Responsible Use of Student Data

  1. “It is crucial to address bias in predictive models, ensure the statistical significance of predictions beyond race, ethnicity, and socioeconomic status, and forbid the use of algorithms that produce discriminatory results. An algorithm should never be designed to pigeonhole any one group” (Ekowo & Palmer, 2017, p.10). http://kresge.org/sites/default/files/library/predictive-analytics-guidingprinciples.pdf (PDF)  ↩︎
  2. See also: http://registrar.ucsc.edu/records/privacy/ and https://its.ucsc.edu/policies/index.html. ↩︎

Last modified: Jan 23, 2025