RCA Podcast: Will AI help to nurture our relationship with the natural world, or erode it?

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In this episode of the RCA Podcast, RCA President and Vice-Chancellor Christoph Lindner is joined by two leading voices working at the intersection of art and design, living systems and future technology.

• Dr Danielle Barrios O’Neill, Associate Dean (Academic Planning & Development), Schools of Communication and Design. Her research explores complex living systems, technology, and the use of advanced play and speculative design to help humans engage with and reshape ‘wicked problems’, like climate change.
  
• Dr Julie Freeman, Founder of art and design studios Translating Nature and ShapedSound. Julie’s work has seen her turn raw data from living systems, like fish or mole rats, into physical and sonic artworks. Her most recent work, Models of Care, uses data from Arctic glaciers to explore environmental responsibility and the relationship between artificial intelligence, climate change, and human agency.

Together, they discuss the complex potential of AI, including:

• Whether our own 'humanness' is the primary block to a better connection with AI.
• The use of data as an art material, including in Julie's RAT Systems project, which translated data collected from a colony of naked mole rats into animation and sculptural works.
• The ethics of our relationship with AI, and how we might think about being more responsible in our use of AI.
• The environmental impact of AI data processing and the technology’s potential to help solve the climate emergency.

Recorded on 4 November 2025

00:00:00:00 - 00:00:18:12

If we were to free AI, what would that look like? And what are the ethics of our relationship with AI? What's the social contract when it comes to other intelligences?

00:00:18:14 - 00:00:36:24

What comes out of AI systems is these unpredictable, complex behaviors. And for me, that's what got me hooked on using technology in my art. In fact, this kind of idea that there's life in the machine that can be created by rules. And I was like, how can we match the life in the machine with the life in the real world?

00:00:37:02 - 00:00:50:03

And for me, that - that's where the intelligence is.

00:00:50:05 - 00:01:19:03

Will AI help to nurture our relationship with the natural world, or will it erode it? Artificial Intelligence has been a huge topic of conversation in recent years and it's impacting us daily. But today we're discussing a particular incredible opportunity that I may be presenting a chance to use this powerful technology to truly partner with nature, not just to observe it.

00:01:19:05 - 00:01:40:21

My name is Professor Christoph Lindner, and I'm the president and vice chancellor of the Royal College of Art. And we're recording today in the very urban setting of our London Kensington Campus. But we're right next to the lush and leafy Hyde Park. And it begs the question, if all the natural life in that park could speak, what story would it tell?

00:01:40:23 - 00:02:18:23

I'm thrilled to be joined by two guests today who, through their research and art and design practices, considered data as an art material and explore how we can better connect with the natural world through AI.

Dr Danielle Barrios-O'Neill is associate Dean (Academic Planning and Development) of the RCA's School of Communication and Design. Her research explores complex living systems, technology and the use of advanced play and speculative design to help humans engage with and reshape wicked problems like climate change.

00:02:19:00 - 00:02:49:22

Her new book, Systems Play, develops a novel theory and approach to engaging humans with complexity and multispecies resilience. We are also joined by Dr Julie Freeman. Julie is an artist, a researcher and a curator who works with natural living systems and emergent technology. She is a Ted fellow, co-founder of Fine Ax and runs Translating Nature, a digital and data art studio.

00:02:49:24 - 00:03:21:07

Julie's work has seen her turn raw data from living systems like fish or mole rats into physical and sonic artworks. Her most recent work Models of Care, uses data from Arctic glaciers to explore environmental responsibility and the relationship between artificial intelligence, climate change and human agency. Welcome, Danielle and Julie. So let's start with the big question driving today's discussion, and I'll ask the whole big question.

00:03:21:07 - 00:03:43:06

But of course, we're going to have to unpack it and think it through. But the big question is, will AI help to nurture our relationship with the natural world? Or will I erode that relationship? Danielle, what do you think? That's great. Thanks for the for the lovely introduction. And it's it's lovely to be here with you both.

00:03:43:08 - 00:04:08:22

So from my point of view, I think that it could it could deepen our connection with the natural world. And much depends on how we how we go about developing our relationship with AI. And I think one of the reasons why Julie's work is so interesting to me is because it is, is they're kind of teaching us a new way of relating to to AI.

00:04:08:22 - 00:04:24:02

So, so my view is if we have more and more work like this, then absolutely. Our relationship with with nature will change because of our relationship with AI. Yeah I think thanks, Danielle. And yeah, thanks for inviting me to be here. I love a podcast. I think it's going to be both, isn't it? It's going to be both.

