S2 E11 | How to Use Chat GPT

Why am I using it? Why am I using this? What is it gonna help me do? And if, if the answer is it's gonna save me time, I might be okay with it. But then I need you to unpack. How is it saving you time? Cause if it's just saving you time and I don't have to learn a whole bunch of other stuff, then I would say that's actually bad, or bad's a bad word. But it's might not be the best use of the tool. Because the reason why I say that is I know we all have busy lives. I know we all want to jam as much as possible into our lives, but what we actually always sacrifice is the opportunity to learn.

Welcome to the Circuit Breaker podcast, where we challenge the status quo of innovation and new product development. We'll talk about tools and skills and methodologies used to build better products and make you a better consumer. I'm Bob Mesta and I'm the co founder of the Rewired Group and I'm one of your co hosts and we're joined by Greg Engel, who is my co founder and chief, Bob Interpreter. Join us now as we trip the circuit and give you time to reset, reorganize and recharge your brain to build better products.

Hey, Bob.

Hey, Greg. What's up, man?

So today we're going to talk about something that I'm going to screw the name up a bunch of times, so everybody's just going to have to forgive me, but we're going to talk about Chat GPT.

Oh, my favorite.

And the reason why we're going to talk, you say that about everything, so I'm not sure, dude. I guess everything's your favorite.

Everything I like.

I just like anything you talk about your favorite or you hear about or you learn about.

So it's cool.

But really the reason why we're talking about it is because I'm not a big social media guy, but the last couple times I went on LinkedIn or went on Twitter, people have either tweeted at you or or posted to you or even just to me about how they've used Chat GPT to do jobs interviews or summarize a book or things like that. And it kind of pains me a bit when I see that or hear that because I'm afraid that we're actually.

Outsourcing thinking, yes, that's my biggest fear with it. I think it's a really good search tool and maybe summarizing tool, but it's not. It doesn't give the Subtleties of what the meanings are. And so it tends to create, in my opinion, pablum, that higher level stuff of like, oh, it's gotta be easy and fun and blah blah, blah. And you're like, okay, what does that mean? And so there's no context. And so I think the other thing is that they can do an interview and it can help summarize the interview, but it's the thinking between the interviews that are way more important.

Well, I want to challenge that because can it really summarize a true Jaws yellow interview? Because it's just going to give you the words, it's not going to give you the intent because they can't actually see the intent.

Yes, the way the algorithm works is it's looking at the next highest probability of words. So it doesn't actually have logic. It's based on kind of the data that it has at the time and looks at it. And so it's again, it's a summary tool, I think, if anything. But it's not necessarily, it doesn't get to what we would consider the essence of the job or the detail of the unpacking of it.

And what I'm afraid of when it's a summary tool, especially using it in a jobs you've done interview, is we're going to summarize to those belief systems that everybody already has it actually, it actually is going to force it more towards the supply side than the demand side because that's what's out there, there. Right. So I'm afraid that by putting it through there, and I understand why people want to put it through there, because they think it's helping with analysis because it's counting the words, it's doing those types of things. The problem is that's not really the analysis. The analysis is trying to figure out what were the intents of people and the patterns and then what context and things were happening. And a lot of times people don't give you the whole context, they give you clues. And that's where you say the thinking. Right, because that's the thinking of how do we now put together this puzzle that we don't have the box to see what it looks like. And we're trying to put together this puzzle of this interview without the box, without the instructions. And that's what the true thinking of Chosmy Dunn is, is that trying to put together those puzzle pieces, it's also.

The human part of all this. Right. And so what happens is it's like what we used to call, I don't know 10 years ago what we call jobs washing, right. Where people would sit around in a conference room and kind of guess what the jobs would be and kind of hypotheses, but hypothesize what it was but never go talk to anybody. It's the same problem is that you can take interviews we've done or interviews other people have done and kind of put them through ChatGPT, but it doesn't actually help you have that understanding. It just actually builds the summary.

Well, and I would say again, the bad summary because it's just counting words or it might even change a word, it might change the word from easy to pleasant to do. And it's like, okay, that's total. Those are totally different things.

