Submission site opens: July 15, 2024

Submissions due: Sept 10, 2024 September 20, 2024

Notification of  acceptance: September 30, 2024

Camera Ready Submissions due for the proceedings:  November 15, 2024 (1 month after the workshop)

The 1st Methods for Teaching Ethics in Data Science (MTEDS) workshop took place on the Tufts campus in 2023. Building on its success, we are organizing a half-day workshop session at ADSA 2024 with the goal of developing a robust collection of accessible, high-quality case studies specifically designed for teaching data science ethics to undergraduate students studying data science-related fields. These case studies, together with auxiliary curricular materials we may develop, are intended to equip educators with valuable tools to engage students in critical discussions and analysis of ethical dilemmas in the field. By fostering awareness and promoting responsible practices, we can ensure that students are exposed to the ethical frameworks that can help them evaluate data science advancements and recognize when care in their implementation is required to serve humanity in an ethical and beneficial way.

We seek submissions of short original, fictional, or real-world normative case studies that explore the ethical considerations of teaching data science methodologies. While the use and evaluation of such normative case studies are common in other fields, they are a novel approach in data science. For an example case study, for tone and two example expert opinions, please see “The Lakeview Times,” an example case study written by the T-Tripods working group on teaching Ethics for Data Science. 

We are particularly interested in case studies that address the following:

  • Ethical dilemmas inherent in specific data science methodologies: This includes, among other topics, issues surrounding bias in algorithms, data privacy concerns, fairness in data collection, and responsible use of data analytics techniques. These case studies need not restrict themselves to a formal dilemma (i.e. between discrete courses of action put forward as choices) but open up an area of challenges for decision-making, design, and policy. In keeping with the theme of this year’s ADSA meeting, this year we especially warmly welcome case studies around ethics for AI. 

Please note: we are also organizing a session at the main ASDA meeting and are looking for submissions for short talks. That topic is: 

  • Challenges and opportunities in teaching data science ethics: Experience reports or position papers on this topic are both welcome and could explore effective strategies for integrating discussions of ethics in data science in the classroom with the aim of fostering a culture of ethical responsibility among data science students.
  • See the related call for submissions here.

Case studies can be submitted either as stand-alone stories or with supporting expert opinions and/or additional supporting curricular materials.

The EasyChair link for submission is here.

All submissions will undergo a peer review process by the MTEDS24 program committee. Reviewers will assess the case study based on the following criteria:

  • Clarity and Comprehensiveness: Does the case study present a clear ethical dilemma or ethical challenge related to data science methodology?
  • Relevance and Applicability: Does the case study address issues relevant to current data science practices? Is it suitable for use in a data science ethics curriculum?
  • Teaching Potential: Does the case study provide a compelling basis for class discussion and critical analysis? Does it offer opportunities for students to explore different perspectives and develop ethical reasoning skills?

All accepted case studies will be published on the ADSA24 website as part of the MTEDS24 proceedings.  Authors agree to have their case studies (with attribution) continue to be incorporated and published as part of future MTEDS curricular materials. In addition, we will select the best two submissions (from all accepted submissions) for an expert review session; this will comprise the main content of the workshop. Workshop attendees will be split into two groups, and each group will work on one of the case studies, both giving feedback to the author on the story and generating or modifying the expert opinions for that case study. They will get co-authorship credit for the produced materials that will then be published as part of the MTEDS24 proceedings. This review process will provide valuable feedback to the case study authors and further refine the case studies for broader dissemination.

Program Chairs

–       Lenore Cowen (Chair), Tufts University 

–       Thomas Arnold (Co-chair), Tufts University 

–       Muhammad Umair (Co-chair), Tufts University 

Program Committee
Anna Haensch, Tufts University
Adam Poulsen, University of Sydney
Filippo Santoni di Sio, Eindhoven University of Technology

Submission Instructions and Deadlines:

Please submit your case study as a PDF document on Easy Chair here.