
Learning is not an assembly line - AI, bias and the mess of learning: Margaret Bearman #CTC16
You've asked AI a question you were too embarrassed to ask your supervisor. Handy. But what does it cost when we start routing around the awkward, slow, human business of learning from other humans? In this episode we talk with Professor Margaret Bearman from Deakin University about AI, bias, and why efficiency might be the most misleading word in education. We get into the black box problem, and why she thinks the real skill isn't opening it, it's knowing a good output when you see one. We talk about bias: not just in AI, but the fact that data can quietly replace the patient in front of you. And we build on the philosopher Lauren Berlant to argue that teaching and learning are supposed to be inconvenient, and that this is a feature, not a bug. A conversation about mess, judgement, and why the most useful question a medical student can ask isn't "is this right?" but "how would I know?" To contact us, get in touch via email: hi[At]curemeded.com & follow us on Instagram @curingthecurriculum





