Why the world feels more complex—and why that feels hard. Why more problems are complex problems. Why organizations struggle with complexity.
A Skeptic's Guide to How Cognitive Biases and Reasoning Errors Fuel AI Hype, Social Learning, The Hidden Cost of ChatGPT is the Erosion of the Digital Commons, and more.
What is complexity? How do complex problems and opportunities differ from simple & complicated? Where do we find complexity?
An interview with Doug Belshaw about serendipity surface & AI.
We're excited to welcome Doug Belshaw to the show today. Doug is a founding member of the We Are Open Co-op which helps organizations with sensemaking and digital transformation.
Listen on Apple, Spotify, and YouTube.
Doug coined the term "serendipity surface" to describe cultivating an attitude of curiosity and increasing the chance encounters we have by putting ourselves out there. We adopted the term quite some time ago and were eager to talk with Doug about how he thinks about serendipity surfaces in the age of generative AI.
As former Head of Web Literacy at Mozilla and now currently pursuing a master's degree in systems thinking, Doug has a wealth of knowledge on topics spanning education, technology, productivity and more. In our conversation today, we'll explore concepts like productive ambiguity, cognitive ease, and rewilding your attention. Doug shares perspectives from his unique career journey as well as personal stories and projects exemplifying the creative potential of AI. We think you’ll find this a thought-provoking discussion on human-AI collaboration, lifelong learning, digital literacy, ambiguity, and the future of work. Let’s dive into our conversation with Doug Belshaw.
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Please check out all of Artificiality at www.artificiality.world.
Doug, thanks so much for joining us.
We're really excited to talk to you today.
Really pleased to be here.
Can you start off by telling us a little bit about the inspiration behind Serendipity Surface?
For those who've listened to us or read our work, you've probably come across us talking about this concept of Serendipity Surface.
And now we get to interview the man who created it.
So we're kind of excited about that.
Well, hey, it's just a term for something which I've kind of noticed in my career to date.
And actually, the funny thing is, the way that I came across your mention of it was Serendipitous.
So for whatever reason, I was searching my own name in Spotify.
I can't even remember why, probably just because I'm an egomaniac.
And it came up with a link to Doug Belshaw in your show notes.
And you mentioned Serendipity Surface.
Of course, I ego listened to your episode and found it really interesting and stuff.
And then I reached out, etc.
So it's an example of something which is unexpected, something which kind of just happened.
I used to be a history teacher back in the day, and I used to have this quotation, which has been attributed to Edison, which says, opportunity is missed because it's dressed in overalls and it looks like work.
And I used to say that to the kids, like we miss opportunities in life because it looks like hard work.
And there's loads of stuff that we could do at any given time rather than scrolling through TikTok.
We could be editing Wikipedia.
We could be messing about with AI tools.
We could be doing anything, but a lot of the time we self-soothe, we do things which don't put ourselves out there.
Now, I'm British, so I'm not like Californian, let's get out there extrovert mindset.
So it maybe becomes a little bit based on personality, a little bit based on nationality, a little bit based on your upbringing, that kind of thing.
But what I'm trying to get to when I'm talking about a serendipity surface is cultivating an attitude of curiosity, really.
There's a podcast that Laura, my collaborator, and I have been on called the Curious Advantage podcast, and that talks about curiosity in a business sense, in a personal sense and things like that.
But the particular term, serendipity surface, came back in 2016 before I was a product manager.
Now, when you're a product manager, you're thinking about the attack surface of the product that you're building.
So for those of you who don't know what that is, when you're building a product which could be attacked by hackers or people who want to kind of steal the details of your users, that kind of thing, the attack surface is something that you want to reduce.
You're trying to reduce the amount of attack surface you've got so people can't attack your product.
And I was thinking actually, a serendipity surface, it's the opposite of that.
What you're trying to do is to cultivate a large serendipity surface so that you can have those random conversations, so that you can kind of find out where things go.
Now, not all the time, because that would be exhausting, but certainly increasing a serendipity surface seems like one way to live a more curious life.
It's fantastic.
I mean, we've used it in a variety of different ways.
And every time we present it, people go, oh, yeah.
