E295 - The Dark Side of Quick Wins

[00:00:00] Nick Roome: What's up, dudes? What's up, bros? How's it going, everybody? We're recording this episode on October 12th, 2023. This is Human Factors Cast. I'm your dude, bro host, Nick Rome, joined today by Mr. Barry Kirby.

[00:00:17] Barry Kirby: Who is this, and what have you done with Nick, and you're bringing him back?

[00:00:20] Nick Roome: No, I'm here. I'm just I'm, this is me.

[00:00:23] Barry Kirby: You're first. This is what happens when you get a couple of weeks off. You get all loosey

[00:00:27] Nick Roome: goosey. Yeah. Look here, there's a lot of excitement in the air. We got HFES. We just talked about it in the pre show, but we got HFES coming up. We're back after being off for a couple of weeks. So yes, I'm in a good mood.

We got an awesome show lined up for you all tonight. We're going to be diving into the world of UX and human factors and exploring how quick wins can sometimes lead us astray. Maybe we'll talk later. We'll be debating modern technology. Such as AI summarization, speed reading, speed listening tools.

Can we embrace this as a primary method for absorbing and understanding literature? Or should traditional in depth reading practices be preserved? All that and more. But first I did just mention HFES is like in a week and a half. We'll be there. Heidi and I will be there in person. Stop by, say hi.

We're going to be in the conference. All throughout the week. I'm going to be recording. I got my like mobile set up here. I'm going to take my UX usability set up. I'm going to be out there around the conference. If you see me come say hi. I'd love to talk to you and get your thoughts about the conference.

There's some exciting announcements that I know of that are coming this year. So I would love to https: otter. ai All of your thoughts and input on that. And if you want, I can record it and I'll put it up on our special live stream that happens Thursday at 8 a. m. Eastern, and that's October 26th, Thursday, October 26th at 8 a.

m. Eastern. We will be live streaming. Hopefully this year, like I mentioned in the pre show, there's going to be a little bit more variety. It's not just going to be interviews this time hopefully you'll see a little bit more representation from the conference itself so we're hoping to get things from, we're hoping to get video and audio from different sessions and like the poster session, the opening reception potentially some more I don't want to promise anything, but potentially some discussion topics and all that stuff.

So stay tuned. We'll be there. Come by, say hi. But Barry, what has, what's been going on at 1202? It's been a while since we checked in. It has been

[00:02:35] Barry Kirby: a while. Cause I've been having a bit of a hiatus, but next week we have a new interview going live. We've. actually got one with Sharon Todd, the current president of the Human Factors and Ergonomics Society of Australia.

She gives us insights into her career, including being an expert witness, which is absolutely fascinating. As well as an overview of HFESA and what it's about, what it's up to, what its main drivers are and what the the main domains they get involved in, they've got their annual conference coming up in November, which includes.

a whole bunch of really interesting people, but amongst many others there is the friend of the our friend of the podcast Chris Chris Reed. He's one of the keynote speakers. So that will be, I think, a really cool conference to listen to and is available remotely as well. What we say in that podcast will be as much of a surprise to me as well as everybody else because I had COVID whilst interviewing Sharon she did a fantastic job in keeping me on track and I can't wait to actually hear what I actually asked her.

That will go live on Monday and we'll be a much enjoyed by us all.

[00:03:34] Nick Roome: Great. I'm glad you're back and I'm glad you're feeling better. And I think we teased it enough. So let's get into the news.

Yeah, that's it. This is the part of the show all about human factors news. Barry, what is our story tonight?

[00:03:48] Barry Kirby: So tonight's story is about how quick wins can betray you or better titled the six essential and fundamental skills in UX research that you shouldn't overlook. Or in brackets, delegate to ChatGPT.

So today's article discusses the importance of fundamental skills in the field of UX research. The author argues that relying too heavily on AI tools such as ChatGPT can undermine the quality and depth of research outcomes. The author identifies six essential skills. That UX researchers should prioritize, and these are learning, listening, writing, creating summaries, analyzing, and problem solving.

They emphasize the value of taking the time to learn and develop expertise rather than seeking efficiency through shortcuts. The author also highlights the significance of active listening during interviews, as well as the importance of honing writing skills to establish a unique perspective. They caution against delegating crucial tasks to AI as AI lacks the ability to prove genuine, to provide genuine insights, they claim.

Instead, they advocate for researchers to take charge of the analysis process and strive for a thorough understanding of the data. Finally, the author stresses that the attitude is key to competitiveness, encouraging readers to approach their work with sincerity. and long overall long term vision.

Overall, the article underscores the need for researchers to invest time and effort into developing their skills and not solely rely on AI tools for quick results. So Nick, you didn't use any AI at all to get us to where we are tonight. You did it all from scratch. You've got a thorough understanding of the topic we're going to discuss tonight.

What are your thoughts on the article?

[00:05:27] Nick Roome: Hilarious. Thank you. Yes. No, we use heavily use AI and all of our production. So here we go. No, I think, look, there's, I think there is a valid argument to be had here where the push for. Efficiency and speed might actually be contributing to intellectual laziness or however you want to phrase this to where you're outsourcing this cognitive effort that you would use to sit down and process something in your research.

