Decoding AI: Part 5, Navigating trust in the age of large language models and generative AI
- Trust is a complex and dynamic phenomenon that shapes our perception and interaction with AI technologies.
- Six core pillars of trust in AI include fairness, reliability & safety, privacy & security, inclusiveness, transparency, and accountability.
- To put trust into action, Microsoft's Responsible AI framework suggests actionable steps such as assigning clear roles and responsibilities, testing and evaluating AI systems, identifying and mitigating bias, documenting and communicating AI systems' purpose and limitations, and enabling users to access and control their data.
- The trust equation in AI is constantly evolving as technology advances.