Comment: How do we learn to work with intelligent machines?

I discussed something related to this earlier this year (the algorithmic de-skilling of clinicians) and thought that this short presentation added something extra. It’s not just that AI and machine learning have the potential to create scenarios in which qualified clinical experts become de-skilled over time; they will also impact on our ability to teach and learn those skills in the first place.

We’re used to the idea of a novice working closely with a more experienced clinician, and learning from them through observation and questioning (how closely this maps onto reality is a different story). When the tasks usually performed by more experienced clinicians are outsourced to algorithms, who does the novice learn from?

Will clinical supervision consist of talking undergraduate students through the algorithmic decision-making process? Discussing how probabilistic outputs were determined from limited datasets? How to interpret confidence levels of clinical decision-support systems? When clinical decisions are made by AI-based systems in the real-world of clinical practice, what will we lose in the undergraduate clinical programme, and how do we plan on addressing it?