Back to Top
Standards for the Control of Algorithmic Bias: The Canadian Administrative Context
Governments around the world use machine learning in automated decision-making systems for a broad range of functions. This book seeks to answer the question: what standards should be applied to machine learning to mitigate disparate impact in automated decision-making?
| Author(s) | By Natalie Heisler, Maura R. Grossman. |
|---|---|
| Publisher | Taylor & Francis Ltd |
| Format | Hardback |
| Pages | 96 |
| Published in | United Kingdom |
| Published | 4 Jul 2023 |
| Availability | POD |
Governments around the world use machine learning in automated decision-making systems for a broad range of functions. This book seeks to answer the question: what standards should be applied to machine learning to mitigate disparate impact in automated decision-making?
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
Natalie Heisler has advised public- and private-sector organizations around the world in the strategy and deployment of data, analytics, and artificial intelligence for more than twenty years. Natalie brings a unique, multidisciplinary perspective to her