Well, it depends on the intent, the context wrapped around how they said it. And so all of a sudden they're assuming, in some cases they assume like, like a thesaurus, that the language is very similar, but in some cases it's very, very different.

Right.

The thing is this is, I want to, I want to make sure we understand like, like for doing these, for doing jobs interview. It's, it's more about discovery and understanding the subtleties. And so to be honest, it's like, it might be a way to summarize, but like it's a great tool to prototype, to learn. Right. In other cases. So like I just want to make sure in the terms of jobs, I would say it's a dangerous thing because at some point if you don't really have a good understanding of what the jobs are and you're, and you don't actually have the notion of intent and the summary and the subtleties behind it. The chap GPT can come back with what seems like a good job, a clear job, but when you actually unpack it, it's not clear because you don't have the detail behind it of what people meant.

Right. And you know, to your point, we're not trying to poo poo it. We're not saying that it shouldn't exist. That's not what we're saying at all. What we're saying is understand. And this is where us humans have to understand how to use something, how to use a tool. Just like you have to understand how to use jobs. We've done right chat B GPT, see.

Is a tool and we have to know how to use it. And I've heard some schools that I think have a really good take on it, which is fine, go ahead and use it as the starter and see what other People have written and give you a starting point, but then add your original thought to it, because that's what we're trying to do as humans, add original thought. If we're just going to regurgitate stuff, then we stop thinking. And if we stop thinking, we stop humanity. So that's what scares me about it, is those types of things. And then the other thing that scares me about it is I saw somebody put a book through it, right, and said, summarize the book for me at some level. And I'm like, okay, that's dangerous. Only because what I know when you write a book and we went through it a bit is we have an intent. The customer or the person reading the book doesn't have our intent.

They have their context.

They have different jobs. We've done. They want out of a book, right? So you already have a distortion of what is going to happen, right? Because we have an intent that we're writing the book for. They have an intent that they will how they want to receive the book. So there's already a disconnect, there's already a possibility of missing misalignment. But now you add another layer of distilling of this thing going out and saying, okay, if this is the summary of the book, let me change this word from prototyping to experimentation, or let me change this word from liking to something, I don't know what the opposite would be, or another word pleasant. And now you've actually distorted even more from our view of the author, right? So now it's even more distorted. So if you're 1 or 2% off at the beginning now you could be 5 or 10% off because it might not even match what you're trying to get out of it.

This is where I, the way I talk about that is they're getting more and more efficient, but less and less effective, right? At some point, like who give me a summary of the book so I don't have to read the book. And so here's the summary. Okay, I got the gist of it, I can move on. And again, I think there's intent behind it. And so again, I think ChatGPT can be a useful tool to help, like with starting points, with, with prototyping, with having, you know, contrast to create meaning, some different things around it. But at some point you have to understand the content that you're actually asking to summarize in order to take it to the next level.

Well, I think I want people to ask themselves a question when they go to use it. Is why am I using it? Why am I using this? What is it going to help me do? And if. If the answer is it's going to save me time, I might be okay with it. But then I need to unpack what is. How is it saving you time? Because if it's just saving you time and I don't have to learn a whole bunch of other stuff, then I would say that's actually bad, or bad's a bad word. But it's might not be the best use of the tool. Because the reason why I say that is I know we all have busy lives. I know we all want to jam as much as possible into our lives, but what we actually always sacrifice is the opportunity to learn or go deeper.

Yep.

And learning is staggered in deepness. Right. Because there's. There's surface learning or theory learning, there's knowledge, and then.

And then there's depth.

