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EE-RDS 2021 : Ethics and Explainability for Responsible Data Science (EE-RDS)


When Oct 27, 2021 - Oct 28, 2021
Where Online - Johannesburg, South Africa
Submission Deadline Sep 30, 2021
Categories    artificial intelligence   data science   ethics   multidisciplinary

Call For Papers

Please register for the conference here:

- Yoshua Bengio (Department of Computer Science and Operational Research, Université de Montréal, IVADO, CIFAR, Scientific Director - Mila)
- Geralyn Miller (Sr. Director of the AI for Good Research Lab at Microsoft)
- Mark Parsons (Editor in Chief, Data Science Journal, University of Alabama)

Is Data Science a new approach to solving problems, one that applies across disciplines as various as physics, sociology and linguistics? Or are machine learning, deep convoluted neural nets, and other exciting phrases just statistics on steroids?

Recent developments in Data Science broadly construed, and the products these have yielded (or promise to yield) are undeniably exciting: identifying and predicting disease, personalized healthcare recommendations, automating digital ad placement, predicting incarceration rates, and countless other tools have attracted a lot of attention. But what about the process behind these products? Are these amazing feats based on traditional scientific discoveries? Or does the problem-solving approach which is being implemented have an even wider range of applicability than we could imagine? While the Sciences and Engineering are driving the field, traditional Humanities and the Social Sciences are also experimenting and contributing to a growing body of knowledge around the use of data. This conference seeks to understand the nature and significance of data science for traditional modes of inquiry across the full spectrum. We also seek to interrogate underlying ethical issues that arise not only in research but also when data science is relied on in decision-making – this is where notions of explainability, fairness and discrimination form part of the practical application of responsible data science.

As a launching event of the Data Science Across Disciplines Research Group at the University of Johannesburg, this 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.

All papers must be pitched in a suitably accessible way and speak to the cross-disciplinary nature of the event.

Please ensure that you have registered for the conference before submitting an abstract:

Abstract Submission: Please submit your extended abstract on the Microsoft CMT website ( and ensure that you use the IEEE abstract template provided here:

Note: You may use either the LaTeX or Word template but your extended abstract must be a minimum of 4 pages long and in .pdf format.

When you submit your extended abstract you will be asked to indicate whether you would be interested in publishing your work in IEEEXplore proceedings at a minimal fee. The authors of submissions of suitable quality will be contacted at a later stage should they indicate an interest in doing so.

Abstract Due Date: 30 September 2021

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