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Advancing Ethical Considerations for Data Science in Injury and Violence Prevention
Nimi Idaikkadar1, Eva Bodin2, Preetam Cholli3
1Division of Injury Prevention, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Public Health Reports (Washington, D.C. : 1974)
|January 21, 2025
Summary
Public health data scientists must address ethical considerations in injury and violence prevention projects. Key domains include privacy, stewardship, justice, and inclusivity to prevent negative consequences.
Area of Science:
- Public Health
- Data Science
- Bioethics
Background:
- Data science offers novel methods and data sources for public health insights.
- Injury and violence prevention research increasingly utilizes data science.
- Ethical challenges arise from using new data sources and methods.
Purpose of the Study:
- To describe ethical considerations for data scientists in public health injury and violence prevention.
- To prevent unintended ethical, legal, and social consequences.
- To provide a framework for ethical analysis in data science projects.
Main Methods:
- Reviewed foundational bioethics and public health ethics literature.
- Organized ethical concepts into broad ethical domains through discussions.
- Developed guiding questions for ethical analysis within each domain.
Main Results:
- Identified four key ethical domains: privacy, responsible stewardship, justice as fairness, and inclusivity and engagement.
- Determined all identified domains hold equal importance.
- Provided examples of ethical considerations, such as identifying project goals, assessing re-identification risks, and minimizing data bias.
Conclusions:
- Data science in public health requires careful ethical consideration.
- Addressing ethical issues proactively is crucial for injury and violence prevention.
- Recommended identifying and addressing relevant ethical issues in public health data science projects.
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