The Privacy-Bias Tradeoff: Data Minimization and Racial Disparity Assessments in US Government

J King, D Ho, A Gupta, V Wu… - Proceedings of the 2023 …, 2023 - dl.acm.org
An emerging concern in algorithmic fairness is the tension with privacy interests. Data
minimization can restrict access to protected attributes, such as race and ethnicity, for bias …
被引用次数：7 相关文章
[PDF] stanford.edu

[PDF][PDF] The Privacy-Bias Tradeoff: Data Minimization and Racial Disparity Assessments in US Government

A Gupta, VY Wu, H Webley-Brown, J King, DE Ho - 2023 - hai.stanford.edu
An emerging concern in algorithmic fairness is the tension with privacy interests. Data
minimization can restrict access to protected attributes, such as race and ethnicity, for bias …
[PDF] stanford.edu

[PDF][PDF] The Privacy-Bias Tradeoff: Data Minimization and Racial Disparity Assessments in US Government

A Gupta, VY Wu, H Webley-Brown, J King, DE Ho - 2023 - dho.stanford.edu
An emerging concern in algorithmic fairness is the tension with privacy interests. Data
minimization can restrict access to protected attributes, such as race and ethnicity, for bias …

The Privacy-Bias Tradeoff: Data Minimization and Racial Disparity Assessments in US Government

A Gupta, VY Wu, H Webley-Brown, J King, DE Ho - 2023 - policycommons.net
Government-wide standards for collecting data on race and demographic data access to
teams conducting an assessment (most ethnicity were established by the OMB's 1977 …
[PDF] mit.edu

[PDF][PDF] The Privacy-Bias Tradeoff: Data Minimization and Racial Disparity Assessments in US Government

J King, D Ho, A Gupta, V Wu, H Webley-Brown - 2023 - dspace.mit.edu
An emerging concern in algorithmic fairness is the tension with privacy interests. Data
minimization can restrict access to protected attributes, such as race and ethnicity, for bias …