You know, it's like it's such a pleasing idea that you can have this surface of serendipity.
And we've used it and used it quite a lot in sort of this sort of a bit of just a way to sort of think about and contemplate the effect of AI.
And we started in what we now consider traditional AI, predictive AI, looking for a particular outcome, predicting a particular outcome or future.
Now it's even more sort of interesting in the world of generative AI, right?
And that this world of generative AI, where you can go prompt a model to come up with some text or an image or an audio or video.
We've talked with artists who have used generative AI to essentially create different realms of inspiration.
We had a great podcast previously with an industrial design prof who said he teaches his students to use generative AI to go find inspiration.
Because he said he always did a walk down the street and he'll see a hill and go, oh, I want to use that shape of the hill in the widget I'm designing.
But I can only stumble across so many hills as I walk around the street, but I can see uncounted number of hills in a generative AI tool.
And it was all about essentially creating serendipity for inspiration.
But then we have the opposite view, which is that people talk about AI and models converging, and especially as dominant models converge, there's a risk that we're all using the same GPT model for both in AI.
So how much serendipity is there really now?
If we're all getting the same answers that all, and everything ends with the last paragraphs, ends with in conclusion, is there really anything left?
I've been wondering and fascinated what you think of that, that duality and that challenge.
Yes, that's a really nice way of putting it in terms of, does it reduce our serendipity surfaces and limit the amount of curiosity that we could potentially have?
Someone shared, and I'll not be able to find it again quickly, but someone shared a PDF with me recently, and it was an artist who had embraced AI.
But instead of it being like, I am now going to type a prompt in and now I'm going to get an image back.
This person was using multiple AI tools, getting inspiration, going down a different avenue, feeding that into a different AI tool, seeing what was happening, and then ending up with this ghostly landscape.
And this person was saying, look, this is something I never would have ended up had I not kind of followed my curiosity, the serendipity, fed this from one model into another model.
So I do think there is a very kind of the cat sat on the mat approach to using ChatGPT that a lot of people use, which is like, please help me do this thing or create an image which illustrates this thing.
But prompt craft is now something that people get paid to do, either teach other people or learn how to create prompts themselves.
There's different AI models.
There's ones you can train on your own material, that kind of thing.
But there's a link that you put in those show notes that I referred to earlier, the original one back last year, I think it was July 2023.
And the link was to a follow up post I made on another blog I've got called Thor Trapnel.
Thor Trapnel is actually a term from a designer who mentioned this in a book that I read once.
And as soon as that person mentioned the term Thor Trapnel in that blog post or book, I can't remember what it was, I bought the domain Thor Trapnel straight away because I thought that is a term that I can do something with.
So on my Thor Trapnel blog, I linked to another blog post by a guy called Rob Miller.
And I could just quote a bit that he says, and he talks about how you benefit from serendipity.
Three stages.
Supply, how many opportunities we encounter, response, whether we notice those opportunities and how we respond to them, and then growth, whether we internalize those results of the encounters with serendipity.
So I now work from home.
I have done for the last 12 years since I started at Mozilla, and then became a consultant and kind of traveled a lot.
Previously, I was a teacher.
So you can imagine how much serendipity you have in a classroom full of teenagers or young people.
People are saying this stuff all of the time.
And unless you kind of dump that down a bit, there's a little bit too much serendipity going on sometimes.
But now, like when you're working from home, like a lot of people are, and maybe not having that kind of everyday interactions and little sparks of stuff, maybe that's just me, you have to kind of cultivate that and kind of notice when those opportunities present themselves and be curious enough to kind of internalize it a little bit.
I'm a big fan of Epictetus, the kind of pre-Socratic Greek philosopher who was an escaped slave.
He was lame.
He had a lot of things to complain about in life, but he had something called the Enturidion, which was his manual for life.
And I'll just read to you the start of Epictetus' Enturidion.
He says, obviously in the ancient Greek, which I can't read, this is the English translation, there are things which are within our power and there are things which are beyond our power.
Within our power are opinion, aim, desire, aversion, and in one word, whatever affairs are our own.
Beyond our power are body, property, reputation, office, and in one word, whatever are not properly our own affairs.