00:04:24:02 - 00:04:46:07

I think the problems, there are so many problems with AI systems. Their extractive nature is obviously damaging to the natural world. That's that's the problem. And then the flip side, the ability of AI to detect patterns and to be able to communicate with nature and living systems on a more on a, on a level that is deeper than our own human sensory perception.

00:04:46:07 - 00:05:05:17

You know, the the way that we use technology and sensors to reach further into the world, to explore things that we couldn't detect otherwise. That's fascinating to me. And that is how, you know, a lot of my work does do that, but that is how we understand, begin to understand the world in different ways that are sometimes from a non-human lens.

00:05:05:18 - 00:05:32:15

So thinking about how the machine views nature is something that is very interesting. I mean, AI is used in this catchall way, which is is not always useful. There are so many different types of algorithms, and a lot of them are nature based algorithms that are actually mimic in nature. So using those to explore real sort of natural systems that we've tried to understand by data collection is something that is really intriguing.

00:05:32:15 - 00:05:59:04

And, you know, all of all of the work in that area is exciting. You know, the the it's difficult to understand how if we're using AI to try and understand dolphins, how are we going to strip away the human way of thinking about that? How are we going to do that? You know, is I going to be able to be non-human enough to give us some feedback about what a dolphin’s communication system might be like?

00:05:59:06 - 00:06:26:20

So hang on a second. This is fascinating, but I'm already confused. So if I if I hear what you're saying correctly, part of what you're suggesting is that in order for humans to potentially have a closer relationship with the natural world through AI, we need the kind of dehumanizing or non-human aspects of AI to foster that relationship. In other words, our humanness is maybe one of the blocks to our relationship with the natural world.

00:06:26:22 - 00:06:51:03

Yeah. Yeah. I think the thing that is what I'm saying, and I think and I don't know, I don't know if that's ever going to be something we could ever solve because we can never not think as we think. Yeah, that's really fascinating because I think there's definitely a popular perception of AI being one of these ultimate machine, dehumanized, abstract, non-material people.

00:06:51:03 - 00:07:18:11

Just think of it as a floating digital entity that just hovers around all aspects of our life. And what you're actually suggesting is that particularly if we take a kind of biomimicry approach to the way that we we are programing AI and creating data sets with AI, that I could be something that is much more tangibly entwined, in our lives and in the realities of the natural world.

00:07:18:15 - 00:07:39:09

Yeah, there could be some alignment that we, that we haven't thought about that does come out of some of these systems or some of these algorithms. I essentially can't really do anything without the data that we feed it. So there's already a human input into it because we're choosing which data to create to feed the system. Can I come in on that?

00:07:39:15 - 00:08:00:16

So the vast majority of the data that that AI that most people think of when they think about AI right now, so it's essentially ChatGPT versions or Midjourney kind of image based or text based. All of that is either determined by human language, or at least that's the the majority of the input that's going in on one end.

00:08:00:18 - 00:08:21:07

Or by images from the perspective of humans. So that is a, that is this thing which is at the moment incredibly, interesting and fascinating to us. And it makes it user friendly as well. There are versions of AI that that will be less user friendly and potentially less controllable that I find really interesting because they do get away from what we can understand.

00:08:21:07 - 00:08:47:05

So when when two AI agents are talking to each other and we don't understand that, there's something slightly that freaks us out a little bit about that, but it's brilliant. And that like, something about that is quite interesting to me too. Yeah. I mean, I often refer to the work that I build as systems or frameworks because they're, they're these frameworks that are created that I think are interest in the AI set, the parameters, and I will decide on a certain amount.

00:08:47:07 - 00:09:16:07

And then I'll often try and use real time data from living systems or predictive data from from AI outputs or, you know, historical data and merge them together so that they then play around in this framework I've created, and then they ultimately create the work. So one of the things I like about using living systems is that you can switch on this model and then the data from whatever is feeding it then creates the artwork.

00:09:16:09 - 00:09:39:00

And although it's not a direct two way communication between the natural world and us, it is a form of communication, opening up to allow them to express themselves in, within my parameters. So that's about the essence, I guess, of the data that's flowing through. And I think there's ways of using AI that could probably do that as well.

00:09:39:06 - 00:10:06:10

So can I just ask what is data? In this conversation is data in the age of AI in particularly when we're drawing data from nature to then translate through AI into creative expression of artworks. Is that the same thing as digital data that we might use in, like ChatGPT in a large language model? So funny I should mention that my PhD is called data as an art material, and within it there's a taxonomy of data and how we should describe data when we're using it as an art material.

