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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
PubMed
Summary
This summary is machine-generated.

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.

Keywords:
artificial intelligencebioethicsdata scienceethicspublic health ethics

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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.