Ethical AI & Responsible Agent Development
This program focuses on the ethical considerations in developing and deploying AI agents, including bias, transparency, accountability, and safety. Explores methods for risk mitigation and responsible AI governance.
Pre-Requisite
- Core Concepts of Agentic AI (or equivalent general AI knowledge)
- Strong understanding of ethical guidelines.
Course Outline
- 2 Sections
- 11 Lessons
- 2 Days
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- DAY 1 - Understanding Ethical Challenges in Agentic AI5
- 1.1Review of General AI Ethics (Bias, Fairness, Privacy, Explainability)
- 1.2Specific Ethical Challenges of Autonomous Agents (Unintended consequences, agency, control)
- 1.3Identifying and Mitigating Bias in LLMs and Agent Decision-Making
- 1.4Data Privacy and Security in Agentic Systems
- 1.5Case Studies: Ethical failures and successes in AI agent deployment.
- DAY 2 - Responsible AI Governance & Best Practices6
- 2.1Frameworks for Responsible AI Development
- 2.2Transparency and Explainability in Agent Behavior
- 2.3Accountability and Human Oversight for Agents
- 2.4Safety Engineering for AI Agents (Guardrails, testing for harmful outputs)
- 2.5Establishing AI Governance Policies and Procedures
- 2.6Workshop: Developing a Responsible AI checklist for an Agentic AI project.
About Us
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