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 *