Explore the legal risks and mitigation strategies associated with AI and machine learning applications in this 51-minute conference talk from RSA Conference. Delve into how neural networks and machine learning can create vulnerabilities and expose companies to litigation. Learn about potential billion-plus liabilities, causes of action, and use cases of AI/ML liability, including unlawful algorithmic biases and AI discrimination in hiring practices. Examine the state of AI fairness, human solutions to AI problems, and the challenges of black box decisions. Discover areas of focus for mitigating legal risks in autonomous driving, healthcare, and service robots. Gain insights on educating yourself about policy and business issues, joining the AI and robotics policy community, forming a team to tackle AI risk, and developing an AI risk management program by design. Equip yourself with the knowledge to navigate the complex legal landscape of AI and machine learning implementation in various industries.
AI and Machine Learning - Managing the Risks of Major Lawsuits
Overview
Syllabus
RSAConference 2019 San Francisco March 4-8 Moscone Center
Roadmap
How Does it Work? (Autonomous Vehicle Example)
Neural Networks and the Brain
Attacking Neural Networks
Billion Plus Liabilities
Possible Causes of Action
Use Cases of Al/Machine Learning Liability
Unlawful Algorithmic Biases
Al Discrimination and Hiring Practices
The State of Al Fairness
Human Solutions to Al Problems
Black Box Decisions
Disparate Impact Analysis
EU Machine Decision Rules
Areas of Focus to Mitigate Legal Risk
Autonomous Driving
Future Modes of Transportation
Al in Healthcare
Surgical Robots
Service Robots in a Hospital Setting
Read this Book
Educate Yourself on Policy and Business Issues
Join the Community - Meetup on Robotics and Al Policy Issues
Form a Team to Tackle Al Risk
Assess Al's Impact to Your Organization
Al Risk Management by Design: Develop the Program
Questions?
Taught by
RSA Conference
