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. 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.

Matt Beane: How do we learn to work with intelligent machines?

How do we learn to work with intelligent machines?

AI's rise in workplaces risks learning traditions, pushing learners away from hands-on experience critical for skill mastery.

Innovative 'shadow learning' emerges as learners clandestinely seek hands-on experiences, challenging traditional training norms.

Fusing AI with mentorship could revolutionize learning, amplifying human skills alongside technological advancements for a better future.