Non-Functional Tradeoffs, Law and Society

Machine learning (ML) has revolutionized many aspects of our lives, from healthcare to transportation, and from finance to entertainment. However, the increasing reliance on ML algorithms has raised a number of important ethical, legal, and social issues that require attention from researchers and practitioners in various disciplines. The tradeoffs between various non-functional aspects, such as resource-efficiency, fairness, and privacy, are becoming more and more important as ML systems are deployed in real-world settings. The ethical and legal implications of using ML in decision-making, such as hiring or lending, are also a topic of growing concern. Moreover, ML algorithms can have unintended consequences that affect different groups of people in different ways, and it is important to identify and mitigate such biases.

To address these issues, the First Interdisciplinary Workshop on ML, Law and Society aims to bring together researchers and practitioners from different disciplines, including computer science, law, philosophy, sociology, and psychology, to discuss the non-functional tradeoffs, ethics, and law related to ML. The workshop will provide a forum for participants to share their latest research, exchange ideas, and collaborate on future projects.

The track on Non-Functional Tradeoffs, Law and Society deals with societal implications of ML and AI techniques broadly conceived; how to design intervention strategies on multiple non-functional tradeoffs; and furthering our understanding of ML and AI from an interdisciplinary perspective (philosophy, law, social science).

A non-exhaustive list of themes of the workshop track includes:

• How to balance competing goals such as resource-efficiency, fairness, privacy, and interpretability in ML models

• How to incorporate user preferences and societal values into the decision-making process

• Novel methodologies, formalisms and understanding for individual non-functional tradeoffs

• Identification of ethical considerations in the design and deployment of ML systems

• Ethically-principled ML models 

• Methodologies to reason about, and implement, ethical concepts and contrasting viewpoints in computer systems and ML

• Ethical challenges of using machine learning in sensitive domains (e.g., healthcare, criminal justice, finance)

• The role of law and policy in shaping the development and use of ML systems

• Regulatory approaches to ensure ethical and trustworthy AI

• Legal challenges arising from the use of ML in decision-making (e.g., bias, discrimination, opacity)

• Issues in data protection law and how it relates to ML and AI

• New conceptualizations and understanding of ML algorithms through the lens of sociology, psychology, philosophy...

• Collaborative efforts to design and deploy ML systems that are aligned with societal values

• Lessons learned from interdisciplinary efforts in other domains (e.g., sustainability, public health) and how they can be applied to the ML and society domain

Keynote speakers

• Prof. Vaishak Belle, University of Edinburgh, https://vaishakbelle.github.io/about/

• Atte Ojanen, MSocSc, University of Helsinki, https://demoshelsinki.fi/ihmiset/atte-ojanen-en/

• Prof. Giovanni Comande', Scuola Superiore Sant'Anna, https://www.santannapisa.it/it/giovanni-comande

Program Committee

• Prof. Roberto Esposito, Computer Science Department, University of Torino

• Shuyi Yang, Ph.D. Candidate, Computer Science Department, University of Torino

• Xenia Heilmann, Ph.D. Student, Computer Science Department, Johannes Gutenberg-Universität Mainz

• Prof. Ruggero Pensa, Computer Science Department, University of Torino

• Prof. Mirko Marras, University of Cagliari

• Valentin Henkys, Ph.D. Student, Computer Science Department, Johannes Gutenberg-Universität Mainz

• Francesca Gennari, PhD, Sant'Anna School of Advanced studies

• Sophie Noiret, Ph.D. Student, Vienna University of Technology, Computer Vision Lab

• Selen Yakar, Ph.D. Student, University of Cologne, Law Department

Call for Papers

Paper formatting instructions are available here: Call for Papers
Submissions are gathered via the Microsoft CMT Instance of the ECML 2023 Workshops. You can create a new submission here: https://cmt3.research.microsoft.com/ECMLPKDDworkshop2023/Track/15/Submission/Create

NOTE: when submitting, please choose the track on 'Non-Functional Tradeoffs, Law and Society'. For any questions, please contact mcerrato@uni-mainz.de.