Me, Myself, and AI Bonus Episode

Bonus Episode: Artificial Intelligence Podcasts With Jennifer Strong

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Artificial Intelligence and Business Strategy

The Artificial Intelligence and Business Strategy initiative explores the growing use of artificial intelligence in the business landscape. The exploration looks specifically at how AI is affecting the development and execution of strategy in organizations.

In collaboration with

BCG
More in this series

While the Me, Myself, and AI podcast is on winter break, we hope you enjoy this episode. Jennifer Strong, longtime journalist and creator of the SHIFT podcast, joins Sam and Shervin to talk about their favorite Me, Myself, and AI episodes.

Find the additional podcasts mentioned in the episode below:

Subscribe to Me, Myself, and AI on Apple Podcasts or Spotify.

Transcript

Allison Ryder: Hi, everyone. Allison again. Really excited to share today’s bonus episode on which Jennifer Strong joined Sam and Shervin to talk about a host of podcasts and artificial intelligence-related topics. They will be talking about their favorite episodes of Me, Myself and AI, what goes into producing a podcast, and other really fun stories about what they’ve uncovered as they’ve researched and told stories about technology and business. We hope you enjoy it, and again, we really encourage you to continue to rate and review our show so we can continually improve and make this a podcast you really enjoy. Let’s jump in.

Jennifer Strong: I’m Jennifer Strong from SHIFT podcast.

Shervin Khodabandeh: I’m Shervin Khodabandeh.

Sam Ransbotham: I’m Sam Ransbotham.

Jennifer Strong: And you’re listening to Me, Myself and AI.

Shervin Khodabandeh: Hi, everyone. Today we have a special kind of guest for you. Today we’re joined by Jennifer Strong, who is an audio journalist, award winner, creator of SHIFT podcast for Public Radio Exchange. Jennifer, welcome to the show.

Jennifer Strong: Thanks so much.

Shervin Khodabandeh: Jennifer, you’ve been covering AI for quite some time and have perspective on what is going on and what you’re seeing. What is top of mind for you these days?

Jennifer Strong: What isn’t top of mind for me right now? Yes, I have been covering AI for a while. I think 2017 is when I first entered this beat over at The Wall Street Journal, but it’s not my background. I feel like I need to say upfront, I’m in no way a technologist. I came at this as a journalist. I’m endlessly curious.

Journalism has always felt like a great privilege, this opportunity to be trusted with people’s stories, to see the world and witness particular moments in history as they unfold. I feel that way about AI too. I would say right now I’m dedicating a significant portion of my time to gathering oral histories because I think in the not-so-distant future, even maybe just a few years from now, we’re going to look back at this time and all of the change and be happy to have that body of work.

Sam Ransbotham: That aligns well with your “I was there when” type of approach from In Machines We Trust, that tries to capture these sound bites and moments in history. Actually one of them that I was [listening] to made the point that this is probably a fleeting moment here.

Jennifer Strong: Yes.

Sam Ransbotham: It’s nice that we’re capturing some of that before we blow past it.

Jennifer Strong: You’re right, Sam. I started this work at MIT. I was a director at MIT Tech Review until this past summer [of 2023] just collecting all of these stories. We’re not quite ready to announce this yet, but the oral histories that are being collected, both in my last role and in my current one, hopefully will find their way into a museum sometime in the next probably couple of years. It’s like something of a time capsule. Anyway, I have my favorite episodes of the show. I’ve been a fan of you guys for a while now.

Shervin Khodabandeh: You’re very kind.

Jennifer Strong: Well, it’s true. It’s fun. A lot of the folks you have on are people I know too, and it’s really a lot of fun for me. Thinking of some of my favorite episodes: Ya Xu. I’m curious, what are some of your favorites or most memorable episodes that you’ve worked on?

Shervin Khodabandeh: Do you want to go first, Sam?

Sam Ransbotham: Yeah, so I think it’s kind of like saying, “All right, which of your kids do you like the best?” You can’t help but malign one if you mention some others, but there are some that just keep showing up over and over again that we end up bringing up as examples. There’s a recency effect. I thought of our NASA episode [with Vandi Verma]. One amazing person and super interesting to talk to, and honestly, flying helicopters on Mars is cool, but just also how we talk about all the planning that must go into using technology in that context.