Now, there's different translations of that, but just that one paragraph completely changed my life in terms of the things that you can control and the things that you can't control.
And one of the things that we can control is what we choose to pay attention to, aka what we find curious, our serendipity, putting ourselves out there, choosing where to focus our attention.
So yeah, I kind of live my life through the lens of Epictetus' work.
Attention is something that fascinates us as instructors as well.
And there's a lot being said over the last few years about the reduction, the reduction in people's ability to pay attention.
I mean, there's good data around it now.
And, you know, I think everybody is aware of it, still feels like it's somewhat out of their control.
We have a saying that we got from a writer, Clive Thompson, right, called rewild your attention, which is essentially about having a state of mind that says I'm going to practice curiosity, and I'm going to actually build that as a skill.
And when we talk to people about that, there's an instant sort of sense that needs to be offline.
And, you know, there's definitely a good argument for having that bias to being offline because of the way that screens structure our attention.
But we do see an awful lot of really healthy, productive interactions with AI that are allowing, these large language models, allowing people to follow lines of curiosity, and obviously the image ones as well.
But that serendipity surface opens up with good and healthy use of these tools.
When we were talking before heading record, you were saying, you know, you got a slap on the wrist from the university saying, don't use it that way.
But I'm betting it was in that sort of realm of searching, something that you wouldn't have searched, exploring something that you wouldn't have explored, because you just didn't have access to it.
So, you know, you got the world's library in your living room, as it were.
How do you advise people on adopting that mindset rather than just a quick in and out, give me the answer, or do this essay for me, or whatever the sort of, not so much lazy route, but the fast route?
Yeah, it's a really interesting question.
So, there's so much I want to say about that.
The first one is that I just remembered when you were saying that, that I recorded a microcast called Rewilding Your Serendipity Surface.
I'll just put the link in the chat if you want to share in the show notes.
Because I read that from Clive Thompson, and there's another blog by CG Ella about rewilding your attention and paying attention to the small weird things.
And it's difficult, isn't it?
Because my kids spend like every kid time on YouTube shorts and TikTok and stuff.
And in some ways, well, you're kind of paying attention to small little weird things.
But there's no coherent narrative to that.
There's no kind of like you're not putting it into some kind of larger structure, anything like that.
The way that I, when I do try and influence other people around AI, mostly I just try and shut up because there's enough stuff on LinkedIn and various other places about how to use AI.
Five steps and 99% of people are missing this one weird trick.
But what I try to do is just tell stories about some of the stuff that I've been trying to do.
So, for example, I did this little weird art project where I tried to imagine, you know, lonely people and doing black and white photography of lonely people in like weird situations.
And so I tried to make those photographs, photographs and a bit of commerce, as weird as possible or as realistic as possible, but kind of as weird as possible as in like I would never be able to go back to the 1970s and go and take those photographs, you know, that kind of thing.
Another one, which usually people are really interested in is, I think I mentioned before we hit record that I am currently renting our house at the moment.
Our family are living in rented accommodation.
We decided not to buy the house that we had an offer and accepted on.
We're now going to move somewhere else in a couple of weeks time.
But this particular house we decided not to buy, we decided partly because of AI.
So if I just tell you the story of this, usually people kind of find this interesting and like a slightly more innovative use of AI.
So I live in a place which flooded.
So a little market town called Morpeth in the northeast of England and it flooded in 2008 and 2012.
And so when we decided that we might want to buy this house by the river, we knew that there were flood defenses.
So we wanted to get a flood survey done and the flood survey said, look, it's not going to flood from the river because there's enough flood defenses.
But look at all these risk potential things from flooding down from the surface water runoff.
Now, this was a very technical report and I didn't really understand it.
I didn't really want to pay a consultant a lot of money per hour to explain it to me.
So I ended up putting this into Chad GPT.
Now, there are different ways in which you can put it in Chad GPT.
You can put it in with some kind of plug-in and say, give me the answer, tell me what happened.
You know, should I buy this house or not?
But what I actually did was to get it to come up with some personas.
So I said, well, OK, I want personas about someone who's buying this house for an investment.
I want someone who's super cautious and they're like a parent.