00:10:06:16 - 00:10:30:21

And so it talks about the different types of data. It could do with updating in the age of AI, but it basically says there's all different types of data that we're using. And then you can, you know, the more granular we are about it, the more we begin to understand what we're doing. So is it data that is time based from, say, an animal moving through the physical location or is it, data from from human factors?

00:10:30:21 - 00:10:50:12

Is it economic data? I don't know the different information, I guess, within that data. But to me, I feel like as much as there's a lot of AI talk, I still keep referring to data a lot because data is the thing that makes up these. The systems around us, which is human to human machine to human, machine to machine.

00:10:50:12 - 00:11:11:06

It's in there all that. We can't get away from it. So I feel like understanding data helps us understand, I, I would define data as, signals in a way. And that really sits alongside what you were, the way that you were kind of framing and moment ago, and that it is the thing that connects us to each other and whatever we decide as data is data.

00:11:11:06 - 00:11:49:21

So whatever we can recognize as data, we recognize this as information. Therefore it becomes information becomes data. There's something about the way that you like. The taxonomy is it's fascinating because it's like, it reminds us that many signals are organic or warm, like warm data versus kind of cold data points. Right. And some of the way that you've talked about your work in, in various places has kind of been around the way that we care for the data, the way that we care for the kind of what we traditionally think of is like the subject or something becomes a part of this, kind of living relationship where care matters, which I think is

00:11:49:21 - 00:12:21:24

really fascinating as a, as a way of thinking about our relationship and in creating, I guess. Yeah, that makes sense. Although it leaves me with another question. When does data become art, or when does data become creativity? Or is creativity already contained within data? So it's quite a philosophical question. I would say that one of the things I really love about data is this, that it can be reframed in so many different ways and that it's it's actually malleable.

00:12:22:01 - 00:12:40:00

And if you if you conceive it as an art material, then suddenly it's a thing that you can play with. You can stretch, you can shift, you can use to add dynamics to a system. You can use it to visualize something. You can, you know, you can use it in so many different ways, and you can keep the essence of the data.

00:12:40:00 - 00:13:10:03

But you don't necessarily have to be really strict about the representation of that data. So when you talked about the reason my practice is called translating nature, this idea of translating is a really personal thing. So like historically with books, some authors always used the same translators, and those translators were able to bring their own creativity to those writings that the original authors like respected.

00:13:10:05 - 00:13:32:24

And it's a very personal thing. So you get multiple translations of the same book and they'll all read slightly differently. And so that's why that word is important to me, because it allows that flexibility. And it sort of says that it's it's from my perspective as an artist, I'm taking the data. I'm doing this thing with it. It doesn't mean if you had the same data, you would maybe come up with something else.

00:13:33:01 - 00:13:56:16

And I think in in statistics and economics, there's this idea that data is very objective and it's kind of the truth. And if everyone has the same set of data though, but there's so many different statistical models, there's so many ways to manipulate it that that's not a very helpful thing. And I really like the idea of data as an art to exploding the myth of data being the truth about the world around us.

00:13:56:16 - 00:14:37:12

And that's that's a really beautiful phrase, data as an art material. And when you talk about it in that way, I start to see and understand, how you can, begin with data and through interpretation, through translation, through engagement. Then, create different forms of expression or materialization or whatever, whatever you want to call it. But then it makes me wonder a little bit about how if we bring AI in, which has a way of, organizing data and analyzing data, presenting data, how can we use AI to co-design better with the natural world?

00:14:37:14 - 00:15:00:15

I did an experiment recently with a piece of work called Models of Care, and we wanted to explore the responsible use of AI as a and using it for sort of in creative ways. And so my approach is to think about low resource models, which are, AI models that use very minimal amount of resources. So they don't need a lot of cloud computing.

00:15:00:15 - 00:15:26:18

They just they need to they take a small amount of data and then they do some training, which is how the AI models generally, sort of get their background and work out how to then process another set of data or come up with something generative. And we used it. And one of the interesting things is that I put in 11 hours of recordings of glacial, field recordings.

00:15:26:18 - 00:15:57:00

So like melting glaciers. And in that 11 hours, there's some amazingly beautiful moments where the ice is cracking and shifting, and then there's these really low frequency, resonant moments of grumbling and rumbling. It's really evocative. And I was like, I can't wait to see what this little low resource model does with it, because it's going to be interesting to see that it picks up certain patterns, and no matter how we manipulated it, it came up with the thing that was just what is the sort of median of the data?