Then at the same time she was searching for the unexpected. They want to find things they’re not expecting, and I think that’s an interesting analogy. I was thinking more about this, that a lot of what we’re trying to do with this technology is push a lot of boring stuff into the background and highlight all the interesting stuff. That’s happening clearly on Mars, but it’s happening lots of places. NASA was a big one.

Jennifer Strong: Yeah, NASA was absolutely one of the coolest episodes I think in tech podcasting this fall. That was an awesome episode for anybody who missed it.

Shervin Khodabandeh: I agree. I think we’ve done 60. It’s hard to say which is the best one, but what is interesting for me is when I take it retrospectively, I think about the sound bites for many of them that have become so true in my experience with AI, and my work with my clients and my work with my colleagues from “The First Day Is the Worst Day” comes up a lot.

Shervin Khodabandeh: Another one is “Learning, Engagement, and Empowerment” with Amit Shah of 1-800 Flowers on what kind of people do you need to hire. That episode was several years ago, and the question was what kind of people are you hiring and what kind of technical backgrounds, etc. He said, “Look, I want people who love to learn.” And that [has] become so true now. If you’re asking companies, “What kind of backgrounds are you hiring?” [they want] people who are open and curious.

Sam Ransbotham: It’s interesting too that most of the people listening probably assume that Shervin and I hang out all the time, but we actually met for the first time in person a couple of weeks ago at the World Bank. We were doing an event there. It was kind of fun. I felt like we were meeting people who had a whole bunch of friends in common because we were sort of saying, “Oh, you remember X, remember Y?” We had this giant shared history from this big list of guests that was fun to go through.

Shervin Khodabandeh: And also the research, right?

Sam Ransbotham: Well, yeah, OK, that’s where it all started years ago. It was fun because then we can speak in code words. Shervin says something like “The first day is …” and I know how to fill in the rest: “… the worst day for technology.” This is a theme that keeps coming [up, such as] Arti Zeighami at H&M [Group] saying, “Well, you don’t just do tons of AI in one place and ignore it everywhere else. You’ve got to tighten it like you tighten a tire, one little lug bolt at a time round and round.”

Some of these themes keep coming up, and I think that comes into some of the design that Shervin and I think about when we’re talking about the show [and with] Allison, our producer. We go through this a lot. We’re looking for things that we think will be enduring, and that’s intentional. We are not trying to chase a headline. Probably while we’re recording this, there’s some crazy thing happening in AI because that’s what constantly happens. We’re trying to hope for some of these sorts of stories that will last for longer, and that’s very intentional, and I feel like that’s working.

Jennifer Strong: I feel like I just learned something. I can’t believe that you two didn’t know each other. How did you come to be making this show together, and what motivates you to keep going?

Sam Ransbotham: Well, Shervin, he just adores working with me. I mean, that’s clearly what it is.

Shervin Khodabandeh: Yeah, actually it is true. We started back in 2019 doing our first series of reports on AI and the implementation of AI and AI and strategy. That was sort of a proper research piece of work between our two organizations. That’s when we first, I think, officially met. Ever since, it’s been such an interesting partnership because it’s been very intellectually stimulating, I would say. We both have the same educational background, chemical engineering.

Sam Ransbotham: That has to come up, always.

Shervin Khodabandeh: Did you also do your Ph.D. in chemical engineering?

Sam Ransbotham: No, no. [It’s a] real business degree, so don’t besmirch me.

Shervin Khodabandeh: We do have that background. Sam is a professor. I’ve always admired professors and people who impart knowledge on us.

Sam Ransbotham: When you ask about the show — the show itself is a bit of a COVID baby because we were doing interviews with people for our research program to pull out their stories — it was frustrating because we’d interview someone, we’d get a bunch of great stories, and one of the 10 stories that they told would fit with the research theme. So we’d throw away nine and we’d end up putting one or two sentences from them in our research, and it just made my little soul sad to throw all this away.

Then I think Allison had the thought of if we just would record these things, we could use them. And so we started to think, all right, this is an interesting thing we could do: This is content that people could use in all kinds of different ways. People walk their dog and listen to it or commute and listen to it, but the show itself is a bit of a COVID baby from that perspective.

