Ensuring robustness and building resilience

All systems fail at some point, no matter how much time and rigor are put into their design and development. AI is not immune, susceptible to attacks, exploitation and unexpected failures. This session will be broken into two presentations to explore:

Design and build:

• Top tips for designing, building and ensuring robustness and resilience in AI
• Improving the robustness of AI components and systems
• Designing for security challenges and strategies for risk mitigation

Testing and evaluation:

• How to test, evaluate and analyze AI systems
• Adopting comprehensive test and evaluation approaches
• Which protocols can be applied and where new approaches are required