I want someone who has lived in the area for a very long time.
I want like all these different personas.
And I want them to have a chat.
I want these personas to come up with their own position and then have a chat.
And then I want them as a group to decide whether this would be a good purchase to make.
And after all of that, they decided this was not going to be a good purchase to make because of the risk tolerance of the group.
And then I got it to explain some of the very technical language which was involved.
Now, one of the comments subsequently on the blog post said that ChatGPT got some of the maths wrong.
I think that was just someone showing off.
I think it was like 0.02% out of what it should have been.
But the whole experience for me of me prompting ChatGPT using this report over a series of about 24 hours on and off was transformative because it meant that it wasn't just a conversation between the vibes that my wife and I had.
It was based on data, but also it allowed us to play with personas of people who maybe we couldn't speak to or wouldn't be willing to speak to us just randomly about a house purchase.
So for us, it was really, really useful.
There's a couple of things in that story.
One is a great story because it brings in weather, which is my favorite subject other than AI, natural hazards, which is another favorite subject.
But that's just the way I think.
But no, one of the things that grabbed me is you spent time, 24 hours, you said.
And that's a long time in AI.
You know, that's trillions of queries to ChatGPT or whatever.
And when we use Serendipity Surface with people, there's a bit of an aha moment.
Yes, I like that idea, but I don't have time.
But this has to be done fast.
But I want to do it fast because I want to do other things.
And whether we're talking about attention, whether we're talking about time to be curious, whether we're talking about learning in schools and college, the thing that seems to be, that rides rough shot over these things that are so human that people intuitively understand and actually desire is this constant pressure of time, time, time, time, time, and saving time.
And because I've got to get on to do more things with my time.
And what would you say about that experience of taking that extra time and going, you know, a conversation that happened collectively between you, your wife and ChatGPT, what would you say to people about, to frame it as you're actually speeding things up rather than having to constantly slow things down?
Is there a way that you think about that?
Maybe drawing on your system dynamics work might, because it's like how do you constantly use your to have remind people that you actually are going faster.
You need to reframe and conceptualize it differently.
Yeah, definitely.
I mentioned before we started recording that I'm doing an MSc in systems thinking.
Actually, I realized a couple of things.
Firstly, I'm just really interested in how things work, first of all.
Secondly, in the client work that we've done through the co-op over the last few years, you often get brought in to do a thing.
And it's a very bounded thing.
And you get stuck because what you realize is that this will never change, this kind of small piece, unless the rest of the organization changes.
They need to change their processes.
They need to rethink what they're doing in the world.
They need to pivot towards being more of a product organization, whatever it is.
And so it's a very frustrating kind of situation to be in.
But seeing it with a systems lens actually works quite nicely.
And you can apply this kind of systems lens to anything in your life.
And I'm still learning.
I'm just on the first module of my MSC.
But one thing I have learned, some of it is just by experimentation.
Some of it is by drawing diagrams, which are always useful.
Is that let's say that you want to read more.
Like it's like, oh, I come across all of this stuff that I see on social networks, or I see like books that I want to read or whatever.
I just need to spend more time reading.
I need to be able to prioritize that.
One of the reasons I set up my blog, Thought Shrapnel, was to have an output.
Because if there's no, for me personally, and this might be different for other people, if there's no output to my reading, I'm never going to have a reason to have the input.
So I love writing.
That's just something that I love.
I must have written 50,000 words for my MSC so far just on my blog, because I love writing so much.
So really, reading then becomes an excuse for me to have content to write on my blog.
And everyone's different.
Some people enjoy drawing, like you need an excuse to draw.
So have more inputs and get more outputs.
And Austin Kleon talks about this quite a lot, about the creative process.
And if you're stuck, you need more inputs.
And then you get more like to get more outputs as well.
One thing I wanted to talk about earlier was two things, cognitive ease, which is a phrase, it's another phrase about like Serendipity Service that a friend of mine called Brian Mathers, who was a member of We Are Open Co-op.
And then he left a couple of years ago to do some what he calls wandering and crime, which ended up being, he's doing this some wonderful work on Northern Irish history.
And when he talks about cognitive ease, it's like the wonderful images that he draws help people understand what's going on in a particular situation.