00:15:57:00 - 00:16:22:15

Which of these low rumbles. And so all it was doing was just rumbling continually. There was no motifs, there was no moments, there was nothing like that. We would say is interesting about that soundscape, because it essentially stripped out all the outliers and left us with something that was really very mundane. What's interesting to me was really far away from the output of these models.

00:16:22:17 - 00:16:53:22

It reveals, in a way, what is, what is very important about the organic living, in this case, the human ear. But it in, in sort of what you think is interesting, but it's also, it kind of raises this sort of series of questions, I guess, about what is salient. To go back to the idea of like, signals and information and data and what counts, that is it is a big thing deciding what is salient and why.

00:16:53:22 - 00:17:21:00

And it is different for different species. Right? So when when you were speaking about, perspectives and, and sort of taking different perspectives, I think that the, the way that we process information completely forms our, our sort of life world as a, as a, as an organic being. Right. And so I'm, I'm a human system. I'm like a sort of human being, my little sort of organic system.

00:17:21:02 - 00:17:58:14

And all of my senses, they, they're, they're organized in a particular way to give me the kind of information that I need in order to essentially reproduce successfully. That is kind of my, my, you know, genetic imperative. And so to think about it that way, everything coming into my sensory apparatus and forming my world view, my or my sort of life world that is totally limited to this tiny little fraction of of what there is, because that all is about just what I need to know to kind of reproduce successfully in on this particular planet.

00:17:58:16 - 00:18:20:01

So there is so that is one like the fact that that we think of the world and we think we're talking about the same thing actually. It's like, you know, a tiny, tiny fraction of what's there. So every time you sort of shift perspectives, like with your RAT project, which I love, it's the more it's just gorgeous because it takes this animal, which is not that charismatic in a way.

00:18:20:03 - 00:18:39:12

To me. I mean, it depends who you talk to. Rats have a bad image. They do. I mean, they're so clever, but but it's the it's the it's not one of the big charismatic megafauna animals that do all the heavy lifting for like the, you know, for, for animal charities. It's this kind of overlooked perspective.

00:18:39:16 - 00:18:59:24

So we desperately need to hear more about the more wrapped project to what can you tell us? So RAT Systems is yeah, project with a colony of naked mole rats. They were my collaborators for about five years. I worked with Doctor Chris Fawkes, who's like one of the world leading naked mole rat keepers. And I needed a live feed of real time data.

00:18:59:24 - 00:19:31:09

And he needed, for his research. Some, tracking of his mole rats. So part of my PhD was to track. I set up a system so that we could track the mole rats 24 hours a day. And because they live in darkness and above 30°C, they're not tracked. I haven't been tracked like that before in captivity. And so we've got four years, this huge dataset of naked mole rat activity, and we we discovered some really, unusual behaviors that they didn't know about before in the sort of mole rat world.

00:19:31:11 - 00:19:55:09

And I use that data in loads of different ways to make soft robotic sculptures that moved with sort of had like a dance like movement to make a visualization, to make, a soundscape and abstract animation and then also a series of portraits. But the thing with the mole rats, they are, they're really unusual animals. And they, they're not actually rats or moles.

00:19:55:09 - 00:20:18:05

There's something else closely related, weirdly, to the armadillo thing. But they have loads of amazing attributes that humans would want. So they I mean, I can talk for a long time about naked mole rats, but they have properties like they can survive for 18 minutes without oxygen. They can live - even though there are tiny animals of like the width of the palm of your hand -

00:20:18:07 - 00:20:44:02

they can last for over 32 years, which is phenomenal. And they have because they have these anti-aging genes, they're resistant to cancer. So funnily enough, they're a really hot topic at the moment for Longevity Labs to be studying, because humans obviously have got this obsession with living forever, and the naked mole rat have got loads of genetic attributes that we would potentially want.

00:20:44:04 - 00:21:09:15

The aim of RAT systems is to use this real time data in multiple different ways, and to talk about the data, using the taxonomy in different ways. So is it real time? Is it being analyzed? Is it kind of, historical data? Has it been time stretched? I used all these different techniques in a series of different artworks to explore and really to promote this idea that a data is an art material would be the same.

