FAILED 2026 brings together researchers and practitioners working on fairness, ethics, transparency, and model debiasing in AI and Computer Vision.

Welcome to the forefront of ethical AI innovation. In recent decades, Artificial Intelligence (AI) has experienced an unprecedented surge, marked by the development of increasingly complex machine learning models. Yet, alongside this growth comes a critical concern: the presence of biases within these models, which can perpetuate disparities and ethical dilemmas. The scientific community has increasingly turned its focus towards understanding and addressing model bias, with growing research activity across many disciplines. This surge coincides with the European Union's AI Act, emphasizing ethics, transparency, and accountability in AI systems. In response to these pressing challenges, we present the third edition of the workshop FAILED: Fairness and Ethics Towards Transparent AI: Facing the Challenge Through Model Debiasing. The workshop convenes experts and practitioners from diverse backgrounds to explore innovative strategies for rectifying biases and promoting fairness and transparency in AI systems, particularly in Computer Vision. By fostering interdisciplinary discussions and sharing cutting-edge solutions, FAILED aims to support progress towards unbiased and fair AI models. Join us at FAILED, a satellite workshop of ECCV 2026, and be part of this collaborative effort to shape a more ethical and fair AI landscape.