And some of that comes from just a wing and a prayer, figuring out like what might be a good metaphor.
But a lot of it comes through the hard work and the digging through stuff.
So this afternoon, my time, we've been working with MIT, who are doing some work around digital credentials.
And they need that team needs to need some help in terms of alignment, in terms of how are they going to act with certain stakeholders to make the impact that they need.
They need alignment.
So we could have started off this project with them by just being like, right, let's get out there, let's do the branding, let's do the kind of reach out to stakeholders, whatever.
But the team alignment, actually, like you just said before, Helen, like allows you to go faster because you get the alignment and then you can go as fast as you want, rather than running a bit, stopping, checking if people are still with you, that kind of thing.
So yeah, a lot of it is that.
And then another thing I wanted to talk about earlier, but this is just an interesting conversation, was the use of AI when people are frustrated for whatever reason.
So something which has always stuck with me, ever since my daughter was about, say, one and a half, was I can remember vividly, it was bath time, and she wanted to communicate something to me, but she couldn't find the words, she didn't have the language to be able to say stuff.
Like this is why sometimes parents teach their kids simplified sound language like Makaton, right?
And she was so frustrated, like she was ready to like Hulk smash stuff because she couldn't find the right words.
I thought about, I was trying to think back to, you know, when we were moving house, we were going through all the kids' stuff, are we keeping this painting from when they were three years old, are we keeping this bit of work, whatever?
And in the end, you take some photographs and you keep some of it and whatever.
And it kind of gave me a flashback to me being really young and just being very frustrated that I couldn't draw very well or I couldn't paint very well or I couldn't color within the lines.
And I think what AI, like it's not a replacement for kids learning how to draw, but it does enable them to put forward ideas and express themselves potentially in a way that they couldn't otherwise, like prompting AI, labels kids to be taken more seriously about the cool ideas that they have, I think.
That's an interesting idea.
I mean, I use it, I'm not a kid, but I've always been frustrated by the fact that I can't draw.
And it is fun to just, it is actually just fun to lever the creative expression that you can use these tools for.
I want to go back to something that we touched on, which is a little bit going into the idea of sort of mental models.
And I was trained as a chemical engineer, so systems thinking is just how I think, just how I think.
I can't think any other way.
And I forget that that's not actually, that is something you have to learn.
If you want to understand stocks and flows, you have to learn them.
They're not intuitive.
And once you understand the math of it, it's beautiful.
You can see the world quite differently.
We've moved, we've sort of layered on complexity to our systems thinking, which is literally another layer.
And that's where the first sort of intuitions that make sense for people is being able to build a network and being able to understand a network, especially networks that are like our social networks where there's hubs and levers and a few big nodes have all of the links, if you like.
That is when I heard Serendipity Surface.
That's what I heard.
I instantly had this three-dimensional network, multi-dimensional network pop to mind that had a topography.
It had hills and valleys and bridges, places in that system where I could imagine increasing my chance of getting onto the bigger hill, if you like.
I was kind of surprised to hear that Serendipity Surface came from the idea of an attack surface, which feels a lot more sort of purely digital.
How do you find people's response to...
What are the different mental models that people bring to the idea of Serendipity Surface?
And how do you get people...
Well, how are you thinking about changing that as you learn more about system dynamics and complex systems?
Especially complex systems sort of defined by the fact that they can't be bounded, they are open.
You do need to...
Part of the art of complex problem solving is actually making a conscious decision about this is where we will bound the system and these are the conditions under which we'll keep it open.
These are the open factors that we care about the most just to make the problem tractable.
What are you finding as you talk to people about how their mental models that they bring to it?
How diverse is it?
How much does it take to sort of get them thinking in a higher dimensional way or in a more dynamic way?
I have to say, sound deputy service isn't a phrase that I bandy around a lot usually.
Like I'm much more likely to introduce it into a personal conversation than like a professional conversation.
But when you talk about mental models and metaphors and kind of the symbolism that we use without wanting to stray into politics, that is how we help people understand stuff and how we get people to do stuff that maybe they didn't really know what they wanted to do or that they felt that strongly about.
