Standards for the Control of Algorithmic Bias

Acknowledgements * List of Tables * List of Abbreviations * Chapter One: Introduction * 1.1 Regulation of Artificial Intelligence: The European Context * 1.2 Regulation of Artificial Intelligence: The Canadian Administrative Context * 1.3 Equality Rights: Disparate Impact in ADM * 1.3.1 Case Study: Disparate Impact in the COMPAS ADM * 1.4 Situating Disparate Impact in the Charter * 1.5 The Role of Standards in Protecting Human Rights * 1.5.1 Narrowing the Scope of Administrative Law * 1.5.2 Soft Law and Its Status in Judicial Review * 1.6 Methodology * Chapter Two: Administrative Law and Standards for the Control of Algorithmic Bias * 2.1 Foundational Principles: Transparency, Deference and Proportionality * 2.1.1 Transparency * 2.1.2 Deference * 2.1.3 Proportionality * 2.2 Reasonableness Review * 2.2.1 Illustrative Scenario * 2.3 Standards to Mitigate the Creation of Biased Predictions * 2.3.1 Construct Validity * 2.3.2 Representativeness of Input Data * 2.3.3 Knowledge Limits * 2.3.4 Measurement Validity in Model Inputs * 2.3.5 Measurement Validity in Output Variables * 2.3.6 Accuracy of Input Data * 2.4 Standards for the Evaluation of Predictions * 2.4.1 Accuracy of Predictions and Inferences: Uncertainty * 2.4.2 Individual Fairness * 2.5 Chapter Summary: Proposed Standards for the Control of Algorithmic Bias * Chapter Three: Substantive Equality and Standards for the Measurement of Disparity * 3.1 The Measure of Disparity in the Prima Facie Test of Discrimination * 3.2 Legislative and Policy Approaches to the Measurement of Disparity * 3.3 The Supreme Court of Canada on Measures of Disparity in Fraser * 3.4 Disaggregated Data * 3.5 Chapter Summary: Standards for the Measurement of Disparity * Chapter Four: Implementation Recommendations * 4.1 Overview of the Standards Framework * 4.2 Implementing the Standards Framework * Chapter Five: Conclusions and Further Research * References *