00:21:09:15 - 00:21:36:00

Data can be used in loads of different ways, and still be effective in triggering some kind of experience. How did you decide to focus on mole rats? It was an accidental moment. So the biology lab and the computer science lab at Queen Mary University share a tearoom. And I was in the tea room, and, I used to do taxidermy as a hobby, and I was looking for a freeze dryer.

00:21:36:00 - 00:21:54:05

And I said to this guy, if you've got a freeze dryer in your biology department, and he said, what do you want that for? Thinking it was like cellular level. And I said, oh, I've got some small critters in my freezer at home. And he went, I've got small critters in my freezer. And we had this amazing moment.

00:21:54:07 - 00:22:12:08

Two people at the whole university both have critters in their freezers. And then it turns out that his were naked mole rats, and mine were actual moles. It was such a lovely moment. We were laughing so much. And then we started collaborating and it sprung from there. It was literally that - the joy of critters essentially was what brought us together. Fantastic.

00:22:12:08 - 00:22:37:11

So I love hearing that word joy as part of our conversation. And what I'm hearing a lot of is that, working with data and using data as an art material, can be supremely creative, but also poetic and and, exciting and, challenging. But it makes me think of a question that I keep being asked.

00:22:37:11 - 00:23:09:15

And I'm sure you are also being asked all the time in recent years, which has to do with the relationship between AI and creativity. And the question I keep getting asked is, isn't AI going to end human creativity and hearing about both of your works and, the kind of language that you're using to talk about AI in the natural world makes me feel that you would have a completely different answer to that question.

00:23:09:17 - 00:23:40:24

That AI is not the end of human creativity, but maybe the beginning of something quite different. I've come into contact with this stuff art that is, interested in AI that's using AI through my AI led a program called Information Experience Design for for about five years at the at the RCA. And so during the last three years, there's this constant kind of, updating of what we feel is possible, what looks like it might be possible soon.

00:23:41:01 - 00:24:05:13

How where where what what the status of human creativity is in that it's just constantly changing every time the capacity of AI to do something new, that we didn't realize it could do, that's happening really, really fast. And so what we believe our role is in relation to that is also changing really fast. So what artists are making is also changing really fast.

00:24:05:15 - 00:24:37:08

So that in itself is fascinating to me. There's a faster pace. There's there's a there's a more rapid pace of change in what the artists and designers that I've been working with are interested in. Then prior to the sort of AI, the really user friendly AI era that we're in now. So in one sense, that suggests to me that it's going to lead to a kind of, like a real flourishing of, of creativity like that.

00:24:37:08 - 00:24:56:14

This will be a really incredible kind of creative age that we're about to come into, because there's just so much change. And a lot of people would, would are worried about things that are really valid around kind of the practicalities. So things like IP and how you sort of maintain control of your work in these kinds of things.

00:24:56:16 - 00:25:18:14

From an optimistic kind of point of view, I feel like, we can get over the idea of ownership to the extent that that maybe at some point in the future, maybe ten years, maybe 20 years or 50 artists will be valued in a way that we won't need hopefully to for everyone to get paid for every usage because we're all fine.

00:25:18:14 - 00:25:47:11

You know, universal basic income is going to come out of the AI revolution, maybe, but that's my optimistic side talking and all of that is really positive for for creatives is my is my view. In the long term, I think in the short term it can be quite, I think it can feel disempowering to see in the, in the initial experimentation, phase, people working with AI, because I think that the first thing that happens, you go, oh my God, that's really good

00:25:47:11 - 00:26:16:00

what it just did. And then it takes a while to realize, where the limitations are, like with anything. And I think some of the, the most interesting work is the stuff that gets away from just getting AI to do what we can do, just to do it kind of slightly faster. I'm moving beyond that to doing things that we can't do, and increasingly that might mean freeing AI to do what it kind of will do.

00:26:16:02 - 00:26:31:19

What it wants to do, in a way. I mean, I don't want to talk about sort of agency in that way, but I think that's that's quite reductive. But but it is a if we were to free AI, what would that look like? And what are the ethics of our relationship with AI? What's the social contract when it comes to other intelligences?

00:26:31:19 - 00:26:52:17

So as soon as you said that, I got nervous, but I don't know if that's because I don't have a sophisticated enough relationship with AI or understanding of AI, or whether we should be nervous about what it means to let AI free, to let it do what it wants to do. You know, ascribing those kinds of motivations to AI.

00:26:52:19 - 00:27:20:24

We all seem to be worried. I mean, that that is standard, right? That is the standard human nature kind of worry is it's an existential risk. Right. And that's in the headlines and that's the response. And I think that that's totally valid and important for us to be thinking about. But at the same time, we're there's almost an assumption that what any, what any other intelligence will want will be to take over and get rid of us or something like this.

