What happens when AI learns from moments where humans were just trying to cope?

In this episode, we explore a fascinating research breakthrough that looks at how artificial intelligence learns rules from the past and why that can quietly go wrong. By studying real scheduling data from long-term care facilities, researchers discovered that not every pattern reflects best practice. Some patterns exist because people were under pressure, understaffed, or exhausted.

This episode dives into how AI can be taught to recognise those moments to ignore burnout, exclude emergency decisions, and learn judgment instead of blindly copying history.

Beyond care worker scheduling, this research opens a deeper question about the future of AI:

Can intelligent systems learn when humans were surviving, not choosing?

A reflective conversation on ethical AI, human-centric intelligence, and why the future of smart systems may depend less on raw power and more on understanding how humans really work.