The article sure is an article and I feel that you and I are going to be aligned on this approach that it's. Not necessarily that old school methods of learning reading or research. Those are not outdated. Those are still. To be done. It's just that these modern trends towards speed and convenience can actually help us out in a lot of ways to speed up the effort and the article calls these things quick wins and how some of these things can be drawbacks.

And I see where. These chat GPT delegations might come in and be less than ideal, but let's talk about I'm curious on your perspective here, Barry, what do you think

[00:06:55] Barry Kirby: I can? I can see where the articles coming from in terms of, the idea that there is people out there and we have. seen examples of people just chucking, I don't, it comes through my Facebook feed, my LinkedIn feed all the time.

People using he's the cheat sheet for chap GPT. And if you haven't got this cheat sheet, then, this is how to structure queries and to get all your results. And I get that. That is, I think that from that fear. Perspective or people just using chat GPT without any thought or consequence that's valid.

However, this article feels to me to be a bit of a cry, cry for help in many ways. Again, this fear that AI is going to take away the UX job or maybe even broader. I think it, it doesn't just talk about UX. I think you could put that against research in general. But it does feel the way it's written.

If I could be so bold as being quite patronizing. Potentious elitist this idea that you have all the time in the world to be able to thoroughly research a particular topic, particularly if you're doing UX role or a an applied research role that you've got all the time to do all that sort of stuff.

Just not that's not my understanding of the world as it is today. We are having to do more and more with less and less. And so we don't have the time to, do necessarily only the way we used to be done. But AI is a tool and the real skill, it's like any other tool, any other method that we use, there is a places where it can be really good and really useful.

And we, we use it but also where it shouldn't. There's certain things that it's not good at. And part of the skill is knowing where to apply the tool and where not and understanding even where you do apply it, what the limitations are. I, we've joked about it about, but the podcast, I use AI in some of my workflows but then.

Equally, there's more time where it takes more time to use AI, evaluate what you've had and rewrite it and do all that sort of stuff that you might as well have just done it yourself in the first place, but, and that, that comes with experience of using it. This article does highlight, our world is fast moving.

There are new theories, new ideas, new case studies coming out all the time, but I also feel that this is. It's knowledge shaming which is a phrase that I just made up for purely for this for this review that it's the idea that how people pick up their knowledge and use it so people who do read summaries rather than read whole books If you don't have time to read whole books, I don't have that time any more than I used to.

I love reading but I don't have time to sit down and go through all that sort of stuff. So I will probably more skim read and then dive into deeper stuff. Or read summaries and then use that as a pointer. We've talked about this before on other episodes about listening to audio books or podcasts at one half speed or double speed whilst you're doing other things.

It's not because you really want to do that. It's because that's how you're making the best use of your time. And they're equating that with putting minimal effort. Whereas I think that's actually managing the best type, best use of the time resources that you've got available. So yeah, that was a bit of a long rant in of itself.

I think it's, I think we, I think it's worth us going through the different areas cause they do highlight these six different areas. But overall. I think I agree with you that the principles behind it are not necessarily wrong, that there is stuff to be done this idea that that it's all to be blamed on AI and AI is completely invaluable completely useless, sorry is going a bit far.

[00:10:26] Nick Roome: Yeah, we've talked about this before on the show, too, where it's compare AI to other technology that's come before, like a calculator, right? We're just going to need to learn how to use, you wouldn't not use a calculator in mathematical school. Analyses or whatever, just because it's a new tool and you fear that it might get something wrong, that's, I get that if it was a new thing and people were unsure about how it worked, but AI, we've talked about this, is at the worst.

Place. It's going to be right now. It'll only get better over time. And it's you're right. We have this time efficiency trade off where we need to get deep enough to understand some things like make it a literary smoothie easy to consume, no chewing. But if you think about some of these, like deep analyses.

I still think there's a place for that in like meta analysis. But yeah, you're right. Let's go into the six points that they bring up here in the article. And I'm just getting this up on my end. But basically they have six points that they make about the different skills that you should have the first one being learning.

I'm gonna go through the list and then we'll talk about each one of individually. Learning is the first one. Listening is the second one, writing is the third one, creating a summary, analyzing, solving problems. Those are the six. And

[00:11:52] Barry Kirby: It's interesting, isn't it? When you look at learning, for example, the, one of the quotes in there that I find really interesting when it comes to learning don't pursue cost effectiveness, I'm sorry, but absolutely pursue cost effectiveness because it's the, and it's that it's not just time cost effectiveness as well is if you've got.

If you've got a significant amount of time and you know you want to, so we're doing a project at the moment where we need to get really down deep and dirty with what is a fairly new area of research. And so we've budgeted in time to do significant amount of reading because it's new and we, there's low, we need to read around the subject, get that.

But there's times when you need to be able to just pick something and get, you may maybe spend, I don't know, maybe you might've got an hour or you might've got a couple of hours or half a day and you need to be able to get the most information in that period of time. So you've got to be able to focus and allow yourself to be as effective in you as you can in the time you've got available.

