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Principle D: Responsibilities to Research Subjects

  
The ASA Committee on Professional Ethics seeks input on the Ethical Guidelines for Statistical Practice, which are permanently linked here:
http://www.amstat.org/ASA/Your-Career/Ethical-Guidelines-for-Statistical-Practice.aspx


If you would like to contribute a recommendation for revision to the Guidelines, or for a comment for the linked discussion, we have created discussion threads for each of the Guidelines' individual principles. Please comment on the principle(s) most directly related to your suggestion(s).

Your suggestions should be as specific and complete as possible so that the Committee or its designated Working Group can review and consider your suggestions and input. All suggestions received through these discussion threads will be considered by the Committee.


The ethical statistician protects and respects the rights and interests of human and animal subjects at all stages of their involvement in a project. This includes respondents to the census or to surveys, those whose data are contained in administrative records, and subjects of physically or psychologically invasive research.
The ethical statistician:

  1. Keeps informed about and adheres to applicable rules, approvals, and guidelines for the protection and welfare of human and animal subjects.
  2. Strives to avoid the use of excessive or inadequate numbers of research subjects, and excessive risk to research subjects (in terms of health, welfare, privacy, and ownership of their own data), by making informed recommendations for study size.
  3. Protects the privacy and confidentiality of research subjects and data concerning them, whether obtained from the subjects directly, other persons, or existing records. Anticipates and solicits approval for secondary and indirect uses of the data, including linkage to other data sets, when obtaining approvals from research subjects, and obtains approvals appropriate to allow for peer review and independent replication of analyses.
  4. Knows the legal limitations on privacy and confidentiality assurances and does not over-promise or assume legal privacy and confidentiality protections where they may not apply.
  5. Considers whether appropriate research-subject approvals were obtained before participating in a study involving human beings or organizations, before analyzing data from such a study,and while reviewing manuscripts for publication or internal use.The statistician considers the treatment of research subjects (e.g., confidentiality agreements, expectations of privacy, notification, consent, etc.) when evaluating the appropriateness of the data source(s).
  6. In contemplating whether to participate in an analysis of data from a particular source, refuses to do so if participating in the analysis could reasonably be interpreted by individuals who provided information as sanctioning a violation of their rights.
  7. Recognizes that any statistical descriptions of groups may carry risks of stereotypes and stigmatization. Statisticians should contemplate, and be sensitive to, the manner in which information is framed so as to avoid disproportionate harms to vulnerable groups.
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03-23-2019 17:15

In previous iterations of the Guidelines (GLs) (through 2018), the focus has been on research subjects. However, data science does not consider those contributors of information or data to be "subjects" in any defined sense; they also do not generally consider what they do to be scientific if it is conducted in a business context. These principles should extend to all those who contribute data (i.e., they're asked for it and give consent to contribute it) but also to those whose data is unknowingly obtained. Particular elements of the principle "responsibility to research subjects" could come into play (i.e., that in deciding whether to analyze "data from a particular source", the ethical statistician/data scientist "refuses to do so if participating in the analysis could reasonably be interpreted by individuals who provided information as sanctioning a violation of their rights". Either the top-level principle needs reconsideration, or other revisions are needed to ensure that data scientists do in fact make it to element 6 in this list - given the current label ("responsibilities to research subjects") because they do not consider that they have any responsibility to "research subjects" and/or are not actually doing research.