AI Governance: Mitigating Risks in the Enterprise

Overview

Join an enlightening session on "AI Governance:

Mitigating Risks in the Enterprise," where you can delve into the critical elements of establishing an effective AI governance framework in any enterprise. Learn how to balance regulatory compliance, ethical imperatives, and return on investment in artificial intelligence initiatives.

This course, hosted on YouTube with expertise-driven insights from Fidelity Investments, will guide you through the complexities of managing AI systems responsibly and efficiently.

It's a must-attend for professionals seeking to harness AI's potential while mitigating associated risks.

Syllabus

• Introduction to AI Governance
Definition and importance of AI governance
Overview of enterprise AI applications
Case study: AI at Fidelity Investments
• Regulatory Compliance in AI
Understanding AI-related regulations
Data privacy and protection standards (e.g., GDPR, CCPA)
Compliance strategies and frameworks
• Ethical Considerations in AI
Identifying biases in AI systems
Fairness, accountability, and transparency in AI
Developing ethical AI guidelines and policies
• Risk Management in AI
Identifying and assessing risks associated with AI implementation
Creating a risk mitigation plan
Monitoring and reporting AI risks
• ROI Optimization in AI Initiatives
Measuring the impact of AI on business performance
Cost-benefit analysis of AI projects
Strategies for maximizing ROI from AI investments
• Building an AI Governance Framework
Key components of an AI governance model
Roles and responsibilities in AI governance
Integrating AI governance into existing enterprise structures
• Case Studies and Industry Insights
Examining real-world examples of AI governance
Best practices from leading enterprises
Lessons learned and future trends
• Developing an AI Governance Action Plan
Steps to implement AI governance in an organization
Tools and resources for effective AI governance
Continuous improvement and evolution of AI governance programs
• Conclusion and Future Directions
Recap of key topics covered
Emerging trends in AI governance
Preparing for future challenges in AI governance

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Subjects

Computer Science