From the course: Agentic AI Fundamentals: Architectures, Frameworks, and Applications
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Ethical frameworks and considerations in AI
From the course: Agentic AI Fundamentals: Architectures, Frameworks, and Applications
Ethical frameworks and considerations in AI
- Imagine if the press discovered that a system which was charged with approving bank loans for a major bank brand was turning down loan applications for people of a certain race. That would be illegal and embarrassment for the bank, and just plain wrong. Ethics needs to factor into the design, build, deployment, and operations of Agentic AI systems. This requires that your organization define how it sees fairness, bias, transparency, accountability, privacy, and data protection. Once that work is done, ethical frameworks in Agentic AI can be designed. So how do we ensure fairness with frameworks? Fairness frameworks help developers design systems that minimize bias within AI systems. These direct agents on identifying and reducing biases by ensuring data sets represent diverse, inclusive perspectives. We're training the bias out of our agents and when done right, all users are treated equitably regardless of race, gender, or age. However, it is a common idea in ethics that a system…