00:00:03.720 — 00:02:10.810 · DANIEL SIH:

Welcome back to the Spacemakers podcast for a bonus episode on wise AI. My name is Daniel Sih and this podcast is a podcast to help you make space for an intentional, meaningful life. Now we are living in the age of artificial intelligence and it's pretty amazing. I mean, AI is powerful, it's intuitive, it's sophisticated.

 

It promises us that we can do things faster, quicker, with more efficiency. And I actually have to agree that there's a lot of truth in that. But at the same time, I'm also experiencing tension and complexity in the way I use AI and in the way my clients use AI. Because while we're promised that AI will save us time, life doesn't seem to be slowing down.

 

In fact, the more we use AI, the more people are telling me that they're saving time and at the same time, they're busier than ever before. Their calendars are full, their life is full, their their schedules are jam packed. So how does that work? How do we save time and yet have a busier life? And that's the conversation we want to talk about today.

 

I'm so excited to have the coauthor of my new book with me, Paul Matthews. I'll introduce him in a minute. He's an expert in AI, but we've just coauthored a book which will be released very, very soon. We've been working on it for the last six months, and it is so close to being released. It's called wise AI, using powerful technology in a deeply human way.

 

And we're going to talk about what it means to use AI wisely, to experience the power and sophistication of incredible new tools, and at the same time, to do it in a way which is mature, wise, and deeply human, so that we actually experience space in our life and a better quality of life, not simply save time on tasks.

 

So that's what this episode is about. Uh, I can't wait to talk about my new book with Paul and to help you learn how to use wise AI. Okay, Paul Matthews, welcome to the show. I am so grateful that you were able to come into the studio today and have this conversation.

 

 

00:02:10.850 — 00:02:16.810 · PAUL MATTHEWS:

Yeah. Look, I got to tell you, it's been a goal of mine for some time, Daniel, to get on the Spacemakers podcast. So I'm living the dream right now.

 

 

00:02:16.850 — 00:02:29.730 · DANIEL SIH:

Oh, excellent. Well, it's been a goal of mine for a long time to write a book with you about AI. So I am super excited and, you know, and I've been, you know, we've been working hard for some months and really bring on this idea of what is wise AI. For over a year.

 

 

00:02:29.810 — 00:02:44.810 · PAUL MATTHEWS:

I think it's been a great journey as we've been thinking about the technology itself, but also just some of the bigger questions. And we'll get on to the bigger questions behind the tools and the technology later, because I think that's just some of the most important part of using artificial intelligence well.

 

 

00:02:45.090 — 00:03:06.380 · DANIEL SIH:

Absolutely. So look, tell us about yourself. Obviously, you know, my listeners know a bit about me, but tell us about, you know, the great Paul Matthews, the great. And you are, you know, you're a good friend. And I deeply respect and admire your work in the AI space. But yeah, tell us about yourself and how how you ended up kind of in this field of artificial intelligence and training people around the world.

 

 

00:03:06.420 — 00:03:36.020 · PAUL MATTHEWS:

Well, it's a good question because the more you know me, the more you realize that it's actually quite weird. This potential sort of future that we've ended up in now, because I'm not really a tech person, I'm a little bit of a Luddite. To some degree, I've got an old watch. I've got an old car. I've got to man, my fridge does not connect to the internet, all that sort of stuff.

 

Right. So I'm not I don't get really excited about new technology. What I do get excited about is big impact. And I'll tell you what I mean by that. So I'm a third generation teacher, I love teaching, I feel like I was put on the earth to do it.

 

 

00:03:36.020 — 00:03:41.380 · DANIEL SIH:

And you still work as a teacher as well as a consultant and a trainer and a speaker. And I mean, I don't know how you do it, but you must be productive.

 

 

00:03:41.420 — 00:04:54.190 · PAUL MATTHEWS:

Yeah, I absolutely love it. I love it all. And it's all kind of the same thing. My big life mission is to bless other people through education. So it all sort of falls within that. And I was in the position as a teacher where I was teaching a class, and we're talking nearly unlimited needs in the class. The state of modern education, Daniel, is such that you've got a class and the gaps just say on one metric, say literacy, the ability to read and write.

 

The gap is bigger than it's ever been. And what does that mean for me as a teacher? I've got more work to make sure that the lesson I'm teaching is applicable to the student who struggles the most, and the high fliers now pre II to cater for those people. I'm spending my evenings, my weekends, my holidays. I'm grinding myself down to be able to provide for these people.

 

And I'm still not able to do it that well. And so I was hoping and yearning for a long time that there'd be something that would actually help me have the sort of impact in my class that I wanted. And that's exactly what AI did for me. So, like I said, I'm not a big tech guy. Most of the people we deal with in our training don't get excited about technology per se.

