The 80% problem: What AI still needs from humans
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What is the 80% problem and why does AI make it harder to judge quality?
Welcome back to Insights Unlocked. In this episode, Jennifer Artebane sits down with Ranjitha Kumar and Jason Giles to explore what happens to human expertise when AI can help anyone create. They unpack why taste, judgment, curiosity, and craft matter more than ever, and how we can use AI to sharpen those skills instead of shortcutting them. Enjoy the show.
Welcome to Insights Unlocked, an original podcast from User Testing, where we bring you candid conversations and stories with the thinkers, doers and builders behind some of the most successful digital products and experiences in the world, from concept to execution.
Welcome to the Insights Unlocked Podcast. I'm Nathan Isaacs, Principal Content Marketing Manager at UserTesting. And joining us today as host is Jennifer Artebane, UserTesting's Vice President of Product Management. Welcome, Jennifer. Hi, everyone. And returning for our second episode in this mini-series is Ranjitha Kumar, UserTesting's Chief Scientist, and Jason Giles, UserTesting's Vice President of Customer Intelligence. Welcome Ranjitha and Jason. Thank you so much,
as always. It's a pleasure.
Good to see you again,
Ranjitha.
Let's start today with a quick this or that segment. No explanations, just snap answers and maybe a one-line comment. So would you rather have an expert with average AI or an amateur with amazing AI?
I'll go first.
Expert with average AI.
Oh, I have to agree with Ranjitha, totally.
Okay. And when you're working with AI, would you rather have a blank page and you get to give it input or a first draft from the AI?
I want the blank page. I want the raw human expression out first and you can use AI to refine it.
I hate starting from a blank page. So I can first draft from AI.
Do you think it's important for folks to learn the craft or learn the prompt? Craft.
Craft.
How do experts vs amateurs differ when using powerful AI tools?
Okay.
Ironic that we're at an event today called Craft It.
Of course. So do you think AI is making us smarter or making us lazier?
AI is a tool, and I want to say I want to use it to make us smarter. I
love your optimism. I think the way that most people are using it, it's making everybody lazier and dumber.
Okay. How about do you think that what we have with AI is good enough today or that it'll be great tomorrow?
Is it good enough? Yeah, it's good enough for today for what it does. Do I think it could be greater tomorrow? Yeah,
I mean, I think it's both. Like there are a lot of use cases today and there'll be new use cases tomorrow.
And as folks are working with AI, working in their craft, do you think they should trust their gut or ask them out?
Yeah, I actually trust your gut. Yeah, I think you need to trust your gut. I mean, this is where the judgment, it's where taste comes from. The machine is going to give you that.
I guess it doesn't refer to us, the model. That's true. You know, if it's not costing you a lot of money. So, I mean, both.
Yeah.
Yeah, that's fair.
Okay, so AI slot. Is that a human problem or a tool problem?
Humans make the tools, so it's ultimately a human problem.
Yeah, if you can't recognize its slot, that's definitely a huge problem. And then what about taste? Is it teachable or is it built through experience?
Honestly, I think it's from experience. I think it's from experience. developing an innate, unmeasurable sense of what's good and what isn't.
Yeah, I do feel like taste is a personal expression of expertise. So I do think it comes from your personal experience. But I hate being the person who says both. I want to also say that there are aspects of it that you could probably teach. But yeah, I do lean on the experience side.
Yeah, because, I mean, you are a teacher, and so it's interesting to think around, like, how do you go about that?
Why does human expertise become more critical as AI tools become widely available?
Like, in design school, it's around exposure. It's around repetition. It's around subject criticism. Yeah. The intent is to maybe mold taste a little bit. I don't know how you think about that in your world.
Well, I do think it's with the, you know, with me being an advisor to my PhD students, I do feel like I am teaching them my taste. So in that apprenticeship model, you are teaching like your personal taste, basically.
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Chapters
8 chapters
1
What is the 80% problem and why does AI make it harder to judge quality?
0:00–2:09
2
How do experts vs amateurs differ when using powerful AI tools?
2:09–4:53
3
Why does human expertise become more critical as AI tools become widely available?
4:53–8:50
4
Is the challenge of AI a human problem or a tool problem?
8:50–12:52
5
Can taste be taught, or is it solely built through personal experience?
12:52–17:03
6
How does the concept of ‘crafted’ evolve into focused attention with AI?
17:03–20:43
7
What should the next generation learn to recognize and improve AI‑generated work?
20:43–24:33
8
What advice would you give your 22‑year‑old self before using AI tools?
24:33–27:52
Speakers
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