Judgment is the New Bottleneck
episode
Where AI Works: Conversations at the Intersection of AI and Industry
26 min
2 speakers
5 chapters
transcribed 1 month ago
Transcript
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Transcript generated automatically by AI and may contain errors.
What is the core argument behind “judgment is the new bottleneck” in AI adoption?
I think unless you have skepticism, you're not going to build a trust because you have to have the judgment to understand if the output is strong or not. The other thing is understanding when to put the human in the loop. And that human having the judgment to say whether this output is strong output or there is an error, and then a way to correct that error so you can have a feedback loop to the AI. So it's continuously learning and improving.
Hello and welcome back to Where AI Works, conversations at the intersection of AI and industry, brought to you by Wharton in collaboration with Accenture. I'm your host, Matthew Bidwell. I'm a professor of management, faculty co director of the Wharton People Analytics Initiative, and faculty director of Wharton's CHRO program. So our goal on this podcast to try and cut through some of the noise and deliver actionable insights for business leaders, combining cutting edge research with real world case studies. Things are changing fast, so let's get going. Today, we're looking at what happens when AI isn't just assisting humans, but starting to run the system itself, and what that means for the people who have to make it work.
Joining me for our final interview of the season, it's my great pleasure to introduce Richard Rungen, Senior Vice President of Product at Expedia Group. Richer, welcome to where AI works.
How does Ritcha Ranjan’s career path shape her view on AI and human judgment?
Matthew, thank you so much for hosting me. It's a pleasure to be here.
Before we get into the AI conversation, I wonder if you could just share a little bit about yourself with our listeners. What does your role at Expedia Group entail and how did your career path get you there?
So at Expedia Group, I basically run the platform. So if you see anything that's happening on any of the Expedia properties, it is touching what I work on basically. I'm also running all of the AI that we are doing from the traveler-facing side. So we're really focused on how can we make it much easier to book, go on vacations, find the right places, and basically just really make it simple for them to travel. I started my career at Microsoft. I was working on speech SDKs before speech was a thing. I won't date myself with uh timelines here, but it was many, many moons ago. Um, and I was very fortunate to be at the cutting edge of speech recognition technology at the time. I went to business school, unfortunately, not Wharton, but another one at a another location.
We all make mistakes. Make mistakes. We do. Um, spent a few years there. And then went to work for Google after his time. And at Google I got a chance to work on everything from ads to workspace. to payments and really cut my teeth as a product manager in that company and was working with AI, I would say far before AI was cool. And uh that journey led me to Microsoft, where I got a chance to work on multiple products, including Copilot for Office. And that journey led me over to Expedia where I am today.
Well, so it sounds like kind of a background that was tailor made to prepare you for this moment, in a sense, kind of moving through all these tech firms, doing AI before AI was cool and so forth. So did you plan all this out? Do you feel lucky to uh to have landed up in in this position?
Yeah, I I wish I could say I'd planned out each and every move, but really it's always the problem that attracts me. And so I just kept finding more and more interesting problems at each role I took within each company or between companies. And honestly, I think a lot of career is luck. And so I've been fairly lucky, I would say, to date with both great problem spaces as well as wonderful managers.
So there are certainly some interesting problems that we're talking about today with AI. I mean, I think something you've said is that AI isn't just another tool, it's kind of a platform shift. I also joined this area many moons ago. I was slightly too late for the shift to the PC, but um I kind of saw pretty much the whole thing with internet, mobile, and cloud. How do you think kind of AI compares with those shifts?
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Chapters
5 chapters
1
What is the core argument behind “judgment is the new bottleneck” in AI adoption?
0:02–1:20
2
How does Ritcha Ranjan’s career path shape her view on AI and human judgment?
1:20–9:30
3
What are the top three misconceptions business leaders have about AI?
9:30–16:47
4
What are the three stages of AI adoption – “help me”, “create for me”, and “run this for me” – and how do they differ?
16:47–23:54
5
How should organizations balance AI risk and reward as they move deeper into automation?
23:54–26:53