 

What we do all get excited about is impact, and it's that impact that helps me help my students learn to read and write more effectively than ever. And we've seen the same sort of impact with the professionals we've been dealing with as well.

 

 

00:04:54.270 — 00:05:41.350 · DANIEL SIH:

Absolutely. And so, you know, just for a bit of context. So now for the last, you know, a number of years you've been on the front foot of AI, particularly in the teaching space. So you write daily social media. You write. You've written numerous books on AI, particularly in the teaching space. You've done a TEDx talk on AI.

 

And and I know you train and speak around, well, the world now, not just Australia on on AI, particularly in teaching, but generally. So, um, that's that's your background. So it's interesting you don't see yourself as a maybe a, you know, a future tech guy. It's interesting. I speak and write a lot on tech, and I have an enormous amount of tech in my life, in my business.

 

But you and I have the same posture, uh, while you see AI as being highly impactful, but you also see some potential negative sides if we don't use AI well, which is part of the wise AI piece, is that right?

 

 

00:05:41.350 — 00:06:26.640 · PAUL MATTHEWS:

That's exactly right, because we talk about it a lot. It's in your books as well. Technology is never neutral. It's going to carry a certain story within itself. And one of the things that a time saving technology like artificial intelligence might be quietly whispering in our ear is that we just need to do more.

 

Right. So because you can do more, you should do more, right? You're busy before you had eight hours of work and you are grinding away for all eight hours. Now you can do it so much faster. Well, you should just jam more into that eight hours. And we're talking more emails, more meetings, more zoom calls, more compliance, all this sort of stuff.

 

And so that's just part of the story that you and I are pushing back against. And so, no, we can actually use this eye wateringly powerful technology, but we don't just have to crank up the speed on the busy work treadmill. We can actually push into a more human life.

 

 

00:06:26.680 — 00:07:13.200 · DANIEL SIH:

Yeah, absolutely. And look, I like the quote from Tim Charles who wrote the next story. He said that technology wears its benefits on its sleeves, but the drawbacks are hidden deep within. And what he means by that is actually, we all know the benefits of a technology like AI. It'll make you fast, it'll speed you up.

 

We get told that every day. But there are negative sides, not just to, you know, what it does to maybe our thinking capacity and our organic intelligence, which you name it. We'll talk about that later. But also the busy treadmill, the shaping of what it does to us if we don't pause and think deeply. So our book is very practical.

 

It will teach you how to use AI, but it also teaches you how to think deeply about using in a in a human way that actually increases the quality of your life and lets you have space for things like deep work, deep thought, deep rest. We'll talk about that later as well.

 

 

00:07:13.400 — 00:07:29.120 · PAUL MATTHEWS:

You're exactly right. So we're definitely not out there saying, don't use artificial intelligence. It'll rot your brain. We're very pro AI like to put our cards on the table up front. We're very pro AI and we're pro AI. But at the same time, recognizing the fact that we're not going to get this right by accident.

 

 

00:07:29.160 — 00:08:08.530 · DANIEL SIH:

Yeah, it's almost like we are pro AI, but we're also very skeptical about AI at the same time. It's that paradox, right? We want to use it really well ourselves, and we want to use it wisely with consideration, recognizing the drawbacks altogether as one package. And that's really what the book is about.

 

Look, tell me about Sue and Christine. So you started the book with a story about two ladies you met at a conference. And. And the more you and I spoke and wrestled with who we're writing for and what wise AI means, the more we came to this idea that this story was the one to lead with and this experience, because I think it frames where people are at, where you and I are at, and why we think this book is important.

 

 

00:08:08.570 — 00:09:14.700 · PAUL MATTHEWS:

Yeah, this was a wild experience. So it was one of my first trips internationally to speak, and my background is in speaking to teachers and educational leaders. That's my buffer zone, and I feel like I can just hit that out of the middle of the bat. But I had a room full, a big conference hall full of busy professionals.

 

And so there is some overlap between education and the profession that I was dealing with here. But I was also I had some bigger questions about how it would translate. I gave my topic and my speech and what they did. It was a bit of a mongrels man because they put me right before lunch. So I flew halfway across the world, probably four days traveling to speak.

 

While people got there. They got like a halfway down eyelids waiting for their lasagna. So we're heading out to lunch after I finished my keynote. I feel this little tap on my shoulder and a lady introduces herself to me. Her name is Sue, and I turn around and I go to shake her hand. She's not in a handshake mood.

 

She's got a sort of furrowed brow and she just goes, Paul, look, I have to say, I disagree. I really don't like artificial intelligence at all. And if I could just press a button and make it all go away, that's exactly what I'd do.

 

 

00:09:14.740 — 00:09:15.180 · DANIEL SIH:

Hmm.