And if AI has got a role to play in that, absolutely use it. I don't know. Am I just being a bit naive here, Nick? Or have you got a different view?

[00:13:09] Nick Roome: No, I don't think you're being naive. I want to bring up another quote here that they bring, that they say, can a baseball player expect good results by having a machine replace their catching practice?

I think what they're trying to say there is if they had a machine catch for them, but if they had a machine pitch to them to catch, I think they could absolutely have good results. I'm flipping that analogy, right? So you if you replace the human with the machine. Yeah, they're not going to improve.

But if you use a machine to augment the humans capabilities, you're absolutely going to be better at it. What a basketball players solely automate their dribbling practice and focus only on slam dunks because it looks cool. No, but they might have. I don't know an AI opponent that might act in predictable or unpredictable ways that emulate a human that they could then practice against.

I think these points are not good points. I think that there's the argument that they're trying to make is not a great one. And I don't want to sit here and just rip on this article. It's just that you and I agree here that I think

[00:14:15] Barry Kirby: should be used. There's a, there's there's a deeper argument here, I think, which is probably worth drawing out, that fundamentally AI cannot teach you, cannot just embed knowledge in your head.

We have to go through a process of learning, and it doesn't just happen by simplicity. You can't, it, You can't just inject it into your head. You have to be able to read it or watch it or whatever it is, understand what it's about, make that sit in your brain, and then be able to regurgitate and use that knowledge and information.

AI has a role here in terms of being able to maybe identify salient points. It could even be in the way that it manages your time to help you understand how much time you've got to be able to dedicate to this with some sort of scheduling and stuff like that. But... What it can't do is fundamentally make you learn.

That is a role that is individual to everybody. Some people read stuff and almost by osmosis, take it in particularly really experienced academics can read a paper, take that in and summarize it brilliant. Cause they're very experienced at it and write, writing papers, which we'll come to later.

That's great. Other people, myself included, if you're reading a paper, you might have to read it two, three times to really nail them salient points. And if it's a real, one of these ones that blows your mind the highlight has got to come out and highlighting the salient points and drilling that sort of stuff down.

This is where I think, yeah, this article is right to a certain extent you cannot replace the learning by AI, but AI can help you do it more efficiently and more effectively and help you learn what you need to do in the time you've got available, I think. So that's not having a, that's not kicking the article as such, that's bringing up the salient point, which is perhaps a point that they should have made.

[00:16:03] Nick Roome: Yeah, I think You're right. I just, to me, almost all these points can be picked apart. And I don't know if I necessarily, you want to, I don't know if I necessarily want to spend the whole time picking these apart. I feel like there's a lot of material to do that with. But I guess like for me, the more cognitively challenging thing would be to stretch our brains and see what are they saying here?

I agree that using it as a shortcut should not replace learning. You should use it in conjunction with learning or use it effectively for learning, but not necessarily in as a replacement to learning the thing to begin with. Why don't you go over the next point since I brought up the first one there.

[00:16:54] Barry Kirby: Listening is the next one. And what they what the author's suggesting here is that rather than using like auto transcription tools and things like that, that we should be listening and taking our own notes through particularly through UX interviews and things like that. And I think this goes down to personal style because.

My own personal thing, whenever I do interviews, where practicable, I always have two people in the interview with me. I will have myself who is leading the interview and I will have somebody else taking the notes because I like to, when I'm doing my interviewing, I like to do active listening.

But in really listening to what they're saying, not trying to not spending my time trying to scribble down what they're saying in the hope that I get it all. But if I got somebody else taking the notes, then I know I can be asking the questions, asking my foot, the follow up questions that I think are relevant at the time.

And so now what I've done, and if I did this fairly recently, is if I was doing a team's interview, I didn't have anybody else to hand switched on the auto transcribing. Or did the transcription afterwards. And that allowed me to basically do the interviews in the way that I like to do them.

Be able to do that engagement and do the transcription at the end. It wasn't absolutely word perfect, but I would say it was 95 to 98% there. It meant that I could then go through it and make the couple of changes that need to be done, but I wasn't having to worry about writing everything down at the time or potentially, miswriting things down.

And even in this case, not, I didn't even have to worry about whether my partner was writing everything down properly. So I think tools like auto transcription and things like that are really valuable. To us now that if you want the verbatim piece of the interview, that can happen in the background.

Now it's not a foreground task. You can now focus more on the listening part. So I think that enables us to do it. But they, in the article that they highlighted, they highlight that if you write your own notes. And there is certain people who doodle, I think have this as well is because I can do, I do this if you're doodling whilst listening to what's going on, you've got more chance of remembering what's been said because you're, because you do, because you basically align what's been said to what you're doing.

With your doodle or whether you're writing your notes. So for some people that ends up being a more makes the experience more fulfilling. So fundamentally for me, whatever works for you, whatever works to help fit your style of interview your way of working. I think go for it.

