DEPICT: A Framework for Ethical Reasoning in Statistics and Data Science with Case-Study Applications

• Published in: Journal of statistical theory and practice Vol. 19; no. 2
• Main Authors: Van Mullekom, Jennifer, Davidson, Mario
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.06.2025
• Subjects: Mathematics and Statistics; Original Article; Probability Theory and Stochastic Processes; Statistical Theory and Methods; Statistics; DEPICT; ASA guidelines for ethical statistical practice; Ethics; McMaster problem solving methodology; Ethical reasoning; Ethical decision–making; Statistical practice
• ISSN: 1559-8608; 1559-8616
• DOI: 10.1007/s42519-025-00442-6

Ethics knowledge and applied ethical reasoning skills are essential for the modern-day statistical practitioner and data scientist. In this article, we introduce DEPICT, a novel, applied ethical reasoning framework for statistics and data science, to facilitate the transformation of novice ethical reasoners to experts as they encounter dilemmas in their data-centric workplace. We provide foundational knowledge on ethics, professional ethical guidance, and ethical reasoning as background for the framework. DEPICT is synthesized from the McMaster Problem Solving Methodology from the engineering literature as well as other ethical reasoning frameworks in the literature. It has six phases with associated steps: Define, Explore, Plan, Implement, Contemplate, and Transcend. We present a complex nuanced DEPICT case-study analysis, which can be used for instruction or professional development in industry, government, or academic settings. A second case-study analysis is presented in the Supplementary Material. A third case study, accompanied by facilitator notes, is also provided in the Supplementary Material. We also outline the competencies required for developing effective ethical reasoners.