So I was working with Laura, who we mentioned earlier.
She's my kind of main partner in crime with the co-op, I would say.
And again, with that DCC project at MIT, we're trying to help people understand quite a nebulous concept of verifiable credentials.
So I've worked on open badges, digital credentials, that kind of stuff for over a decade now.
But verifiable credentials is particularly difficult because it's almost like trying to explain private and public key cryptography to people all over again, which is hard enough anyway.
So we wrote a post about kind of nesting within like Russian dolls.
The symbolism that you use depends on metaphors which have an underlying mental model.
And sometimes you can kind of like bypass having to explain a lot of what's going on by using the symbolism of things that people have previously understood.
Now, whether that's flattening the world, going back to what you said earlier about AI flattening everything, if for example, you know, in this blog post, we use the example of kind of encrypted email.
So there's a padlock with an email, like an envelope on the front of it.
Now, if we use a padlock every single time we talk about security, like we're flattening what actually that means, like we're not having a three dimensional view of what we mean when we're talking about security and that kind of stuff.
But does it do the job?
Does it kind of convey to people who just need to know, oh, right, that's secure?
Yes, it does.
So it's horses for courses in the sense of how deep do you want people to go?
Like, are they happy with the symbolism?
Are they willing to dig into the metaphors?
And do they want to go into mental models?
This is probably the time of the conversation, but I should probably say that I've been unreasonably interested in ambiguity for the last quite a long time, as I'm sure you have.
And I've actually got another blog called Ambiguities about like strategic use of ambiguity.
As part of my, again, this comes from curiosity, serendipity, surface and stuff.
Let me tell you another story.
So in the UK, we have a number of remainder bookstores.
So the kind of stores where they sell off books that they, you know, haven't been able to sell through regular retailers.
And it must have been about 2008.
And I was absolutely stuck on my thesis, maybe 2009.
And I wandered into this remainder bookstore, and there were loads of this book called Seven Types of Ambiguity by William Empson.
Now, William Empson was an English guy.
He basically got exiled to China because he was gay, and being gay in England at the time was like not the thing to do.
So he spent a lot of time being kind of exiled teaching in China, and he wrote this amazing work on literature and types of ambiguity in literature.
And this was fascinating to me.
And so much so that I ended up using ambiguity as part of the core of my thesis, like how to understand what was going on with digital literacy through the lens of ambiguity.
And so I came up with this continuum of ambiguity, which I can go into if you want.
But basically, on the one hand, we've got generative ambiguity, which is when you say something to someone else, and it makes sense to you, maybe because of your background, or Helen, you were just talking about systems dynamics there, and we share something there a little bit in common, so it might make a little bit of sense to me.
If you talk to someone else, maybe it wouldn't make sense.
But generative ambiguity is when you say something, which makes sense to you, but other people don't really get, because they don't really get the connection between the things that you're talking about.
Whereas on the other end of the spectrum, you get what Richard Rorty calls dead metaphors.
So these are cliches, things which are massively overused, so they don't mean anything anymore.
So when someone says, oh, we're going to double down on something, all the business jargon is basically dead metaphors, don't mean anything anymore.
And the sweet spot I found is what I would call productive ambiguity.
So if generative ambiguity is something which makes sense to you because of your experiences, creative ambiguity is maybe something which makes sense to people in your sector who have had similar experiences to you.
But productive ambiguity is something which you can put out there.
People can kind of put their own stamp on and kind of understand in their own way, but there's a core to it which is common to everyone's understanding.
So this is what you're looking at when you do a political campaign or you're trying to convince someone of something else.
They can take this idea, apply it to their situation, and it kind of goes viral like wildfire and stuff.
So productive ambiguity is the sweet spot that I'm trying to aim at in my life.
And everything else kind of gets put into that serendipity surface and cognitive ease and everything else, AI.
Am I right in thinking it feels like in productive ambiguity, there's still an invitation to the audience, whether that's one person or many people, to take some sort of creative journey to come to an understanding of it.
It's not so ambiguous that they don't get it.
You know, like, I don't understand what you're talking about.
But there's still some invitation that people actually need to engage to get there, like to understand.
That's right, yes.
