Stephen Downes

I think there's the genesis of a good argument here. After discussing what AI does to evaluation as we know it, Heléna Stakounis raises the question of why we're evaluating at all. "Evaluation, in its ideal form, should not in fact be a form of evaluation. It should be a task that invokes knowledge that stays, skills that can be employed, products that can be used." Or we can be more radical: "We should stop insisting on testing, measuring, ranking and reducing the long, complex learning process to a simple percentage or letter." If we were to actually use AI to evaluate students, what would be the value of assigning grades to pre-assigned work? I have long argues that once we can look at a person's work in its full complexity, we can skip the shorthand and use AI directly to offer jobs, placements, or rewards.