I think both views are equally

[00:19:32] Nick Roome: valid. Yeah, I think the. The thing for me with this point specifically with listening that is our job. I'm here's the part where it's interesting to me is that. When you just get a raw transcription, or even the raw input of somebody saying something, an AI may or may not, but is less likely to, introduce bias like where we might be listening for something that we perceive to be true already, and just you know, Sort of validating that assumption where an A.

I might actually come up with something completely different based on the full context of that conversation without any prior knowledge on. And it might actually provide you with a further insight. I also think that when you start to look at Scalability, you can't listen to every single thing every single time even for me, when I go back and listen to interviews, I listen to them to X, so I'm not getting like all the nuances of the pauses, but then, I don't know I get that because I listen to podcasts and other media at 2x and so it's natural in that sense. So I can understand roughly where it's at. I think there's a lot to be said about listening as a skill for us and I think that's absolutely valid. We should be listening, but I think when you introduce those scalability and reducing that bias, I think that there's a lot to be said about that.

And there's not Like I said, AI is at its worst right now. It'll only continue to be better over time. It'll start to recognize speech patterns, better idioms and the underlying intent of different speech ticks. I don't even know what to call them. But I think those insights will become more refined over time, especially if you feed them through an AI system that starts, that, that.

Learning, listening itself. I'm going to move on to the next one here. The next point that they make is pull up my article. I just missed it. Hold on. Learning, listening, writing. Okay. Okay. Let's talk about writing because this one's fun for me. I hate writing. I hate writing. It's the worst. And the thing for me is that.

When I look at a blank slate, it's intimidating when I look at the podcast notes, and if somebody were to say, Nick put together some podcast notes for an upcoming show on this topic, I would go what do we normally do? And then I would start to think about a template. Okay. So I use templates to begin with, and that gives you structure, but it doesn't necessarily give you the language.

And so you can start to fill in that template with language, but what AI can do is it can start to flow together thoughts and organize them in a cohesive way that actually tells a story and is effective for the right audience. And so I don't necessarily think this is a bad thing to use AI for writing.

I think, or at least for a first draft, I should say. In its current state right now, I think a first draft is fine as long as you review it for accuracy and truth and not just accept it as fact because I think AI is prone to hallucination and that is, I think, where the author is trying to get here is if you just let AI run wild and write something, it could hallucinate and link together a couple different facts that are not necessarily true.

They also mentioned that writing skills are important. Yes, I agree, but. Too important to delegate to AI. I don't think so. I think if you can convey to an AI what your perspective is and ask it to write in that perspective or your tone of voice, you can do that with AI. It just seems I don't know. I feel like this is just too much self reliance, like it takes too much time to do it. But am I crazy here?

[00:23:57] Barry Kirby: No, I think you're right. It makes me, it's interesting because there's a, to quote a bit of the article, it states however, it is quite obvious when you use a chatbot for writing.

There are tools available that can detect whether your text was written by AI or not. If you work at an agency or a consultancy where you offer design services. To clients, imagine the consequences if your clients discovered that your work was entirely composed by a chatbot. Would they trust you and be willing to pay for future projects?

Now, I was quite Intrigued by this paragraph this phrase, because actually when they said, it's obvious when you use chatbot for AI writing now, both me and you, when we play around with stuff, we know when something's written by chatbot because we use it quite extensively. And you just know with the structure way things are put together overall.

Oh yeah. In the main, but the fact that they say in this it's obvious there are tools available that can help you detect it. Actually that means that it's not actually obvious in the mainstream and some of the stuff I've put out. So we maybe some like marketing material and stuff like that has had its initial source in AI.

The way that you describe it is absolutely perfect that you. They've been struck with that blank page. I could be struck with a blank page for half a day of not knowing where to start. And you've got handrails that use structures, templates, things like that. Whereas now you can chuck it into chat GPT and say I want to write something about this.

Where do we go? Slightly better. Prompts on that, but you don't mean it's, you make that, and it at least gives you something to start with, to get the mind going and things like that. And when I've written things like articles within the first person so I write a few articles for a couple of magazines now and maybe for like presentations and things.

I normally, probably never use much of the original material that chat2BT give me, but it's allowed me to kickstart my thinking process. But fundamentally, if they're saying that you need a tool to detect it. It's then not obvious. So we need to be able to say it yeah, it goes back to what I said at the beginning that the people who are using ChatGPT and stuff as their final product, yes, they're the ones who need to be highlighting that's not the way that you should be using the tools at the moment.

Maybe in the future we'll get there. As you said, there's going to be an evolution. But right now. You use it in a way that is a good starting point. You shouldn't use it in its raw format, but let's not take away from the value of what it can do because it can write a downside better than I can.

Quite a lot of the time. So I like having the initial ideas, being able to put them into chatGPD and it allow me to take me on a journey of of me producing a final product.

[00:26:34] Nick Roome: So we're halfway through this list. I want to make sure we have time to address every single thing here because I feel that in this article, they almost start with the weakest evidence up front.

And I almost feel like the last three or specifically the last two are the strongest points. So I want to get to those. I know you have strong opinions on four. Do you want to go over for creating a summary?

