1.7 Ethical Considerations
Ethics play a very important role in study design and data collection procedures, especially when humans and animals are the observational units. In the United States, the Belmont Report is the main federal document that provides the “Ethical Principles and Guidelines for the Protection of Human Subjects of Research”. The three fundamental ethical principles for using any human subjects for research are:
Respect for persons: This principle is about protecting the autonomy of all people and treating them with courtesy and respect and allowing for informed consent. Researchers must be truthful and conduct no deception;
Beneficence: This principle is the philosophy of “do no harm” while maximizing benefits for the research project and minimizing risks to the research subjects; and
Justice: This principle is about ensuring reasonable, non-exploitative, and well-considered procedures are administered fairly — the fair distribution of costs and benefits to potential research participants — and equally.
For a brief, limited history of ethical regulation in human research, see https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3593469/. A few key moments in international history are
- Nuremberg Code (1948) in response to medical experiments in Germany performed without consent
- Declaration of Helskinki (originated in 1964 and frequently revised) established by World Medical Association.
- The Belmont Report written in response to the Tuskegee Syphilis Study (1932 - 1972).
- Common Rule (1981) is regulatory policy which all U.S. government-funded research and nearly all U.S. academic institutions must abide.
Macalester College has an Institutional Review Board (IRB) that oversees research at Macalester that includes human participants (see: https://www.macalester.edu/irb/).
Throughout this class, we are going to stop and think about the ethical considerations of the many parts of statistical practice, ranging from data collection to model prediction.
Ethics are the norms or standards for conduct that distinguish between right and wrong. In particular, we are going to consider the ethics of
- How the data are collected
- Random assignment to treatments
- Data storage
- Data privacy
- Data use
- Choice of sample data used for predictive modeling
- Use of predictive modeling
We are going to pay extra attention to negative consequences of the above that may disproportionately impact marginalized groups of people.
Throughout the semester, you will be asked to think about answers to the question: “What are the ethical considerations for this data set/analysis?” Like in other disciplines, the choices we make will be biased by our life experiences. Throughout this class, let us be mindful in increasing our awareness of the real consequences caused by choices we make in Statistics.