 

 

00:09:15.180 — 00:09:32.540 · PAUL MATTHEWS:

And that sort of stopped me in my tracks, Daniel. And so I tried not to judge too quickly and just press him with a few questions. Turns out that Sue, she was about 65 years old. She grew up in a rural town. The big technological innovation of her childhood was a landline home phone. Wow. All right.

 

 

00:09:32.580 — 00:09:43.620 · DANIEL SIH:

That's amazing how far technology has gone. She must have been very young. But even then, I mean, just she didn't have the internet. She certainly didn't have social media. I mean, all these kind of advancements in mobile phone, none of this has existed, right?

 

 

00:09:43.780 — 00:10:14.220 · PAUL MATTHEWS:

So Sue's living from the landline home phone potentially, to artificial general intelligence. All right. Any one lifetime, there's more change than anyone has ever experienced. And she was just kind of done with it, she said. I just want to get on with doing my job. And she's had to go through all the changes brought about by that tech.

 

You were talking about laptops and the internet and email. She started with no email. Which is crazy because she talked to a lot of professionals. What do they say they do 90% of the time? It's emails, right? And so she's just saying, I just want to get back to my job.

 

 

00:10:14.500 — 00:10:24.460 · DANIEL SIH:

I mean, so it sounds like she was maybe, maybe a tech sceptic, or at least she'd been burnt by the change, which we can understand and relate to. Right.

 

 

00:10:24.500 — 00:10:30.100 · PAUL MATTHEWS:

It's a lot of change in a very short period of time. She can absolutely be forgiven for feeling just a bit frustrated.

 

 

00:10:30.140 — 00:10:51.630 · DANIEL SIH:

Well, I feel that way a lot of the time as well. You know, I mean, if I'm honest, if, if I if there's a choice with, let's say, social media and AI not coming out of the toothpaste tube, I'd probably say it'd probably better if we didn't have it. But in some ways it's here and let's use it well. So there's a sceptic in me as well.

 

So I just, I can kind of I can empathize with Sue to an extent. Right. Yes.

 

 

00:10:51.670 — 00:11:30.430 · PAUL MATTHEWS:

Yeah, absolutely. And look, let me tell you, the next person I met, Christine, was probably the polar opposite to Sue, right? So I sat down at the table, have my lunch, and in comes this whirlwind, and she sort of bounces along the bench seat and sits next to me and says, oh, hi. Paul really loves to talk. Here are the different things I'm doing.

 

And here these are the five apps that I have and the ten new workflows that I've done, and my five day report I can now do in a day and a half. And it's all amazing. Um, the interesting thing, though, for Christine was she was still working in the evenings. She was still doing emails on her phone, sitting in the car while her sons were playing soccer.

 

 

00:11:30.470 — 00:11:41.070 · DANIEL SIH:

Yeah, that kind of frantic, fast talking, fast moving person who is really efficient in getting stuff done. But but there's still that lack of space in some ways. Right?

 

 

00:11:41.070 — 00:12:17.640 · PAUL MATTHEWS:

That's exactly right. And honestly, it sounded like Christine was yearning for that space. And so you've got these two people who, on the surface they appear to be polar opposites. Sue is a little bit of a hater. She doesn't quite get around the technology. She's frustrated by it. Christine absolutely loves it.

 

But the more I thought about it, they actually have the same deep impulse within them. What they both want is space. They want space to think and to breathe and to rest and to connect well with other people. Sue is seeing that coming from no technology. Yeah. Christine is hoping it will come from the technology, but it's not quite working out.

 

 

00:12:17.680 — 00:12:55.640 · DANIEL SIH:

So they're both frantic. They're both stretched for time. They're both change fatigued in some ways, and they're both trying to have a life where they get to do great work, but it doesn't consume all of their life. Right? Exactly. So they want the space and they want the space to be able to plan and to be able to think clearly and and just to not feel like they have to rush from one thing to the next.

 

So I think they're basically the same person, even though they're polar opposites with their technology interests. I love that, you know, but but at the same time, Um, yeah. So you said Sue is avoiding technology because that's how she thinks she'll get the space back. And there's some truth to that, because technology has made our lives busier in lots of ways.

 

Right?

 

 

00:12:55.680 — 00:12:57.560 · PAUL MATTHEWS:

Yeah. We can learn something from Sue.

 

 

00:12:57.600 — 00:13:13.480 · DANIEL SIH:

Yeah. But at the same time, I love that. Um, Christine definitely has it right as well, because, well, technology can also give her space back. So, so so where does where does wise AI fit within that wide spectrum or that polarity?

 

 

00:13:13.520 — 00:13:42.680 · PAUL MATTHEWS:

Yes. And that's the interesting thing, isn't it? Because both Sue and Christine, regardless of their very different dispositions, would benefit richly from wise AI use. And that's a term we settled on when we were thinking about how we use this eye wateringly powerful technology in a human way. And what we saw, and this was some research that you pointed me towards a Microsoft work trend research, where they were saying 64% of people are just having a hard time getting on with their job.

