The path to skill around the globe has been the same for thousands of years: train under an expert and take on small, easy tasks before progressing to riskier, harder ones. But right now, we're handling AI in a way that blocks that path — and sacrificing learning in our quest for productivity, says organizational ethnographer Matt Beane, an assistant professor in the College of Engineering's Technology Management Program at UC Santa Barbara. What can be done? Beane shares a vision that flips the current story into one of distributed, machine-enhanced mentorship that takes full advantage of AI's amazing capabilities while enhancing our skills at the same time.
Wednesday, February 6, 2019