The importance of trust in AI systems is growing, as users need assurance that these systems will behave reliably and consistently.

Trust in AI systems is becoming more critical than raw performance, as users need to feel confident in the reliability and consistency of these systems.

The stakes are higher when AI has access to sensitive information and systems, making safety a critical concern.

Trust in AI systems involves verifying their reliability and consistency, which is crucial for user acceptance and enterprise success.

Accuracy and transparency are crucial in AI healthcare applications, allowing physicians to interrogate the sources of information provided by the AI.

The integration of AI into software development raises questions about managing non-deterministic behavior and the reliability of AI-driven applications.

The future of AI will shape how we interact with critical systems like education, healthcare, and government, raising questions about the values embedded in these technologies.

AI needs healthcare as a domain where its application can justify the high costs associated with developing AI technologies.

While AI can automate many tasks, it is not yet reliable enough to handle critical decisions without human oversight.