Shervin Khodabandeh: I also find that when you let people just talk, a lot of other content comes out that will just not come out in a more, I would say, structured interview. Whereas the show, as you could tell even by how I’m talking right now, is completely unrehearsed. Other than reading the background of our guests, we don’t send them questions in advance.

Jennifer Strong: I’m loving this very much. Also, it’s pointing out how much that I suddenly feel like we have in common. Journalists never send their questions in advance. It’s actually an ethics violation. You don’t want people to prep in that way. You want their honest reaction to a question. For me, the reason I focus on audio journalism is for this reason, because I don’t want to have to just answer this narrow slice of something. I want to hear their stories. I want to learn something I don’t already know enough about to tease out that one thing that propels that one idea.

Shervin Khodabandeh: That’s right. You’re not shooting for a headline that’s going to be grabbing somebody’s eyes in a written piece.

Sam Ransbotham: When we first started this, Dave Lishansky, our sound engineer, sent some article to me about what resonates well in podcasts. It really reinforces what Shervin just said. It’s not a headline chase; it’s when an emotion comes through. How did something feel? I would never have thought of that before he turned me onto that idea.

Shervin Khodabandeh: Yes, I remember a lot of emotion coming out when I told Dave that I forgot to record a session.

Sam Ransbotham: Fortunately, all that gets covered up pretty well.

Shervin Khodabandeh: I said, “I have the recorder here, but nothing’s moving. And I think I forgot to press the red button.”

Sam Ransbotham: Oh, gosh. I’m going to check right now to make sure that mine is moving.

Shervin Khodabandeh: Yeah.

Sam Ransbotham: I’m sure we’ve all screwed that up, so don’t worry.

Jennifer Strong: Oh, we have all screwed that up. What’s the book that either of you haven’t written yet?

Shervin Khodabandeh: Sam, should we write one?

Sam Ransbotham: Shervin, you have to take this because I’m nagging Shervin right now about this, so we’re going to make him answer this on the spot.

Shervin Khodabandeh: What’s the name of the book though?

Sam Ransbotham: Well, I don’t know. See, we’re going to workshop this and it’s going to be a problem, but I think it’s Beautifully Boring. [It’s] my working title because I think we get so interested in chasing these monstrous, “Oh, this looks like a robot. This looks like a machine. This replaces a human, or I beat the Turing test and I couldn’t tell. …” I don’t know, that to me just isn’t interesting.

I think that there’s so much more going on in the boring corners of AI, both good and bad, and I think we have to worry about both the good and the bad. The insidious nature of the recommendations we’re seeing is a boring topic. It’s not front of mind like Boston Dynamics robots, which are cool, but not, I think, things that are going to change the world.

Jennifer Strong: One, I completely agree with you, Sam. The title of an article I wrote at the Journal was for business leaders to embrace AI more — it needs to become boring. The other thing is, in regards to those Boston Dynamics robots, I did spend time with one in recent months that disobeyed me. And I now have to disagree and say you can’t eventually have a robot helping, for example, an elderly person if it’s going to hurt them. There are times when we’re going to ask a bot to do something that’s not safe. I spent a few days after that encounter thinking deeply about it. We digress. You were about to tell us about this bestselling book that you plan to write.

Shervin Khodabandeh: Oh, you’re going back to that?

Sam Ransbotham: Well, actually, we did get on a technology tangent, and something that Shervin mentioned earlier that I think is a recurring theme is —

Shervin Khodabandeh: See, Sam is still trying to dodge your question. We’ll switch out.

Sam Ransbotham: The point is, we’re Me, Myself and AI, and two of those words are human, and one of them is technology. I think that’s something that has come out over and over again, and that really needs to be a theme of whatever we talk about.

Shervin Khodabandeh: No two parts human, one part technology.

Sam Ransbotham: Exactly. Is that your recipe?

Shervin Khodabandeh: Yeah. That’s actually interesting. That’s sort of a BCG rule, when you think about it. We have a 10/20/70 rule, which is 10% is the AI and 20% is the data and digital and technology backbone of an AI algorithm or system. Then 70% is the people and the organization and the ways of working and all that.

