"“It certainly isn't often framed to us as being fun. I think the most important thing I would say for learning anything: It doesn't have to be fun. It just has to be that it keeps people motivated. There are multiple ways to keep people motivated. With Duolingo, we've chosen mainly fun. That's the main thing we've chosen, but you don't have to do that.”"
"“For example, seeing results keeps people motivated. In the case of learning AI, I would say that's probably a better motivator of the form. I'm going to learn AI, but the first thing that I'm going to do is make myself a dashboard or a mini-dashboard or something. But I think if you find the right motivation, that helps a lot.”"
"“Now he unpacks what he got right, what he got wrong, and what the backlash taught him about the real limitations of AI. It's a candid reckoning with hype, growth, and the surprisingly complicated promise of technology in education.”"
Learning AI for work can be approached by focusing on motivation and visible progress rather than insisting the process be fun. Motivation can come from outcomes such as results and dashboards that make improvement tangible. A prior internal message about AI created disruption and sparked debate about the future of work. The backlash revealed that AI’s capabilities and constraints are more complicated than hype suggests. The experience points to the need for practical, evidence-based decisions about roles, hiring, and how technology is integrated into education and work. Real limitations determine what AI can replace, augment, or fail to do reliably.
Read at Fast Company
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