Discussion: View Thread

�� Track description: https://ecis2026.it/track-descriptions/red-teaming-for-responsible-ai-challenging-ai-plans-systems-and-assumptions/

AI is rapidly reshaping the future of work, redefining organizational structures, and transforming how decisions are made. Yet, despite its immense potential, AI adoption continues to raise critical ethical and governance challenges - especially within the workplace.

Aizhan Tursunbayeva, Ward van Zoonen, and Ksenia Keplinger thus invite interdisciplinary, critical, and practice-oriented contributions:

·     Conceptualizing responsible development, implementation, and utilization of AI for employees, groups, and organizations
·      Red Teaming the assumptions embedded in AI plans, datasets, models, and adoption policies and practices
·      Revealing employee dilemmas connected with recognizing/using AI at/for work, as well as the potential workarounds they can adopt
·      Demystifying the potential and perils of AI for diversity and inclusion, including the potential for discrimination, bias, or systemic inequalities in organizations
·      Developing quantitative and qualitative approaches to understanding, measuring, and managing the impact of implementing or using AI on individuals, organizations, and society
·      Identifying and managing the potential "dark-sides" of AI, including issues related to privacy, surveillance, and employee monitoring
·      Examining spatial, temporal, and behavioral work boundaries affected by AI
·      Comparing human versus algorithmic decision-making and management
·      Studying cases on (ir)responsible uses of AI at/for work in various organizations (e.g., SMEs or multinationals) and sectors (e.g., healthcare, public, or private sector companies)
·      Developing and evaluating new and existing theories, models, methodologies, and frameworks for studying and evaluating AI in organizations on individuals, organizations, and society

Join us in critically interrogating AI's role in reshaping work and management - and in charting a path toward its more equitable and accountable use.

Track Associate Editors:

Gilda Antonelli Raluca Bunduchi Catalina Crisan Stefano Di Lauro Vicenc Fernandez Christian Fieseler Sona Gachayeva Elisabeth Kelan Dejun "Tony" Kong Matti Laukkarinen Luigi Moschera Claudia Pagliari Phoenix Van Wagoner Simon Schafheitle Marjo Siltaoja Dan-Andrei Sitar-Taut Lior Zalmanson