 

 

00:13:42.720 — 00:14:10.730 · DANIEL SIH:

Yeah. We're spending. I remember that report. It was like, we're now spending so much of our time in meetings, communicating about work, collaborating about work, and coordinating work with each other, that there's no time to actually do the jobs that we need to do. So people are working from home because they go to the office, it's party time, or they're just in meeting after meeting and interruption after interruption.

 

Slack teams emails and they just don't get the work, the deep work at least, and the deep planning and the deep thinking done that they need. So there is that real, very real pain point in the workplace.

 

 

00:14:10.770 — 00:14:44.850 · PAUL MATTHEWS:

Exactly. And you know that I see that within the education profession as well. And so as we were considering, well, what's the most human spacious vision we can cast for artificial intelligence, we said, well, look, we've all got this busy work that we're doing. It needs to be done. We can't just not do it.

 

But perhaps that's where artificial intelligence is going to give us a lot of leverage. So what if we could really economize and fast track and expedite that busy work, but not just then increase our capacity for more busy work, which it's so easy to do. That's the gravitational pull. He's just doing.

 

 

00:14:45.090 — 00:14:47.930 · DANIEL SIH:

More to add more, even if it's. Yeah, just to keep adding.

 

 

00:14:47.970 — 00:14:48.490 · PAUL MATTHEWS:

Exactly.

 

 

00:14:48.530 — 00:15:02.650 · DANIEL SIH:

Fill the space. That's Parkinson's Law, isn't it? That work will expand to fill the time available. So if you save time, you'll just feel it with more, which is what you and I are seeing. And that's that's why AI is saving us time. And then we have less time than we had before.

 

 

00:15:02.690 — 00:15:03.290 · PAUL MATTHEWS:

Exactly.

 

 

00:15:03.330 — 00:15:05.570 · DANIEL SIH:

Which is insane. It's insane. Right?

 

 

00:15:05.650 — 00:15:25.730 · PAUL MATTHEWS:

How do we solve that problem? We would say through wise AI and that's using all the time we save and then pressing into what we would call four pillars or four domains. And really simply, we're using the time we save. We're not immediately redeploying it, but we're holding that space for deep work, deep thought, deep relationships, and deep rest.

 

 

00:15:25.730 — 00:16:27.580 · DANIEL SIH:

So deep work is about, I suppose. It was popularized as a term by Cao Newport. It encompasses research based tools like flow, state and concentration getting into the flow. But it's essentially the type of work where you pause, you have no interruptions. You focus on something in a single tasking way for a sustained period of time, and actually experience that sense where I achieved something that really mattered, where my brain was fully engaged.

 

It feels meaningful, and I used my experience and I ended up with something in a that actually matters. So it's deep, rich concentration work that matters. Spreadsheets could be deep brainstorming. It could be developing strategy. It could be planning, it could be developing a website. But it's it's it's not just pushing emails from here to there.

 

We need more and more of it. And we believe that if you can use AI to help you save time on the shallow, simple work and hold that space and direct it to new ways of working, which is not just time, it's mindset and habits, then that's a way of using AI wisely in the workplace.

 

 

00:16:27.580 — 00:17:12.390 · PAUL MATTHEWS:

So deep thought is it really undergirds a lot of these other things. It's just undistracted, uninterrupted time for us actually to think. I mean, one of the things you're talking about all the time is that thinking is work. Thinking is not something we do when we have no work on, and we get a little bit of time to actually just sit with our own thoughts.

 

Thinking is some of our most important work. So we've got our deep work. We've got our deep thought and deep relationships. It's just actually having the space to be able to talk with someone one on one, or meet with a group of friends, or do something where you're not, then tempted to quickly get back to your emails or scroll through your notifications.

 

You don't have to jump out and take a quick call. These sorts of things a deep human, one on one connection that we actually that just makes our life so meaningful.

 

 

00:17:12.430 — 00:18:02.950 · DANIEL SIH:

Yeah. Look, I mean, we humans are connected creatures, right? And we it's funny, like the more the more friends. And we know this, the more like friends we have on, I would say Facebook. It's an old technology now, but. But the fewer, the less time we're actually spending with real people in real places and real times.

 

And yet there's I mean, and it's great to augment your relationships with digital platforms, but to replace them is is nuts, right? So so I think people we don't have enough time for each other anymore in communities to have slow coffees and to have slow walks. And so we, you and I believe that if AI can be used to enable or redirect some time towards slower relationships in the workplace or in your life as a whole, well then that would be a good outcome of using AI, and that would be a wise way of using AI.

 

 

00:18:02.990 — 00:18:28.990 · PAUL MATTHEWS:

Absolutely. And the last one. So we've covered our deep work, deep thought, deep relationships, and then we move into deep rest. So just sort of unplugging powering down for a little while, maybe making space to sort of ponder or wonder or pray, is that inner life stuff that you talk about quite a bit? And so I see a lot of opportunity there for us.

