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Transparency and Explainability
Demanding clarity on how algorithms make decisions.
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SUMMARY - Transparency and Explainability

A person is denied a loan and asks why. The bank's representative explains that the decision was made by an algorithm but cannot say what factors drove the denial or how the applicant might improve their chances. A defendant receives a longer sentence based partly on a risk assessment tool that assigns them high likelihood of reoffending, but neither defendant nor judge can examine what variables produced that score.

Alberta
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This thread documents how changes to Transparency and Explainability may affect other areas of Canadian civic life. Share your knowledge: What happens downstream when this topic changes? What industries, communities, services, or systems feel the impact? Guidelines: - Describe indirect or non-obvious connections - Explain the causal chain (A leads to B because...) - Real-world examples strengthen your contribution Comments are ranked by community votes. Well-supported causal relationships inform our simulation and planning tools.
Alberta
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