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Towards a Responsible AI Framework for the Design of Automated Decision Systems in DFO: a Case Study of Bias Detection and Mitigation (view source)
Revision as of 17:50, 22 December 2022
, 17:50, 22 December 2022no edit summary
('''Français''': [[Vers un cadre d’IA responsable pour la conception de systèmes décisionnels automatisés au MPO: une étude de cas de la détection et de l’atténuation des biais|Vers un cadre d’IA responsable pour la conception de systèmes décisionnels automatisés au MPO: une étude de cas de la détection et de l’atténuation des biais - wiki (gccollab.ca)]][[File:Res ai poster Dec8.jpg|alt=|center|frameless|996x996px]]
('''Français''': [[Vers un cadre d’IA responsable pour la conception de systèmes décisionnels automatisés au MPO: une étude de cas de la détection et de l’atténuation des biais|Vers un cadre d’IA responsable pour la conception de systèmes décisionnels automatisés au MPO: une étude de cas de la détection et de l’atténuation des biais - wiki (gccollab.ca)]]
== Executive Summary ==
== Executive Summary ==
Automated decision systems are computer systems that automate, or assist in automating, part or all of an administrative decision-making process. Currently, automated decision systems driven by Machine Learning (ML) algorithms are being used by the Government of Canada to improve service delivery. The use of such systems can have benefits and risks for federal institutions, including the Department of Fisheries and Oceans Canada (DFO). There is a need to ensure that automated decision systems are deployed in a manner that reduces risks to Canadians and federal institutions and leads to more efficient, accurate, consistent, and interpretable decisions.
Automated decision systems are computer systems that automate, or assist in automating, part or all of an administrative decision-making process. Currently, automated decision systems driven by Machine Learning (ML) algorithms are being used by the Government of Canada to improve service delivery. The use of such systems can have benefits and risks for federal institutions, including the Department of Fisheries and Oceans Canada (DFO). There is a need to ensure that automated decision systems are deployed in a manner that reduces risks to Canadians and federal institutions and leads to more efficient, accurate, consistent, and interpretable decisions.