So what I'm afraid of is, is everything becomes Cliff Notes, and then do we actually really understand what they meant? And I can. You know, you could talk to Clay's struggle towards. Unfortunately, towards the end of his life, of how people were taking disruption theory and distorting and distorting it to fit a context. That was not what he was trying to say. And even I've distorted what he. What he says. Right. Because my take on it is at the basic principle. What he was trying to get done was say, look, sometimes even when you're a business leader, you make very rational decisions, and you make the right decision for the moment in time, but you might not make the right decision for the long term. And you have to start looking at both, and you have to understand it. And that's my take of what he did, but that's not really what his take was. So I've distorted it as well to fit my narrative or to fit my thing. So we all know it happens, but can we. I acknowledge it happens. I acknowledge it. And by acknowledging it, I can also read his stuff and say, okay, what else was he trying to get across? And I think people had used the word describe disruption as all kinds of different things.

Yeah.

Any new thing was.

Any new thing was disruption.

Right. And that's not what he was saying. He was saying disrupt. Well, you could probably say.

But yeah, the whole premise was that. That the incumbents, the people who are leading a market, basically can be disrupted by somebody who is at the lower end of the market. And that most incumbents would look at and laugh at because at some point, they're not as Good as the incumbent. But at the end of the day, they're serving the underserved and they're actually bringing a new technology to bear to literally get to scale that ends up, you know, basically killing the incumbent. Right. And so it was a very, very detailed, rigorous work around, kind of studying, kind of how the smartest and best leaders can kind of be met misaligned because they're still worried about short term profits and not actually looking at the underserved.

Right. So that, that's what I mean by so if I put his disruption theory book into, through this thing, I don't know what it would come up with, but it's probably not his intent.

Well, and I think part of this is to realize it's a tool that needs respect and that you need to realize it's only going to give you so much. It's only going to regurgitate what's there. It's not going to help you actually with new thought. Right. And so that's why again, I go, even though we've done, let's say, interviews on multiple categories in multiple ways, like we learn something new every single time and we hone and refine and peel back that onion. And so to me, the warning label is, look, this might help you get to a certain point, but ultimately you have to get into the details to get to the next level. The thing that I really like about ChatGPT, though, is the fact that I think we're going to notice this flip, and maybe we already have, but I feel like there's a flip from knowing the answers to asking better questions. And so people are asking ChatGPT way better questions, do you think? I think they're thinking harder about the questions. And so when you look at kind of how it's, it's way better than search. Right.

Well, I, I think it does things better than search for a lot of things, I think. Like I know we had talked in the office with a couple people that are closer to the field than we are, and they're like, look, if I have a technical question like how to fix X, they go to that. Because it does search better.

Yeah, right. That's what I'm saying.

So for those types of things, I think it does well. And I think what you're saying is for original thought or for understanding things, it might, it might search up some stuff, but then you have to go do work. So are actually doing more work or less work by doing this? And that's the question I have for a lot of it. Right. We think we're shortcutting it, but are we actually creating more work for ourselves?

Exactly, exactly. And I think that this gets back to kind of our overall kind of approach and kind of the mindset shift we've had in the last couple of years, which is like this is about thinking, development is about thinking, it's about thinking differently.

Right.

And it's about actually framing things from different perspectives and being able to connect dots and do those kind of things. I think that chat GPT might be able to help summarize, but it's not going to actually connect those dots. Right. And so this is where there's, that's where I think we have to be very careful that it's not going to give us the answer. It's going to give us a better summary of the data that we have to still integrate and we still have to do the work.

And the question to me, if you use it for like jobs we've done and stuff, is it summarizes, but then does it actually bring you a degree further from what the person was actually trying to say? And that's my fear with that.

I saw somebody, I saw somebody take the, the, you know, an interview we did and break it down into its components of a push up pole and anxiety and habit. And you know, here's the statement, here's what it is, but it's like it's still missing all the details of what they meant by it. And so this is the, and this is the debrief part afterwards. And so to me it's the, it's the arguing, it's the clarifying, it's the unpacking that happens afterwards. And so the raw data itself sometimes is misleading because they use a word over and over and over again and it seems like, okay, this is a big word, but it's like it now has eight different definitions as opposed to.

One depending whether you're talking about being a push or you're talking about being a pull. It could have been different definitions.

Exactly, exactly.

It was an anxiety sync.