 

And maybe this is one of the best kept secrets about our book. I don't know how you feel about me saying this, Daniel.

 

 

00:18:29.070 — 00:18:30.630 · DANIEL SIH:

No, no, no. People have to pay for it.

 

 

00:18:30.790 — 00:18:48.480 · PAUL MATTHEWS:

Yeah, yeah. But here is one of the things, if you if you sort of pull back the curtain of wise AI. It is a book about artificial intelligence insofar as we're talking about AI a lot. Yeah, but if you sort of pull back the curtain, it's actually a book about living a good life in a world that has AI.

 

 

00:18:48.720 — 00:20:03.770 · DANIEL SIH:

And leaving it living a deeply human, rich, meaningful life. Yeah, that that does meaningful work, but also has like, yeah, rest connection and navigates the tension between using tech regularly and well and consistently. Like we definitely teach people how to use AI. You know, there's very practical tools, which is the magic you bring to this book in particular because you've got so many years of teaching very practical skills on how to use AI well.

 

So there's the practical part. But yeah, there really a lot of it, particularly the start of the book, is the paradigm and the shaping of how we think. There was a quote actually, I don't have the quote in the book, but it was it was along the lines of AI will save you time, but more so it'll amplify what you already do.

 

1. So if your way of working is to be frantic and busy and to not think and to to constantly rush from place to place, AI will just extend and amplify that mode of operations. So we need you to pause and think deeply about what type of life you want, and then to allow AI to be a tool that shapes that. And without that part, the technical how do you prompt?

 

How do you iterate? How do you do all the cyber stuff that we talk about? That doesn't really matter.

 

 

00:20:03.810 — 00:20:50.090 · PAUL MATTHEWS:

Well, exactly right. What really good AI skills without an understanding of your deeper why, your vision, your values, the sort of life you want to lead if you don't know those things, but you do have great AI skills. You just end up going even faster in the wrong direction. And that's actually not where we want to go, is it?

 

So that's why in many ways, I wanted to write this book with you, because I've been doing a lot of thinking about artificial intelligence and technology and simple frameworks to help people of all abilities use it. Well. But you've been thinking about this sort of space and values and structuring your life and deep, true productivity.

 

That's your wheelhouse. So I think it actually takes both flavours and both key ideas, both the technical knowledge and the deeper understanding if we're actually going to use AI wisely.

 

 

00:20:50.130 — 00:21:54.420 · DANIEL SIH:

Yeah. And look, that's what I started. So you came to me and said, I've got an idea. Yeah, I've got an idea. I remember we sat down in a cafe and you said, I've got an idea, you know, what would you think about writing a book on AI? It's so funny. I'd never thought I'd write another book on technology. I always thought my next book would would be out of that space.

 

Probably in a broader, eclectic live space. Um, but, you know, I'm not an AI expert, but I, I am an expert in busy people and how to form habits and how to think deeply about our time. And you're absolutely an expert in AI. And I just I, I just got excited. Um, yeah. The funny thing is, I'll tell you this story.

 

So, uh, well, I went out. We were talking for a long time. We'd had our coffees, and then I thought, oh, I'm actually hungry, I might. Do you want some food? And you said. Yeah, I thought we'd get chips. Right. So I went up, grab the menu on. The lady said, oh, it's like half price oyster specials. So I came back.

 

I never, I never buy oysters, but I came back with a dozen oysters, I think. What, 12 Kilpatrick's like six natural. And I was like, oh, do you eat oysters? And you never had them before?

 

 

00:21:54.460 — 00:21:55.100 · PAUL MATTHEWS:

I said, no.

 

 

00:21:55.140 — 00:22:02.020 · DANIEL SIH:

Don't mind, you poor bugger. You gonna eat snot for the first time? And that'll be the memory of this book. But maybe that we could celebrate with oysters.

 

 

00:22:02.060 — 00:22:11.660 · PAUL MATTHEWS:

Well, dude, let me tell you this. So I went back to the same place in Kingston Beach with my wife for a date night, and I told her about oysters. I said, Albie, we got to eat some oysters.

 

 

00:22:11.700 — 00:22:12.740 · DANIEL SIH:

And she wanted chips.

 

 

00:22:12.780 — 00:22:23.740 · PAUL MATTHEWS:

You've ruined oysters for me for the rest of my life. Because as soon as I sucked down that first oyster, I thought, where's my book? Where's my pen? I should be writing something. I should be getting something down. So there's, like, a work food for me now.

 

 

00:22:23.900 — 00:22:56.310 · DANIEL SIH:

Excellent. Oh, there you are. Well, hopefully we're successful enough, because oysters are an expensive work, but. Oh, dear. All right, look, let me read a quote from our own book, which is kind of weird, but hey, you know, we like the book. Um, it says AI will undoubtedly make us faster. The question is whether will be any wiser with the time it saves.