Sam Ransbotham: All those are the complicated things that mess up.

Shervin Khodabandeh: Right. And so, that means the title of the book would be Two-Thirds Human. That’s a good title, Two-Thirds Human.

Sam Ransbotham: Let the listeners chime in on that because that’s another thing that we think about. We’re being a bit sort of nostalgic now, but all the people listening and the things they’ve brought up are really fascinating to me. We keep running into people who say, “Oh, I listen to this,” and it’s really always fascinating to me which episode really resonates with them. I’m really poor at predicting what’s going to be the one that they mention. Given what I know about a person, what are they going to pull out? That’s been a fun part of it as well.

Jennifer Strong: Oh, that’s one of my favorite parts of making podcasts. We had an episode back at Future of Everything, which is a franchise that I started, that podcast for The Wall Street Journal that once a year would just spike on the charts, and we couldn’t figure it out. It was about antimicrobial resistance and some of the efforts that were at hand. We found out that a nursing [program] — I guess it was considered a continuing education program or something — was using this years later. Every time it would get used, it would spike on the charts. Anyway, fun things. This was a rather nerdy episode that I taped at Duke. I mean, who knew?

Shervin Khodabandeh: Jennifer, how do you prepare for your podcast?

Jennifer Strong: My podcasts are weird in that they’re really different. My field recordings require quite a bit of prep. I use this example: I was in an experimental fighter plane last year, and we went out over the Pacific Ocean and got into dogfights with AI. So preparing for that is a little different than going out to tape some oral histories where I just want to hear someone talk about how they’re preparing for governance.

Sam Ransbotham: Maybe a different way to redirect that is that you started by talking about your background being particularly not technology, but then this is a heavy technology field. How do you get over that sort of, “Oh, they’re going to say something weird that I’ve never heard of.” I have that fear going into every episode. We bring in these smart people and I’m like, Oh my gosh, they’re going to know something that I don’t know and it’s going to be humiliating.

Jennifer Strong: This is a luxury that I think I get because I don’t have the degrees that you do. Also, I feel like everybody needs to understand [that] in order to know where we’re going the next five, 10 years, to understand to be active in our society, we need some baseline understanding of AI. That’s what I’m in it to do, to document history as it’s going down, hear the stories of people, and also to really understand what’s happening. I have no ego in asking somebody to explain what I don’t know. I will also assume that a lot of our listeners won’t know as well. They also don’t have your background or degrees.

Shervin Khodabandeh: Yeah, I actually think she’s at an advantage.

Jennifer Strong: I think so. But I would also say in some specific examples, I don’t trust that something works because I know technically it can. I trust that it works because somebody shows me it works. Some specific moments were when friends, colleagues, researchers were sure in 2020 that face [recognition] was not going to work on somebody in a mask, except it worked quite well on people with masks. It took, what, 90 days for that to be working everywhere.

About the same time, specific groups, and [I’m] thinking of one in particular in Russia, got their video analytics working so you could not only do face rec on the mask, [but also] know how well the mask was, see who you were associating with, and read your license plate at the same time — I didn’t have it in my head that it couldn’t work for these five reasons, or it wouldn’t work yet for this reason. Then going forward, that’s happily how I found myself in that fighter plane because I can’t take your word for it.

My phone screen sometimes is hard to read when I’m standing on a sidewalk, so why am I supposed to believe that an AR fighter jet is going to be perfectly visible during sunset over the Pacific Ocean? Just saying.

Sam Ransbotham: I think we could take a lesson there. We need more fighter jet plane rides. Can we, Shervin? We’re doing something wrong here.

Shervin Khodabandeh: Exactly. First of all, yes, but tell us about the fighter plane. What were you reporting on?

Jennifer Strong: Looking at how AI is being used to train pilots in the future. This is extremely dangerous. We have lost more fighter pilots in training accidents than really any other way for a significant period of time now. You go from basically being in a simulator to being in a real plane, and the first time you land on an aircraft carrier, the precision required … [there are] refueling exercises too.

Then just the other part of this, how often are you going to train against a Chinese jet? Our pilots and other pilots are training against themselves, and they will pretend that the other aircraft is not the aircraft it is, being flown by someone who wasn’t trained the way they were. What could go wrong? There’s a lot of tech, including in particular this group called Red 6 that I was out flying with that are looking for what comes next.

