Papers should be submitted in accordance to the ECMLPKDD formatting instruction. Submission should be limited to 16 pages including references (following again the main conference guidelines). Papers must be written in English and are to be submitted in PDF format online via the Easychair submission interface:
Each submission will be evaluated on the basis of relevance, significance of contribution and quality by at least three members of the program committee. Submitted papers cannot be identical, or substantially similar to versions that are currently under review at another conference, have been previously published, or have been accepted for publication. All accepted papers will be included in the informal workshop proceedings and will be publicly available on the conference web site. A selection of accepted papers will be invited to submit to an open call for papers of a special issue of a journal (to be announced). At least one author of each accepted paper is required to attend the workshop to present. For the accepted papers, we will have regular talks and additional poster presentations to foster further discussions, based on local venue capabilities.
We will follow the suggestions for workshops from the ECMLPKDD website.
Workshop Paper Submission Deadline (extended):
July 02, 2020
Workshop Paper Author Notification:
August 06, 2020
Workshop Paper Camera Ready Deadline:
August 27, 2020
Workshop Program and Proceedings Online:
September 7, 2020
Workshop Date:
September 18, 2020
Jesse Russell. The Limits of Computation in Solving Equity Trade-Offs in Machine Learning and Justice System Risk Assessment
Cora van Leeuwen, Annelien Smets, An Jacobs, Pieter Ballon. Blind Spots in AI: the Role of Serendipity and Equity in Algorithm-Based Decision-Making
Tim Draws, Nava Tintarev, Ujwal Gadiraju, Alessandro Bozzon, Benjamin Timmermans. Assessing Viewpoint Diversity in Search Results Using Ranking Fairness Metrics
Atoosa Kasirzadeh, Andrew Smart. The use and misuse of counterfactuals in fair machine learning
Karima Makhlouf, Sami Zhioua, Catuscia Palamidessi. On the Applicability of ML Fairness Notions
Pieter Delobelle, Paul Temple, Gilles Perrouin, Benoît Frénay, Patrick Heymans, Bettina Berendt. Ethical Adversaries: Towards Mitigating Unfairness with Adversarial Machine Learning
Eduard Fosch Villaronga, Adam Poulsen, Roger A. Søraa, Bart H.M. Custers. Don’t guess my gender, gurl: The inadvertent impact of gender inferences