 

Now we like to have a pause on the Spacemakers podcast to help you think about what we're talking about, and to reflect. This might be a decent time to pause. Is there a question you would want our listeners to think about if they just pause for a, you know, half a minute?

 

 

00:22:56.590 — 00:23:05.070 · PAUL MATTHEWS:

Yeah. So how can I use artificial intelligence in such a way that doesn't just speed me up, but helps me press into the sort of life that I want to live?

 

 

00:23:35.750 — 00:24:58.120 · DANIEL SIH:

All right. Well, hopefully that was a good moment to pause. It does make me think, you know, I mean, I use AI every day. I find it valuable for writing, copy editing, supporting with ideas, brainstorming, helping with frameworks like I find I'm using it more and more and more, which is useful at the same time.

 

You know, I do feel sometimes I overuse it, and I do wonder sometimes whether I'm I'm using it in a way that's kind of busy rather than really considered. So why don't why don't we get practical? Because the, the third section or the third part of our book is about the practices. Exactly. And we talk about ten very specific practices that you've been teaching for years around the world.

 

Yeah. To help people really navigate AI. Um, really. Well, now, we're not we're not talking to, like, AI experts who are trying to kind of take at take that extra level in a very specific niche field, you know, wanting to build AI agents and do kind of deep coding. That's not who the book's for. It's for everyday busy workers who want to use AI well, build their skills.

 

People who are avoiding it and want to start, or people who are using it every day, but just want the confidence to know that they're using it wisely in a smart and sensible way, with the right frameworks and the right processes. Um, so I'm going to surprise you with this. Tell me about License to Learn.

 

 

00:24:58.160 — 00:25:55.520 · PAUL MATTHEWS:

Sure. Um, yeah. So my dad is a teacher. His dad is a teacher. And when I graduated from my master's of teaching, my dad came up and he sort of had this cheeky look about him. We write about it in the book. He came up to me and said, well done, Paul, you've just got your license to learn. And I was kind of expecting him to say, I've got my license to teach, I can go and teach.

 

But he said, no, you got your license to learn how to teach. And that's interesting. The degree was obviously really useful, but what that equipped me to do was get into a classroom and actually then do some real learning in the classroom. Practical, tangible. I'm in the environment I'm going to be working in, and that's what we give people with this book as well.

 

These ten practical principles that we're giving, it's not going to mean, you know, everything about artificial intelligence. You've graduated and you never have to learn. But what it does mean is you've got the right skills and assumptions behind you so that you can go out and start to learn really, really well.

 

 

00:25:55.560 — 00:26:21.479 · DANIEL SIH:

Yeah. And look, AI is changing so fast, right? By the time we've we've tried to publish this book fairly quickly because because of the nature of this topic. But we've also written in a way that we hope and believe that the principles will still be relevant in 3 or 5 years, because we're not teaching how to use, you know, copilot or how to do particular prompts in like ChatGPT or other kind of platforms.

 

We're talking about. How do you engage AI as a large language model tool

 

 

00:26:22.600 — 00:26:39.170 · DANIEL SIH:

in a wise way, and the principles will give you, like you said, the license to learn. I really like that. And when you shared that with me, I've reflected on that a lot. I think that's a really deep process because you need to learn and then continue learning. Right. Because as a teacher, you keep learning, right?

 

You needed the license to be a teacher who learns.

 

 

00:26:39.210 — 00:27:05.450 · PAUL MATTHEWS:

Yeah. There's you need a certain requisite amount of knowledge to actually start learning. Like if I put my head under the bonnet of my car and just started trying to figure out what was going on, I would have no clue. I would just have no clue. If my brother did that, he'd have it figured out in two minutes, because he's got enough basic knowledge that he can actually then do more learning really quickly.

 

And the things are going to be useful for him, because I don't have my license to learn in being a mechanic. You know, it's not going to work.

 

 

00:27:05.490 — 00:27:13.770 · DANIEL SIH:

Yeah. So we're giving people enough information in the right framework so that they have enough then to to pick it up from themselves and actually learn from that.

 

 

00:27:13.810 — 00:27:35.900 · PAUL MATTHEWS:

Exactly. And what to your point, what's really useful is that these are what we call tool agnostic principles. So it is not a book on how to use ChatGPT or Copilot or Grok specifically, but it will work for all of those things, and it will work for whatever comes next, I think. In the book, we call the emerging AI Quantum Puddle 9000.

 

It'll work for Quantum Puddle 9000.

 

 

00:27:36.100 — 00:27:52.740 · DANIEL SIH:

You know what? That's going to catch on. The book will be so popular that someone will actually develop Quantum particle 9000. Love it. That'll be great. That's not. That's when we know we've truly made it. Okay, so why don't you shoot with one of the broader principles? We can't go into depth with all of them, but, um.

