicity, and seamless experiences. These design principles, foundational to traditional user experience (UX), were not conceived with AI-driven decision support in mind. This conference calls for a paradigm shift from the canonical UX principle “Don’t make me think” to a new imperative: “Make me think.” In the context of pervasive AI, it is essential to design systems that actively foster cognitive engagement, transparency, and critical reflection, especially in high-stakes professional settings. Based on a series of NeuroIS experiments conducted at Tech3Lab, HEC Montréal, this research examines how professionals interact with AI in decision-making contexts. Findings suggest that, without intentional design interventions, users frequently rely on AI in automatic and unreflective ways. This underscores the need to rethink interface design to promote more mindful and responsible AI use. The presentation concludes with the introduction of the newly published volume The Design of Human-Centered Artificial Intelligence for the Workplace (Springer). This book provides scholars, designers, and practitioners with both conceptual foundations and practical insights for developing AI systems that are not only efficient but also aligned with human values and cognitive demands across a range of industries.