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Enhancing Data Science Ethics Through Statistical Education and Practice
Author(s) -
Utts Jessica
Publication year - 2021
Publication title -
international statistical review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.051
H-Index - 54
eISSN - 1751-5823
pISSN - 0306-7734
DOI - 10.1111/insr.12446
Subject(s) - engineering ethics , ethical issues , data science , data quality , interpretation (philosophy) , computer science , quality (philosophy) , management science , psychology , engineering , epistemology , metric (unit) , philosophy , operations management , programming language
Summary As sources of data become more plentiful and massive datasets are easier to acquire, new ethical issues arise involving data quality and privacy, and the analysis, interpretation and dissemination of data‐driven decisions. There are numerous anecdotes involving abuses of complex data analyses and algorithms, and the impact they have had on society. In this paper, we discuss what statisticians can do to help enhance data science ethics in practice and what statistics educators can do to instil sound ethical behaviour in our students. We have opportunities to practice and teach ethical conduct relevant to all stages of the data life cycle. This paper discusses issues impacting ethical data science, with a focus on how statisticians can help raise awareness and encourage implementation of ethical best practices.