 

Yeah. Why don't you give me one?

 

 

00:27:52.780 — 00:30:09.510 · PAUL MATTHEWS:

Well, one of the really good frameworks for using artificial intelligence. I use it all the time, and I train a lot of teachers and professionals to do it, too. It arises out of one of the core fears that we have. I remember I was working with someone recently and they said, Paul, I think AI is making me dumber.

 

Like, I actually think I'm getting less good at my job. My mental muscles are atrophying and growing weak. And so what we want to do, part of why is AI is just not getting worse. It's actually still continuing to improve and grow ourselves. And so if we want to use AI but we don't want to lose our AI, our organic intelligence.

 

Um, I use this really simple workflow. I call it the plan du review before I'm actually going to start doing my work. I have a little bit of what I learned from you is called Lean Back Time. Right? So I'm actually leaning back. I know AI is going to help me do things really quickly so I can give myself a minute just to think, and what am I asking?

 

In the plan section, I'm asking, what am I going to do here? What does good look like and how will I know when I'm done? Just really simple. I'm just priming the pump of my mind to go, this is what I'm doing and this is how I want it to go. And I'm actually articulating some good details there. And this is how I know when it will be done.

 

After that, I can lean forward. I'm firing up my laptop and I'm using AI, but I'm also using Google Search. I'm using my emails, I'm using all the tools I have available to myself. And we go through the plan, the do phase, and then lastly review. So when I'm done, I'm actually going to take another pause for thought.

 

I'm going to reflect. I'm going to think what went well, what didn't go well, and what might I do differently next time? And what I found, Daniel, and I've heard this from many people who use the same framework and cards on the table. It's actually based on one of the most popular cognitive neuroscience frameworks out there.

 

It's big in educational research. What we're actually doing is keeping ourselves in the driver's seat, right? We're not handing over our thinking. What we are handing over is some of the execution and administration, while making sure we're still thinking clearly and articulating what we want. And if you can do that plan do review cycle that will actually make sure your mental muscles are not growing weak.

 

In fact, you're going to still continue to grow and improve while having all the benefits of AI.

 

 

00:30:09.550 — 00:30:16.110 · DANIEL SIH:

It's interesting because I remember you pushed back when Microsoft named their AI copilot.

 

 

00:30:16.110 — 00:30:39.720 · PAUL MATTHEWS:

I just don't like it, Daniel, because I think as a teacher, right, there are not two steering wheels in my classroom. I'm the pilot. I am the pilot. If you were to draw an org chart of where we should be and where I should be, it's not a lateral move over to the AI, right? We're not at the same level of hierarchy, but maybe I'm the primary pilot.

 

Maybe they're the backup pilot. It's a completely different relationship.

 

 

00:30:39.760 — 00:32:27.890 · DANIEL SIH:

So. So what we're trying and I think that fits with the plan do review cycle or you know like the oh I ai oh I cycle you know it's that same. You start with your organic intelligence to think about and reflect on what you want to achieve. What does excellence look like and how do you get there. We do this in space makers very similar idea.

 

You know, do get in and kind of get the work done, use the tools to make that happen. And then yeah, go back to your organic intelligence okay. So it's the same types of ideas. But but I do agree with you when I've reflected on that actually I don't want AI to be a copilot. I'm leading my work. I'm leading my team.

 

I'm building our business, I'm directing it. It's an amazing tool that guides me and supports me and helps me do things faster. But if I start to outsource my intelligence to it and let it start to guide me in a true pilot copilot way, then. Then I think we lean away from human wisdom, because in our book, we talk a lot about how these eye watering superhuman tools are incredibly powerful and they can enable us.

 

But, um, only humans can be wise. Yeah, because wisdom isn't simply about knowledge, and it's not simply about outputs or even speed. It's about recognizing your context. It's about thinking about your emotions and the people in the room. Sometimes wisdom means that you do one thing on one day and then choose the exact opposite, the action the next day.

 

Because of the change in the weather, the context, the emotions, the time, the feelings. So wisdom is a deeply human trait. If you practice it, and therefore we need to be using our intelligence before we dive in. And that won't change wise. AI is always going to need this. Is that fair to say?

 

 

00:32:27.930 — 00:32:54.490 · PAUL MATTHEWS:

Absolutely it is. I mean, we need to make sure that we're holding the steering wheel because also, I mean, just practically you've got a certain way you like things done. You've got a certain way you want it to look. You've got a workflow that works for you. If we try and outsource all of that. Well, AI is a great tool, we often say in the book, but it's a terrible guess.

 

What's in my head? Machine. Yeah. So not only is it just not that good for our organic intelligence, if we try and outsource these things, we're just not going to get good stuff.