That’s why I was up there, to see if it actually works because it’s a little bit hard, again, for somebody to say, “Oh, yeah, absolutely. The planes will be vibrantly colored. You’ll see them in the sun.” I’m thinking, my VR headsets also don’t work if I leave my living room, so how are you flying at speed, pulling Gs without any type of trouble?

Sam Ransbotham: That’s great. I mean, we hear all these stories and I think that cynic is a great skill.

Jennifer Strong: Well, thank you. It’s a curious cynic. I’m not mean about it. I just genuinely want to know and see it. I do have to say it’s the only time I’ve ever thrown up in a podcast. I tried to edit that one as politely as I could.

Shervin Khodabandeh: I was trying to not ask that question, but I’m glad it came up because I thought that you would either say that you’re proud that you did not throw up or that you would say you did throw up.

Jennifer Strong: No, no. The guy who took me up was a former Top Gun pilot and he was having fun.

Sam Ransbotham: You know they love that.

Jennifer Strong: You know they love it.

Shervin Khodabandeh: Some new kid.

Sam Ransbotham: Yeah.

Jennifer Strong: I mean, friends, they handed me a sandwich baggy before we left. This sucker didn’t have a Ziploc on it. I don’t know what I’m supposed to do with it upside down. But yeah.

Sam Ransbotham: In our shows, we have this five question thing, and we ask rapid fire questions of our guests, but it doesn’t fit well here. So I’m going to take a little segue here and I’m going to rapid-fire different questions for different people. This is going to be new. Including you, Shervin, I’m looking at you.

Shervin Khodabandeh: Oh, you’re completely surprising me. OK.

Sam Ransbotham: I’ve thought about some mean questions for you, Shervin. What’s your favorite part of working with me? To just really put you on the spot. Let’s look at this whole thing. What about the podcast has gone better than you thought it would, Shervin?

Shervin Khodabandeh: The whole thing. It’s a lot more fun than I thought it would be, at least for me, and a lot more insightful. Also, this notion of it not being rehearsed, I thought was really, really good for both our guests and for ourselves, to allow a free flow of thought. I thought that was a lot more productive than I thought it would be.

Sam Ransbotham: Jennifer, why do people like podcasts?

Jennifer Strong: Take me somewhere. Teach me something. NPR used to call them driveway moments, the moment you’re listening to a story that you just have to sit there and you don’t get out of your car until it finishes. Yeah, we’re looking for connection and I think never more than the last few years.

Sam Ransbotham: Maybe a follow-up. We never do follow-ups in our rapid fire, but you could get that from a printed word, you could get that from video … why podcast?

Shervin Khodabandeh: Can you?

Jennifer Strong: Can you? What about the human voice? It’s the first thing we experience even before we’re born. I think the sound is special. I say this, and we’re talking about AI, and I don’t know, maybe one day we’ll feel that way about synthetic voices, but who knows? To me, the voice is the ultimate human experience.

Shervin Khodabandeh: Well, actually, I’d like to modify my answer a little bit. Part of this that I did not really appreciate while working with you prior to the podcast, Sam, is what a great radio voice you have.

Jennifer Strong: It’s so true.

Shervin Khodabandeh: This is in addition to a TV face.

Sam Ransbotham: What he’s trying to say is [I have] a face for a radio.

Shervin Khodabandeh: What a great radio voice you have, yeah.

Sam Ransbotham: OK, so what about our guests have surprised you, Shervin?

Shervin Khodabandeh: How do I answer that question? I don’t know.

Sam Ransbotham: See, it’s all fun and games when you’re the one asking the rapid-fire questions.

Shervin Khodabandeh: That’s right. Every time.

Sam Ransbotham: You don’t have any sympathy for a guest, but now you’re all —

Shervin Khodabandeh: Well, Sam, I have a question for you. What about our guests has surprised you?

Sam Ransbotham: Is that fair? I thought when we started this that things would be much more tech-heavy, that there would be a lot of discussions about this algorithm, that algorithm, this thing, and how these are normal people doing not normal [things]. These are not superhuman people. These are people curious, trying, interested, working hard, not doing it perfectly the first time, willing to improve it the next time. I think there’s been a certain sort of aha with me that these are not sort of deities that can magically do things that the rest of us have [not].

