Conversational AI: Ensuring Compliance and Mitigating Risks

Overview

In today's tech-driven world, the relevance of conversational AI is unquestionable. The human voice is a unique channel; besides identifying a person, the human voice and respiratory sounds contain biomarkers that reveal physical, neurological, and psychological conditions and a person's overall health.

The human voice is classified as sensitive data and requires risk mitigation strategies. With AI technologies rapidly evolving, professionals equipped with risk mitigation knowledge are in high demand.

This course will make learners adept at identifying and managing potential risks in AI implementations and ensure their expertise aligns with the latest international standards and regulations. By completing this course, they will enhance their career prospects in various fields, including AI development, project management, compliance, and risk management, ensuring they remain at the forefront of AI advancements and ethical considerations.

Syllabus

• Introduction to Conversational AI
Understanding Conversational AI technologies
Relevance and applications in various industries
• Understanding Biomarkers in Human Voice
Identification and analysis of human voice data
The significance of voice biomarkers
• Data Sensitivity and Privacy Concerns
Classification of voice data as sensitive information
Ethical implications of voice data collection
• Risk Mitigation Strategies in Conversational AI
Identifying potential risks in AI implementations
Strategies for data protection and privacy assurance
• International Standards and Regulations
Overview of key regulations (e.g., GDPR, CCPA)
Compliance requirements for conversational AI systems
• Implementing Risk Management Frameworks
Developing risk management plans for AI projects
Tools and techniques for monitoring and managing AI risks
• Career Prospects in AI Risk Management
Exploring opportunities in AI development and compliance
Essential skills for AI project management and risk mitigation
• Case Studies and Best Practices
Real-world examples of successful risk mitigation
Evaluating and learning from compliance failures
• Ethical Considerations in AI
Balancing innovation with privacy and ethical standards
Advocacy for responsible AI development and use
• Course Conclusion and Future Outlook
Recap of key learnings and knowledge gained
Future trends in AI compliance and risk management
• Final Assessment and Certification
Evaluation of understanding through a comprehensive test
Certification of completion for professional advancement

Taught by

Diego Gosmar, Oita Coleman, Sara Oliver G.V. and Michael Novak

Subjects

Business