[00:27:01] Barry Kirby: Creating summaries for me is almost where AI is strongest. The fact that you can pump your stuff into it and it will bring out decent summaries for you.

Now, again, it's not, it's a tool, it's not the be all and end all, but what I really like it for, and I didn't really value it for until I did my, I would say last seven or eight sets of interviews most recently within the past few months, that it can really help, and you mentioned it earlier, identify potential bias.

It's caught me out that I'm not saying I'm brilliant at this sort of thing, but I didn't realize certain elements of where I was inflicting my own bias on some of these interview summaries and it's bought out some of these, but I just, I was like, that's really valuable.

That's really good. That's improved the quality of my research. And so I'm now making practice that I will, I still make my own summaries because I think there is value in doing that you get. you'd allow, you have to get stuck into your own research at some point. And the summary for me is the first really good point of doing that because you get in, you actually look at what you've got and you bring it together and you have to sum it up.

And but I'm now making a real standard thing that I'll do my own summaries, but I will also run it through something like chat, GPT, because they should roughly tally up. Or it will bring out some ideas that I hadn't necessarily thought about, or maybe I've couched them in a different way, or it will couch some of my ideas in a different way.

And it allows me the opportunity to think about why it did that. I might disagree with it, but it allows me to think about it. So that whole idea about I'm not saying it replaces what you do, because as the article says, you, it's where you put a lot of your own thought, your own influence into it, that is absolutely right.

But. AI does actually allow you to put some more rigor into your summarizing, personally, I believe.

[00:28:47] Nick Roome: Yeah, I think summary is a really weak point. I think it's probably the weakest point. I think it does a really good job of summarizing things that are there. And yes, you should be able to summarize something, by inherently understanding that thing.

So I get that point. If you have a lot of data and you're trying to summarize all that data, it's easier to do. Is it a short, is it a quick win? Yes, absolutely. You're having something go through all that data very quickly and say, what is the theme from this? And I would, I think there are correct ways to do something like that, where if you are If you're going to do that analysis, or if you're going to do run that prompt or whatever it is, have an idea in your head before you do that.

So you're not biased in 1 way or the other, but it can either confirm or like you said with your initial summary, right? You run it through and it might come up with something else. And that's additive. It's not the base. It's Additive to what you've made, and I think that's the right approach here when I get into analyzing.

And I think, like I said, the last 2 analyzing and solving problems are probably the strongest points. This author has towards using as a quick win. I think analysis is a long way off right now. I think it can't necessarily understand or embody a specific role looking for specific things with all the nuance that there is.

I agree with that. However, There are certain analysis tasks that it can handle, such as summarization or even reporting on an analysis. If you want to say make this APA format. Really? You're going to say, I can't use AI to do that? Verify. But instead of hand jamming it, why not just use a shortcut and get in there and do it?

I think... Yeah I'm not going to go any further. What do you think? Analysis? I just, no, I agree. I'm

[00:30:55] Barry Kirby: At my end here. Yeah, no, again it's almost repetitive. What we said, it's a tool. And I, if you're going to analysis you, if you want to analyze a whole set of data using SPSS or Excel or pick another tool, then you would use it because that they're great statistical tools, they're great analyzing tools, why wouldn't you use?

An AI tool that can do that level of analysis for you to help you get to an answer quickly, as long as you could, with SPSS, with Excel, whatever it is that you set up, you can trace back how you got to the, as long as you know how you got there. Awesome. And it will take you take the time give you back the time to do more interesting things.

[00:31:32] Nick Roome: I will I will bring up a quote here because I find it laughable. Take charge yourself. The process simply requires attentive listening, diligent note taking, and a systematic approach to categorizing information and identifying patterns. Easy. What

[00:31:49] Barry Kirby: about the rest of it? Oh, is that all the numbers?

[00:31:53] Nick Roome: Easy. Follow the step by step process and strive to gain a thorough understanding of how the analysis process works.

[00:32:02] Barry Kirby: What, just by category? They haven't started the analysis process. Anyway in the interests of time, the one I will go largely and say, yes, I think they're right, is this whole problem solving piece.

I think there is the human brain, Is brilliant at imagine imaginative solution hearing the the problem solving in the wider sense, coming up with wacky ideas coming out with things that were left field. But a lot of that, a lot of the. Really creative. A lot of the truly brilliant imagineering solutions are based on experience, are based on things that you've seen before that is the whole the whole idea of innovation is that, innovation isn't just coming up with brand new stuff.

It's about taking stuff that you've seen in maybe a different field, a different environment, a different world, and bringing it into this new end environment, this new area and applying it. And we don't tend to that there is a, what's that say that there's nothing new in the world. What you, and you don't just look at a problem, come up with a miraculous solution.

You come up with something that you've never seen before and apply it here. And this is where the likes of chat GPT, we talk about that level of AI would struggle because they could only really analyze what's there or say what's happened since. Since before 20 2021 we could argue or discuss about the future where we look at artificial general intelligence, things like that, where first Paul Simon scares me every time.

