Helen Beetham brings it all together re AI in the classroom, and in the office.
Existing uses of machine learning and generative AI at work show that they can automate the routine parts of tasks. But you can only know how this automation will be useful if you are already an expert in that task. You can only initiate and guide the generative component if you are already an expert in that task. You can only correct for errors and refine the outcomes if you are already an expert in that task. You can only participate in the design and development of new workflows if you are already an expert in that task. This is true whether the task is writing prose or diagnosing cancer. So universities should continue to produce graduates with expertise, confident that they will be able to accommodate any efficiencies that computation may offer down the line. Technologies are designed for ease of use: expertise is hard to acquire.