Addressing AI security and safety challenges

As AI technology is evolving so fast, it is difficult to comprehend the dynamics of the AI risk landscape. However, as of today, there are endeavors from both communities and industries that try to address these challenges. Some of these efforts are theoretical, while others are practical. It is imperative for you to understand both dimensions to keep confidence in adapting the technologies and tools.

In this section, we show some high-level methodologies and implementations that help navigate the complexity of responsible AI.

Theoretical approaches

The theoretical approaches to address AI security and safety challenges can be broken down into several key components concerning governance, principles, practical measures, and ethical considerations. You can find some components here:

• Robustness and safety: AI systems should be stable, consistently meet performance requirements, and prevent unintended or harmful actions. The...