But where we're at the moment, we don't really have AI there that will give you that, that spark, that that light bulb moment. I don't think, but again, it can help you get along the way, but this is where the human brain is still brilliant doing this sort of stuff.

[00:33:43] Nick Roome: And I don't necessarily think it's like an all or nothing either. I think I can still be used here. You can prompt it in a way that says how might somebody in this role handle this type of information and it might give you different insights and how other people might think about it and. You and I have talked before innovation being an application of one solution from one domain to another domain, and that might get you there.

So I don't want to go too deep into this because you're right. We're short on time. But I think, overall, this article it doesn't hit the mark for me. I think there are some good points here that like, yeah, don't let it do everything to completely write it off is just something that's impractical with where we're going with technology.

And I think that there's like a lot to be said for. Learning to use these tools in ways that augment these things that this person is talking about, because yeah, flat out, AI can't do all this, you're right, but it can augment and help us with those short wins. So I don't think this is necessarily a dark side.

I think this is, you need to learn how to use the force here. To really do well.

[00:35:04] Barry Kirby: Final thoughts, Barry. Yeah. And I guess the article itself I felt was just a slightly pious attitude to this, it doesn't really express. Nowhere through the article does it say why actually using it is a bad thing.

It doesn't say that you're going to get necessarily bad results. Which I think what we've highlighted through what we've talked about, you can actually get bad results if you don't, if you don't use it properly. And as you quite rightly say, it is a tool that needs to be used in a measured way. And you need to learn about where it's good, where it's bad, or where to stop and what the human intervention needs to be.

The fundamental thing this mentions chat GPT quite a lot is this whole idea now around prompt engineering. And I think that is an art as much as a skill. If you just put in a simple problem that says, give me that, give me, write up this article. It will give you something akin to that, but the more nuanced you make your prompt, the more you bet you work on your own experience of developing a better prompt, which takes time.

It takes effort. Then you do get better results. So it's not just this idea that chat GPT is just a simple, quick win actually to you. If you use it well, you put it, you have to put time into it. In the same way that I would use put time into learning how to use a method properly from NASA TLX all the way through to writing a literature review.

So it's a tool as you quite rightly say. It's not that it's not going to change our world, but hopefully it'll make it a bit better and enable us to do more stuff.

[00:36:28] Nick Roome: I can't wait to see what chat GPT says about this transcript. All right, thank you to our patrons for selecting our topic and thank you to our friends over at UX Collective.

I don't know if they'll be our friends after this one. For our news story this week, if you want to follow along, we do post the links to the original articles in our weekly roundups in our blog. You can also join us in our Discord for more discussion on these stories and much more. We're going to take a quick break and then we're going to do that thing that we did last time that turned out to be okay.

Stay tuned.

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Oh, we love our patrons. Huge thank you as always. Always. To all of our patrons. But we especially want to thank our Human Factors cast. All Access and VIP patrons. Michelle Tripp and Neil Gainey. Patrons like you truly keep the show running. Even in the off weeks. It is truly something special to have all of you as supporters.

I can't say how much it means to me. But we have something else to talk about. Hey Do you know we have a merch store? Do you Wha I'm gonna do away with the AI written ads for this one. Do you wanna look sexy for HFES? Cause that's next week. No. Two weeks from now. Do you wanna look sexy? I got the solution for you.

Go to our merch store. And we got sexy hoodies. That you can use to impress your colleagues. We got some sexy stickers that you can double as pasties. I don't know. We got a merch store if you want to support the show. And look sexy at HFES in two weeks. You might have to pay for expedited shipping, but

[00:39:53] Barry Kirby: how cool would it be to have a whole bunch of people turn up to HFES in Human Factors cast, hoodies and t shirts and beanies and things like that, just showing their support for the Human Factors community around the world. That'd be awesome. We

[00:40:09] Nick Roome: have like other stuff on that store. That is not just our logo.

We have it depends all over the place. We have, I'm going to human factors the out of this. I'm going to, there's there's no such thing as human error, user error. There's a bunch of cool stuff up there that's based in human factors culture. So go check it out. That's my plug.

You want to look sexy for HFES. Anyone in the press, go to the Human Factors Casper store. Alright I still don't have an intro for this. It came from the debate stage, we can do that.

That graphic is so dumb, that it doesn't fit anymore with the debates. But

[00:40:49] Barry Kirby: the music is really

[00:40:50] Nick Roome: cool. I'm gonna keep the music. Absolutely. I like the audio. It's just the visual. And I joked about this with Blake a long time ago. That visual sucks. Okay. We have a debate topic for tonight. Okay, you ready for this?

This one's going to be related to the show that we just had. Should modern technology such as AI summarization and speed reading or speed listening tools be enhanced, or sorry, be embraced as primary methods for absorbing literature and information, or should traditional in depth reading practices be preserved?

Now, Barry. You've opted for the more difficult choice tonight, I feel.

[00:41:35] Barry Kirby: No, I've gone for the easy choice because I think we should be arguing for preserving traditional in depth reading practices because otherwise, what's the point? What is the point in us coming down and doing stuff and learning things as a species?

