Ethics and Explainability for Responsible Data Science

his conference brings together reflections on both the actual and potential impact of data science across disciplines and sectors. Submissions are welcome from any disciplinary background, with a focus on scientific contributions, conceptual themes, and reflections within the areas of:

1. Responsible Data Science: Reliable and Trustworthy approaches for data engineering, data science and modern machine learning.
2. Algorithmic Fairness, Transparency, and Explainability.
3. Social and Ethical aspects of Responsible Data Science.
4. Use cases illustrating the cross-disciplinary nature of the field of Data Science.

https://futureofknowledge.org/ethics-and-explainability-for-responsible-data-science-ee-rds/