Uncovering Bias in AI: Join the 4th Workshop on Bias and Fairness in AI
The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) is hosting the 4th Workshop on Bias and Fairness in AI (BIAS ’24) to address the growing importance of fairness in machine learning. This year’s workshop aims to explore the broader perspective of fairness, taking legal and societal implications into account and involving different stakeholders in the design process of fair algorithms.
Submit your research on various topics, including supervised learning, unsupervised learning, ranking, generative models, and more. Interdisciplinary work bridging Computer Science with fields like Human-Computer-Interaction, Law, and Social Sciences is especially welcome. Contributions may focus on the fairness auditing/assessment of ML systems or the design of fairer algorithms.
The workshop will accept two types of submissions: full papers (max. 14 pages, excluding references) and abstracts of already published work (max. 2 pages, excluding references). All papers must be anonymized and formatted according to the Springer LNCS guidelines. At least one author of each accepted paper is required to attend the workshop to present.
Don’t miss the opportunity to share your insights and learn from other experts in the field. Visit the official website for more information, and stay tuned for the submission website announcement.
Important dates:
- Paper Submission Deadline: June 15, 2024
- Paper Notification Deadline: July 15, 2024
- Workshop Date: September 9 or 13, 2024