So, I mean, you can't control what other people think about a thing.
So, for example, I think the classic example would be like a mother.
If I think about my mother, lovely and warm and generous and kind and nurturing, not everyone's mother is like that.
So if I use a mother as an example, it's not going to be understood the same way for the whole population.
The way that I usually describe productive ambiguity is if, you know, if you nailed a bit of wood to the wall, it would have one fixed point, but it will be able to rotate 360 degrees around that.
So you've got, you know, you can apply it to almost anything, but there's something fixed in the middle.
So it means something in practice, you know.
And the way that this ambiguity is generated is because when we talk and live in the world of language, we denote stuff.
So we say, you know, home, for example, our house, we say like that is a house over there, but also it connotes something as well.
So for me, if I point to that house, it's my home and there's an ambiguity in the middle of that, because for me, it means something which might not mean something for other people, that kind of thing.
So at the overlap of something which denotes something else and something which connotes something else, you get this whole realm of ambiguity.
And if you can dig into that and not think that ambiguity is necessarily something to be avoided, then you get this really rich, creative, serendipitous kind of experience in the same way that you don't get it if something is just vague.
If something is vague, then it's just unspecified and not very useful.
And I think sometimes in our cultures, in Western culture, we tend to say that something is vague and ambiguous in the same way when actually ambiguity and something being vague is quite different.
I'm actually really liking this.
Now you've given us yet another thing to think about and another phrase to use.
And what I'm attracted to is that I'm attracted to this.
What I find is the best communications that we come up with, the best product slogans that I've experienced in the past have all been something that has some ambiguity to it because it allows the audience to then apply it to their own world.
So it is ambiguous enough that they're like, oh, I know what that is to me.
I know what a thousand songs in a pocket could feel like to me, which would feel different to you because there's something there that fuels, but it is productive.
It's not so vague that you're like, I don't know what you're talking about.
I'm lost.
I'm not engaging.
There's something in that productivity zone that you described that to me says, when we're giving a workshop and we're talking about something, it's something that invites people in and then they find that connection.
They have that aha moment, but their aha moment might be different for each of them because we're dealing with something that has some level of ambiguity to it.
But I love that invitation to aha.
Yeah, and if you go a little bit further, so my thesis supervisor, so I was writing a doctoral thesis on the concept of digital literacy.
And my thesis supervisor introduced me to the word ZUGMA, so Z-E-U-G-M-A, which is an ancient Greek word, which means yoking together.
And he was saying, well, look, digital literacy is a ZUGMA.
Like, is the emphasis on digital or is the emphasis on literacy?
Is it digital literacy or is it digital literacy?
Which is an emphasis which is important to different kinds of people.
So if you're a literacy educator, you're interested in the literacy element of that and know this is like a modifier, digital to the world of literacy.
If you're interested in the internet and that kind of stuff, then you're interested in the digital world and you're interested in, oh, literate practices in my world that I'm now inhabiting.
And you can see that for the work that I'm doing now, verifiable credentials.
Is it on verifiable?
Is it on credentials?
Is it on open badges?
Is it like anything where you've worked together two things to...
It's interesting investigating which word the emphasis is or should be on.
How do you see these tools being used in higher education?
And with everything you've...
All of your experience at Mozilla and your postgraduate work, how do you think about advising universities on the best use and policies for students and faculty?
It's really difficult because sometimes you can see the stuff coming and you can talk about it and you can try and engage people in it and they're not necessarily interested.
So a really good example of that was...
You could see what was going to happen when...
So I used to be a teacher and senior leader in schools.
You could see what was going to happen when every kid had a smartphone in their pocket and a very fast data connection that they didn't have to pay very much money for.
It was obvious what was going to happen, right?
But then there's this huge moral panic.
Ten years later, after there's a group of us going, hang on a minute, shouldn't we be talking about this right now and putting some stuff in place and maybe doing something?
People aren't willing to have the conversation until something bad's happened.
And usually it's too late.
They try and bolt the door after the horse is bolted.
And that's usually the wrong answer.
Banning stuff is not the right thing to do.
So for example, before we started recording, I mentioned how I'm using AI as a postgraduate student and I really wish I'd had it as an undergraduate.
