Description

Ethical principles guiding AI development and deployment applied to financial contexts such as lending, trading, and insurance. How biases can be introduced into AI systems through data, design, and deployment. As well as practical mitigation strategies such as data audits, inclusive design, and algorithmic transparency.

Learning Objectives

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1. Apply ethical principles to evaluate the design and use of AI systems in finance.
2. Identify common sources of bias.
3. Identify strategies for mitigation and fairness.