Shervin Khodabandeh: Two-thirds human, I agree.

Sam Ransbotham: Well, here’s another statistic: Zero percent of the people in the world are born knowing about how to do artificial intelligence. Well, I mean, I’m not going to cite my source on that. I think our guests have shown that they’ve gone through a process, they’ve learned. One of the things we ask them is [their] background. It’s always fascinating how they connect all the pieces of their backgrounds to what they’re doing now and how it informs that and connects that in weird ways.

Jennifer Strong: I have a question for you guys. What’s something you’ve changed your mind about?

Shervin Khodabandeh: I’ve changed my mind about how fun it is working with Sam. I think it’s more fun.

Sam Ransbotham: Which direction did that change?

Shervin Khodabandeh: In the direction of more fun.

Sam Ransbotham: No, actually I think I’ve changed to maybe a fear of the speed. I thought these things were progressing and we were making progress of whatever. And now as we’ve gone through more and more of these episodes and more and more of these examples, I see it may be so much of what we’re going to do wrong here is because of pace.

Shervin Khodabandeh: You think we’re going too fast?

Sam Ransbotham: Actually, this is not me calling for a slowdown or a pause because I don’t think there’s any hope of that ever happening, but we think they’re moving so quickly, and they’re moving faster than organizations can digest them, they’re moving faster than consumers can digest them. That doesn’t bode well. That’s not exactly I think what you’re getting at, but that’s something that’s sort of resonated with me, listening to all of our guests.

Jennifer Strong: No, it’s exactly what I was getting at.

Sam Ransbotham: I teach a class in machine learning and AI. I, like every professor, like to be a little lazy and use the slides from last semester. A year ago, I worked people through an example using a natural language processing model, and they all thought it was amazing. I used that same model this year, and people thought it was garbage. We went from one year ago, this model is amazing to this year, this model is garbage. The model hasn’t changed. It’s what our societal expectations of how this stuff is working have just so, so quickly evolved.

Jennifer Strong: Absolutely fascinating. Maybe you’ve answered my next question then. Sorry to interrupt our lightning round, but I really do want to know. What’s something you think we’re going to look back on in regards to how we’re thinking about AI right now and go, “Wow, we got that wrong.”

Sam Ransbotham: One of our guests from Orangetheory had a great answer to “What were you proudest about artificial intelligence?” He said, “Oh, when we solved it with linear regression.” I think one of the things in our current zeitgeist is that this technology fits everywhere, does everything, is the perfect tool for everything. I think we’re going to look back and say, “That was not the place to use this technology.” I think we’re going to find a lot of places where this technology is overkill or is just not the right way to go.

Jennifer Strong: I get that. Not as universal as we might have first thought.

Sam Ransbotham: It’s been a fascinating discussion today. We’ve talked about all kinds of different things, and somehow I can even think of more that we should talk about. If you’re interested in more, Jennifer has a podcast, SHIFT, that you can listen to. Jennifer, tell us a little bit about that.

Jennifer Strong: This is a brand-new project from public radio, distributed by PRX, and you can find links to the show and all the different players in YouTube at shiftshow.ai.

Sam Ransbotham: We’ll include some of those links in our show notes as well. Thanks for joining us today.

Jennifer Strong: Thanks so much for having me. This has been so much fun.

Allison Ryder: Thanks for listening to Me, Myself and AI. We believe like you that the conversation about AI implementation doesn’t start and stop with this podcast. That’s why we’ve created a group on LinkedIn specifically for listeners like you. It’s called AI for Leaders, and if you join us, you can chat with show creators and hosts, ask your own questions, share your insights, and gain access to valuable resources about AI implementation from MIT SMR and BCG. You can access it by visiting mitsmr.com/aiforleaders. We’ll put that link in the show notes, and we hope to see you there.

Topics

Artificial Intelligence and Business Strategy

The Artificial Intelligence and Business Strategy initiative explores the growing use of artificial intelligence in the business landscape. The exploration looks specifically at how AI is affecting the development and execution of strategy in organizations.

In collaboration with

BCG
More in this series

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