I really wish I'd had it at school and that kind of thing.
Now, most of the articles I read is like, how can we stop students using AI?
And instead of the nuanced approach, which is my background is digital literacy, helping people understand what's going on.
When I was at Mozilla, it was WebMaker.
How can we get people creating the web rather than just elegantly consuming it?
Instead of stopping people using stuff in a very, what's the word, transactional way, where it's like, I want the answer to this question.
Please do my homework for me.
I've seen such great examples of educators using AI, games, mobile technologies for all kinds of amazing purposes.
And that's the kind of conversation you have before everything goes wrong in inverted commas and you're in a situation where there's blatant plagiarism and cheating and everyone's getting 100% on their assignments or, you know, tutors and lecturers are spending all their time trying to do plagiarism detection and that kind of thing.
We have to step back and think, what are we trying to do here?
We're not trying to perpetuate the current system of higher education or the current system of school.
And what we're trying to do is have informed, literate, engaged, curious people.
And we don't get that by doubling down on making sure that they're not cheating, by taking away all the technology, putting them in an exam hall and making them write with a pen or pencil.
That's not a cool thing to do in 2024.
So, yeah, I think it's for educators, for instructors, for people who are thinking about this kind of stuff, it's engaging with these things before they can become massively mainstream.
It was very difficult to do with things like Chachi PT because it seemed to most people to come out of nowhere.
But as you know, it didn't come out of nowhere.
There's a long history of what's going on.
And although it might not have gone into people's consciousness until a couple of years ago, you couldn't have seen exactly how this was going to come, but you knew it was coming at some point.
Yeah, there's a particular challenge in education.
It's not unique to education, but I think it's the most profound in education.
And the work that we do with colleges and universities, especially at that level, there's a sort of an existential question about what it means to teach, what it means to learn.
And the way that we've measured learning is by producing something as evidence of learning.
And in some ways, I simplify, which might be an oversimplification, but I find myself simplifying down to the fact that the problem is that production has now become so much easier.
And so if you're looking for efficiency of production, I'm going to have a paper and I'm going to produce that I could actually read this book and da-da-da, then that's actually become really quite easy to do with a tool that doesn't actually prove the evidence of actually what you've, the learning journey you've been on.
Whereas what we're talking about here is using these tools to actually enhance and embrace that curious journey, that learning journey that is about curiosity and discovery, which has a level of friction to it.
And so there's this problem that these tools are being marketed as things that are so efficient, right, in the corporate world.
We're going to be able to get so much more done, 26% to 73% improvement of efficiency, and da-da-da-da, because everybody's driving to have increased earnings with fewer people.
But in the learning world, you actually need to say, we need to use these tools to make life a little bit more difficult.
Because the difficulty and the friction is how we learn.
That's the part of the process.
And so it's hard to get the right messaging around that, I find.
Yeah, I think you're absolutely right.
If we were honest as educators, what we've done is we've made assignments easier, the easiest possible way for us to be able to mark en masse.
That's what we've done.
By making them objective, having a rubric, and then grading everyone against the same rubric.
Whereas actually, we know that everyone learns best when you get personalized feedback based on applying stuff to your own life.
And that's why I'm finding this Systems Thinking course through the Open University so useful.
Because actually, yes, the assignments include some kind of reflection on what this thing means, whatever.
But most of the marks that you get for the assignments, and I'm doing one of the assignments right now, I was working on this morning, is having a situation of concern, designing a system of interest, and applying it to your own situation.
And you can't really fake that, because how could you ask an AI to do that unless you fed in all of the stuff?
Even then, it wouldn't really make sense, because you have to bring your humanity to it.
Which again, brings in the kind of embodied element of thinking and learning.
There is an embodied element to all of this, which AI will never be able to achieve.
Well, thank you so much for joining us.
This is certainly one of those podcasts where I feel like we could keep going for quite a while.
But that's a good thing.
But thank you so much for joining us.
It's a real pleasure to talk to you about all of these topics, serendipity and creativity and learning and everything else.
And we hope to keep the conversation going.
Thanks, Helen.
Thanks, Steve.
Thanks, Dave.
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