This is going to be the fundamental to our survival in the future. If we don't have deep cognitive engagement with what we're doing, we don't have our critical thinking skills, we don't understand what it is that we're actually reading. We can never be empathetic with the people that we are listening to, engaging with.

gaining the knowledge from and all them other cognitive skills that if you're just doing a superficial review or you're just half listening to what people are saying, or you're getting your fancy AI tools just to do all the work for you. You don't get that depth, that level of knowledge. Your brain has to go through them simple processes of engaging with the material that you're working with to allow the neurons within your brain to make the connections that you need in order to, to not only just develop a way of putting a report out there, but you need to get that longer term understanding of what you're doing and being able to regurgitate, but also in future future endeavors in a way that will allow you to solve the problems of the future.

So that's me done. I've clearly won. Okay. You win.

[00:43:01] Nick Roome: Thank you. All right. Let me start with my opening statements here in this era of relentless progress and change the way we absorb information. Hang on. Let me scroll up must evolve to match the rhythm of our fast pace. World efficiency is no longer a mere advantage.

It is a necessity. With the dawn of innovative tools like speed reading applications, AI driven summaries, and audiobooks, we are provided with the unparalleled opportunity to assimilate more information than ever before, and in record time. This isn't just about staying informed, it's about maintaining relevance in our respective fields, without the often impractical commitment That traditional deep reading demands.

Moreover, these advancements aren't just accelerating our learning. They're breaking down barriers for those hindered by learning disabilities, visual impairments, or other challenges. These tools aren't just convenient, they're transformative. They have the power to turn what was once daunting and inaccessible into something digestible.

Inviting a whole new demographic. To the banquet of knowledge, but this isn't merely a matter of personal convenience or accessibility. It's about collective adaptability as the gears of technology and society continue to learn and turn. We too must learn to adapt adopting. new efficiencies in every facet of our lives, including how we consume information.

By embracing these technologies, we're not just learning faster, we're becoming more adaptable, ready to pivot with the world's ever changing demands. It's important to recognize, though, that these methods don't replace the depth offered by traditional learning. No. Instead, they complement it. They provide us with a sneak peek into the range of topics guiding us to those worth our full exploration and deep dive.

It's, this isn't an eradication of the old, but an enrichment of our learning experience. In our current reality, we're bombarded, unprecedented volume of information. Without these quick consumption tools, we're not just inefficient, we're... Potentially lost, unable to discern the signal from the noise. These tools are our compass, helping us navigate the vast ocean of information to find those islands of relevance that resonate with our journey.

In conclusion, embracing these modern technologies of learning is not just about keeping pace with the world, it's about inclusivity, adaptability, enriched learning experiences, and steering our ships confidently and competently through the overwhelming waves. of information that define our digital age.

[00:45:59] Barry Kirby: That's fantastic in your chat GPT written speech there. But does that not highlight the fact that we necessarily need to maybe think about quality over quantity? You've managed to give us a a two to three minute speech there, which was eloquent. It was full of many points. It also had me falling asleep about halfway through, because you could tell by the cadence and the rhythm that wasn't, that was something that was written outside of something that that we were trying to do.

And so maybe there is, so what would happen if your Your, that technology was suddenly taken away. How would we cope? How would we be able to do what we're doing now if we have so much heavy reliance? On AI technologies in order to be able to do some of these things, how, if we were, if these tools for whatever reason, be it through government mandate, because of the fear of advancing technology, or through some sort of matrixy type intervention where we just don't have these technologies anymore.

How would we as a species cope to go going back to more traditional capabilities and routes if we don't regularly. Practice them. And we just rely on technology. It could also argue that again, that the amount of information you can get out of chat, GPT and other associated technologies means that we can put out social media means we can put out lots of reports means we can put out lots of textual based stuff for other.

Technologies to then consume that stuff and auto process it as well. And so we will end up in a state where technology is producing artifacts producing data to go and publishing that data to be consumed by other technological instances. And therefore the human will be outside of that loop entirely.

And that could be quite a scary place for us to be if we don't really think about where the human in the loop ends up and we don't carefully curate that. And there's also the elements around what does it mean to us as people? What does it mean to us as human beings to engage with this type of research, to engage, manipulate, utilize, struggle with and conquer?

The data that we are engaging with as UX specialists, we need to be able to go through. We need to be able to see the patterns, create the linkages, come up with the solutions based on the struggle that it can be to sit to be overwhelmed with a lot of data, but then pick and find your way through it. If we don't have by doing this type of stuff, we get it not only it.

A level of stress relief engaging with some of that stuff, but actually we get the fulfillment, the enjoyment the amazing climax of a design of a development of doing something ourselves rather than having just a machine pop that, that's that type of thing out for you. So I put it to you that yes.

ChatGPT can save us a few minutes. It can put, it can develop some adenine thoughts. It can put the, it can state the obvious for us in a way that we just don't have the time to do, but is it actually going to get us anything new? Is it going to bring anything new into what we do? Or is it going to take away that spark that is the human imagination, the human ability to come up with new solutions in new times and blow ourselves away with what the future can hold.

