Why an IIT Professor Hires for 'As Little Learning as Possible' | ibl.ai

Why an IIT Professor Hires for 'As Little Learning as Possible' | ibl.ai
#FutureOfWork #AI #Hiring #HigherEducation #Skills

This clip is from a panel discussion on agentic AI in higher education, recorded in Mexico City. The panel brought together Paul LeBlanc (moderator), Andrew Joncas (Syracuse University), Ron Stalnaker (Georgia Southern University), and Miguel Amigot (CTO of ibl.ai) to discuss how institutions are deploying AI agents, what it actually costs, and what works.

In this clip: Paul LeBlanc relays a provocative hiring philosophy and why precision of language and thought now matters most.

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Miguel Amigot: and external operations in that way.

Paul LeBlanc: So I had at Harvard a week ago, the faculty member who teaches the most sort of iconic data science class in India at IIT, 1% acceptance rate, crazy place. And he has 17,000 students per term across all their campuses. It's not really teaching, it's an army of TAs in Egypt and by India. But one of the Harvard grad students said to him, when you hire for your team now, what are you looking for? What are the skills I should be thinking about? What are you, what are the traits you look for? And he wasn't being a jerk when he said this, but he said, as little learning as possible. And of course, I was mad, I was like, what do you mean? And he said, if you have grown up, if you've been educated in the old way of doing the work, you are prepared for the future. And what he then went on to talk about is, I want precision of language and precision of thought. Like AI agents don't do well if you are, if you leave a lot of gray area, right? And linguistics may actually be one of the key disciplines. Right, absolute philosophy, precision of thought, precision of language is really critical

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