May 18, 2023, 3–4 pm CT
Ethics Discussion Forum: Health Data Privacy and its Impact on Representation and Algorithmic Fairness
Without data, there is no modern artificial intelligence. However, getting access to data, and particularly data about a person’s biology or healthcare, can be difficult. Many factors limit health data sharing on a broad scale, with privacy being one of the principles most voiced as a concern. Our society, and the organizations that function with it, have devised a number of strategies for managing the tradeoff between health data privacy and accessibility. These include, but are certainly not limited to,
- creating online data enclaves where users are limited by the program languages and computing infrastructure support (e.g., pay per compute in the cloud),
- entering into contractual agreements with data controllers, which can be onerous to establish, maintain, and manage, and
- subjecting data to de-identification practices that reduce the likelihood that the identity of the individuals to whom the data corresponds will be recognized.
In this ethics discussion forum, we will walk through some of these strategies, as well as examples of how data sharing practices have been realized historically. Along the way, we will discuss how the tradeoffs inherent in these strategies can affect,
- which researchers have access to these data and
- the extent to which the resulting datasets can (and cannot) support health equity research
Discussion Host:

Bradley Malin, Ph.D Vanderbilt University Medical Center
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