Career Development Seminar Series: Leveraging Racial Equity Data in Research


Unconscious bias affects translational research, scientific and operational principles underlying each step of the translational process, and ultimately individual and public health. With respect to racial data, algorithmic bias built into predictive models and re-presented via equity dashboards, may yield unintended second-order consequences that subjugate planned first-order intentions. Join your colleagues to discuss leveraging racial data, in research, with equity-minded intentionality.

Seminar Learning Objectives

At the conclusion of this seminar, you should be able to: 

  • Engage in impactful exchanges about unconscious bias, in research contexts; 
  • Develop strategies for leveraging racial data in research with equity-mindedness; 
  • Recognize, interrogate, and mitigate algorithmic biases that inform and guide research and decisions, thereby perpetuating inequities in health care access and outcomes; and 
  • Critically examine structural racism that contributes to and is reflected by data, modeling strategies, and interpretive schemas in clinical research and translational sciences.

Implicit Association Test:



NIH Funding Acknowledgment: Important - All publications resulting from the utilization of SC CTSI resources are required to credit the SC CTSI grant by including the NIH funding acknowledgment and must comply with the NIH Public Access Policy.