Exactly, exactly. And so this is where I think being able to sense those things is important. But I think it's more of that is decided in the debrief than it is in the interview because the interview is just a lot of pieces of data and then ultimately we're actually connecting those dots to say what really was pushing them and pulling them, etc.

Well, I think it's in both because you have to have the right questions and the right thing to get to it. And we're going to do a podcast. More on that in a minute. Yeah. I think what we're saying is, I mean, to kind of summarize, look, it's a good tool. No one's saying throw it away. No one's saying, don't ever use it. We're saying, make sure you're asking your questions. And I think that's, to your point of you think people are doing better questions, which I don't know if they are or not, but stop and ask yourself a question. Why am I putting it in here? What is it going to help me do?

What progress am I trying to make.

By putting this in here?

And what are the limitations of what I'm going to get from it?

And the easy answer for people is to save time. Well, why are you trying to save time? What is it you're trying to save time with? Because if you have to write a column or a blog and you want to get an idea. Yeah. I think that saves you time because that saves you research time. Well, and if, if you say, hey, it's going to save me time because I don't have to do the work and I don't have to think, well, then I think you're doing something. I think you have to rethink that.

You'Re going to be in trouble.

So that, that's what we, that's all we're saying, is take the time to actually figure out why you're doing it and what's going on. I mean, and I could tell a story like, my mom passed away recently, and I had to write the, the obituary. Right. And I don't know how to write an obituary. Right. And I, I, I kept thinking, should I put it in there and, and have it help me write it? And the struggle there was, yeah, it would help me write it. But does it actually take away from my relationship with my mom? Right. Because writing it is the remembering things, trying to do that stuff. So was that the right time to use it or not? And I decided it wasn't. For some people, it might be, but that's an individual thought process that you have to actually think about. And I think a lot of times what we do is we see a new shiny tool and we try to shove everything into it without thinking of what it's going to do for us or what it's going to take away from us. Because in my case, it might take something away from me. Right. So that's what I want people to just stop and think about, why you're doing it. And I get people are just playing right now. I get it. So, I mean, I get why people put our interviews through it. I get why people are trying to use it for analysis, because you got to see if it works. I get it. But don't think it works just because it spits out an answer.

Yeah, yeah, that's right.

You need to also think about what it really did or didn't do for you.

And the hard part is that what you're getting back, especially if you're not an expert in it, you don't know if it's any good. And so this is where all of a sudden it's like, it might be good at some superficial level, but when you start to unpack, to go develop something, I'm not sure that I would actually build based on what ChatGPT tells me to build.

And I always try to figure out, like, we laugh a lot because, you know.

We just laugh a lot. We work hard, but we also have more flexibility than most people, right? So when we're working, we're working very hard. And when we're off, we get to do things, we get to think. And you always talk about the thinking part of it. And what I'm afraid of is people, because their drive of saving time, because their derive of trying to jam as much possible into it, they're actually shortcutting the thinking time. And that's, that's not only do I think it's dangerous, I think it's bad for the person.

I think it's bad for. For a lot of reasons. I think in the end, it's. It's that. It's the. My being the myopic of being more and more efficient, that we're less and less effective. And that's where we lose sight of like, oh, I can do this faster and faster, faster. But now I can't change. It's like, so I look at school, and schools are so efficient that they actually can't change. And so there's no room to do any innovation. There's room, no room to think about anything different. And so when it does, it's like innovation is a luxury because they're not thinking, they're just executing time after time after time. And the reality is, like, they need time to think.

So I think this week, the thing we're asking people to do is just to step back anytime they use a new tool, be it chatgpt or not, why are you using it? What is it doing for you? And also, I want to challenge people to carve out some time in their work schedule to think.

That's, that's, I think the bigger, the biggest thing we're really trying to get people to understand is how do we give you tools and frameworks to think? And I mean, we just started a newsletter and the newsletter is again, similar to the podcast. It's just trying to cause you to take a minute, take a step back and think about what you're doing, why you're doing it, and using a framework or two to help you kind of go a little bit deeper and a little bit better.

So, as always, thanks for listening and hope to see you guys next drop.

See ya.

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