No, it's not going to do that. The only way you're going to do that is by human ingenuity. Okay.

[00:49:28] Nick Roome: But it might help with that by providing you options. Yeah. Okay. So you just said that's your, okay. All right. All right. Who won that one? Let us know it's time for one more thing. Barry, what's your one more thing this week?

[00:49:40] Barry Kirby: So I will go for I'm going to go for three. Because we've had a couple of weeks off. So today was really interesting. I took an entire day off to go and pick up a new board table boardroom table for our new offices. And we got one on eBay and I had to go and pick it up. It was four hours drive there, four hours drive back.

And what was amazing about that was because you can't use like your phone when you're driving and all that sort of stuff, I had four hours there, four hours back. of just chill, listening to audiobooks, listening to podcasts, and it was forced doing nothingness except the driving task. And I thoroughly enjoyed that.

That was really good. I mentioned, I think in January, February of this year, that we'd be getting plans for the house renovations and all that sort of things for our home. All them plans got canned because everything got really expensive. But I can finally say that new plans and our house renovation has finally started.

We had the build around the other day and he started knocking doors out and started breaking up holes in walls and stuff like that. So that's actually exciting to see something that's taken what, six years for us to get here. Things are actually happening. And the final thing is, as I mentioned at the beginning not only have we got HFES coming up, but in November HFES A is coming up as well.

And so I'd recommend that people, if you want to go to another hybrid conference, that our friends in Australia are going to put on a cracker of a conference and we should try and engage with them. Yeah,

[00:51:02] Nick Roome: great shout. I'm, I have plenty, but I'm going to save some for later. The one that I will talk about is, I managed to get an inbox zero.

No.

[00:51:13] Barry Kirby: Yeah. How do you do that?

[00:51:16] Nick Roome: You just take everything and mark it as read and then archive it and then you're good. But no, seriously, like it was an exercise. It was an exercise and I took hours to do it. I sat at my desk for hours and said, okay, which things do I really need to respond to? Which things can I trash?

Which things require action? And the way in which you do it is Fascinating to like, I looked up some videos and tutorials on how to get inbox 0. If you've just let your inbox get overblown. And there's some really good resources out there. I I think it was probably like 6 months where I just let my inbox just blow up and I just didn't respond to anything and it was bad.

But what I did was I Went through all of them and there's a couple shortcuts depending on what what service you're using. But there's some really cool tricks where if it requires action, you snooze it till later. You've dealt with it for now and it's not in there anymore, but it'll come back later.

And then if you Have dealt with it. Then you archive it and it's not in your inbox. You don't have to worry about it until somebody responds to it and then it'll come back in. And so I've managed to get an inbox zero on both my personal email and my work email. Not the podcast email yet, but I'm working on it or I plan to work on it.

But it's fantastic because then I just, it's there. And if I need to search anything, everything's still there. I don't, it's it solved this hoarding problem with emails that I had that I didn't know I had. Anyway, I highly recommend going for inbox zero if you haven't. And if you don't know what I'm talking about, that just means I have nothing in my inbox except the action items that I need to take care of.

[00:52:49] Barry Kirby: I've just looked at my inbox and I've definitely got inbox zero. And fortunately I've got a number of zeros and some numbers. Yeah, I've got some way to go inbox 10,

[00:52:57] Nick Roome: 000. Anyway, that's it for today, everyone. If you liked this episode and enjoy some of the discussion about AI, whatnot or even UX stuff, I'll encourage you to go listen to episode two 77, where we ask what the point of user stories is.

Maybe we use AI in them. Maybe we don't. Comment wherever you're listening with what you think of the story this week for more in depth discussion. You can always join us on our discord community, visit our official website, sign up for our newsletter, stay up to date with all the human latest human factors news, and stop by our booth at HFES in two ish weeks.

We'll be there in two ish weeks, one and a half weeks. Stop by. We'll be there. If you like what you hear, you want to support the show, show up to HFES. Stop by the booth. I love talking with all of you as you come by that booth and let me know that you actually listen to us in your ear holes. That's amazing.

Leave us a five star review wherever you're at. That really helps the show. You can do that for free. Tell your friends about us, especially at HFPS. Let them know that this amazing podcast exists and sometimes records regularly. Consider supporting us on Patreon. If you like what you do, you want to see more of it.

That is not free for you to do, but it does really help the show out. As always you, any of our links to all our socials, our website and in the description of this episode, Barry, thank you for being on the show and surviving COVID so that I have somebody to talk to we're listeners going.

Talk to you if they want to I don't know tell you how poorly you misrepresented the story.

[00:54:15] Barry Kirby: That's just same old. If you want to come chat with me, then you can come and X with me buzz underscore K that's Twitter for your, all your cool dudes. If you want to listen to some podcasts podcast interviews with some interesting people in and around the world of human factors, then find me at 12 or two, the human factors podcast at 12 or two podcast.

com.

[00:54:32] Nick Roome: Thanks dudes. As for me, I've been your host, Nick Rome. You can bro out with me on discord and across social media at Nick underscore Rome. Thanks again for tuning into human factors cast until next time. It depends.