Ranjitha Kumar

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92 appearances 1 recordings 1 series first heard Sep 2026 last heard yesterday

Ranjitha Kumar’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 1 in all, peaking in Sep 2026 with 1.

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Insights Unlocked · The 80% problem: What AI still needs from humans · 21 Sep 2026 podcast

So in that apprenticeship model, you are teaching like your personal taste, basically.

But they, you know.

They should not just adopt all of it without thinking about how they think about the world and their problems.

Yeah, I think there's a lot to unpack there.

With my students, I can see that the tools are only as good as the mental models and the conceptual frameworks you have because what it comes down to is are you –

do you know when the AI has produced something that is good or bad?

And do you know how to interrogate the AI to get to better quality outcomes, right?

And so I do feel like there is this article that came out maybe a decade ago from the Stanford Education Department, and they were trying to just figure out, like, how do you tell...

that first graders have, you know, different types of expertise versus college students.

And they gave them a topic, and I don't exactly remember what the topic was, but it was a topic where both the, you know,

the first graders and the college students had no exposure to that topic before.

And what, you know, what you saw was the questions that the first graders asked was all around these like very surface level questions like, you know,

Is the thing red?

Is the thing blue?

But then college students were digging into like what makes it behave the way it does or getting into more of the conceptual layers of understanding.

And so you can kind of.

think of expertise, I think as you know, how deep can you go?

And how far past that surface layer level of detail?

Can you go and really understand whether something is good or not?

And so I do think that's part of the answer here is like, do you can you recognize when the AI is producing good quality output?

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