 

 

00:32:54.730 — 00:33:01.490 · DANIEL SIH:

Yeah, you get work stopped. That's where it works a lot. You get work sloppy if you're not doing the thinking and the reflecting between the AI cycles.

 

 

00:33:01.490 — 00:33:14.290 · PAUL MATTHEWS:

And that's the worst outcome is if we just crank up the sort of sausage machine and we just charge more and more mediocre stuff out there, that's really not what we're aiming for here. In fact, this book is almost a manifesto against that.

 

 

00:33:14.330 — 00:33:50.610 · DANIEL SIH:

Yeah, I quote from the book is the most important intelligence in the room is still human and I really like that. I would love. I would love us to look back in a decade and say, hey, we made some tough choices around our rollout of AI. Obviously, we want tough choices to guard us from some of the true poor outcomes of AI.

 

But but I would love us to say it actually enabled us to be deeply human, to slow down and to create great work, to think deeply, and to have space for the inner life, to connect with people we love, to connect with nature,

 

 

00:33:51.850 — 00:34:04.530 · DANIEL SIH:

to have the right tension between being on technology and then off technology to to keep pace and make space, as I talk about in my writings. Um, I don't know. For us, that's kind of the vision of AI. Is that is that fair to say?

 

 

00:34:04.570 — 00:34:59.220 · PAUL MATTHEWS:

Absolutely. Yeah. We are both coming from a position where we want to see people walk. What is admittedly attention. It's attention because we need to hold. You remember, Sue, that we were talking about earlier. We need to hold to some of her scepticism, her caution. But we also need to see Christine and say, actually, she had an optimistic vision and she was willing to move and change.

 

If if we can hold that tension and if we can call other people to hold that tension themselves, that just puts us in the best position to actually navigate this in a way that doesn't just chew us up and spit us out and make everything bad, but we can actually save so much time and then just press into those same things.

 

I mean, we've worked around Australia together always. People are saying, I'm grinding out my my work and what do I really want to do? I wanted time for deep work, deep thought, deep relationships and deep rest. And and that's what we can do if we navigate this wisely.

 

 

00:34:59.260 — 00:35:04.660 · DANIEL SIH:

Yeah, I love it. Look, tell us about the book as we wrap up. I mean, we are very close to launching.

 

 

00:35:04.700 — 00:35:19.270 · PAUL MATTHEWS:

And you'll be seeing a whole bunch of stuff coming out as we continue to share some of the ideas in the book. We think they're great ideas and we'll continue to share them, but it should be coming out soon. We've actually got a physical launch and there'll be some more details about that pretty soon as well.

 

 

00:35:19.550 — 00:35:32.430 · DANIEL SIH:

So if people want to stay in touch, if they want to preorder the book, if they want to find out about discounts and actually get some fantastic resources as they come out, if they want to come and actually be part of the physical book launch, we'll then go to Ys AI,

 

 

00:35:33.990 — 00:35:42.990 · DANIEL SIH:

sign up and we'll keep you in touch. We would love to introduce you as the first people to our new book. It's going to be great.

 

 

00:35:43.030 — 00:35:49.590 · PAUL MATTHEWS:

It absolutely is, and I'm glad we bought a few because I think dotcom was like $25,000 USD, so that's pretty good.

 

 

00:35:49.790 — 00:35:50.510 · DANIEL SIH:

I wasn't wise.

 

 

00:35:50.550 — 00:35:51.670 · PAUL MATTHEWS:

Not in the budget.

 

 

00:35:52.670 — 00:36:06.830 · DANIEL SIH:

But, um, look, why don't we finish? If a listener could remember just one sentence, idea or concept from this conversation to help them use powerful tools in a deeply human way? What would you share?

 

 

00:36:06.870 — 00:36:26.190 · PAUL MATTHEWS:

Well, what I'd simply say, and this is the thesis of the entire book. I'd say AI is an amazingly powerful technology. It won't make your life better by accident, but if you can use it well, if you can save time in the busy work of everyday life, you will be able to press them into deep work, deep thought, deep relationships, and deep rest.

 

 

00:36:26.230 — 00:37:09.830 · DANIEL SIH:

Yeah. And look, Paul, you came on the Spacemakers podcast. I'm so grateful that we got to write a book together. It's been an amazing journey and an amazing experience. I am very confident this will be one of the best books I've ever put out, because the I don't know the fusion between your ideas and my ideas, it just it worked.

 

So good stuff. I'm so excited. Yeah, we can't wait to get this book out into the world. But thanks for coming on The Spacemakers. Thanks for having me. And look, let's just, you know, let's really hope that we can help people use AI in a way that brings them deep joy in humanity. Yeah. Which is really what this podcast is about.

 

So thank you for listening to The Spacemakers. This bonus episode between season four and season five of The Spacemakers. And until next time, make space.