00:27:21:01 - 00:27:47:15

When in fact, what most intelligence systems seem to want to do is just thrive and explore new areas. And there's what we describe as curiosity. Maybe it's just kind of moving into new spaces and doing different things. So I'm not sure. I mean, maybe, maybe you have a very different answer. I think the, the, the idea, the intelligence bit of the AI acronym is so problematic.

00:27:47:15 - 00:28:13:01

It doesn't have that intelligence. It doesn't have that intention. Yeah, literally. And I think there's a lot of hyperbole around this idea that there's going to be an AI that's going to seek there's going to have consciousness and stuff. I, I just feel like it's very investor friendly, those kind of yeah, that kind of rhetoric. But it you know, I think you're right in what you're saying about back to the creativity bit.

00:28:13:03 - 00:28:39:21

I think what you probably mean by ‘setting AI free’ is kind of getting out of the shackles of expectation of what we think I should be and is at the moment. And for me, it falls into like, there's these categories of, of spectacle where it's very like, wow. And it's very, you know, there's a, there's a sort of a lot of technology there and it's pushing processing power and they're making these amazing kind of wallpaper adjacent maybe works that are very spectacular.

00:28:39:21 - 00:29:07:12

And that's one. And then there's people that an artist are using behind the scenes AI in a slightly different way. So it's kind of aiding using it maybe as a tool to aid something that the human intention that they couldn't make potentially. But it's allowing them to make something that the eyes it's not necessarily evident in the final work, or there's a very critical approach where people are making work that is critical of AI and looking at the ethics and the morals.

00:29:07:14 - 00:29:23:21

And then the other conversation is the copyright one. But I think they're different. I think they are all different conversations that we're having. And because it's so new and so exciting, like any new technology, everyone's kind of like, well, using it, what should I be doing with it? And that's, that's it's an interesting space to be in.

00:29:23:21 - 00:29:50:15

And it's not dissimilar to the space where the internet came along. And art is like, how are you going to use internet? And if you look at the net art movement or media arts, and there's been artist working with AI for over two decades. So it's not sort of brand new. It's just this, ability of the speed of technology essentially to allow us to do things that's really made it, become massive and also things like that.

00:29:50:16 - 00:30:17:20

You know, the NFT boom, which put all of those visual artworks in everybody's eyeline and generative AI particularly. But there's so much more to the world of AI creativity than those things. Can I come back to something that you were saying earlier? Because this was actually a question I wrote down that I wanted to ask you is to come back to the idea of intelligence and what it is.

00:30:17:22 - 00:30:33:07

And I was like, this won't be fair to ask you on the spot what ‘how do you define intelligence?’ but actually, I do want to know, like, how do you especially with the work that you do, how do you define intelligence? Yeah, I mean, my my answer to this is probably not going to align with lots of other people's.

00:30:33:07 - 00:30:57:10

But I because I work so much of natural systems and because I've used a lot of, nature based algorithms or like generative algorithms in my work, which are normally called artificial life rather than an artificial intelligence. And there used to be two camps of researchers, AI versus AL, when I was first learning to program like nearly 30 years ago.

00:30:57:12 - 00:31:23:02

And I - the Artificial Life program is one of the first things that I learn. And it's simple rule based systems doesn't need any data, and it's based on sort of cellular like either cellular replication or like fractal rules or something like that. Lots of the patterns we find in nature, can be computationally created using artificial life algorithms, and you can write a bit of code and then you can see it just flourish.

00:31:23:02 - 00:31:46:22

And it's like this amazing, generative, unpredictable, complex behaviors. And it's really interesting. And for me, that's what got me hooked on using technology in my art. In fact, this kind of idea that there's life in the machine that can be created by rules. And I was like, how can we match the life in in the machine with the life in the real world?

00:31:47:00 - 00:32:16:08

And for me, that that's where the intelligence is. Those things that are emergent behaviors, those things that kind of become as we became into the world, that's where there's some intelligence rather than the top down idea. The more data you give it, the cleverer it will be. That for me isn't as intelligent. So I'm kind of interested in the words that we're using here and the power or the weight of some of those words.

00:32:16:08 - 00:32:55:00

So ‘life versus intelligence’. But we haven't talked about the word ‘artificial’ and listening to the conversation increasingly, I'm wondering, is that a problematic word? So, you know, artificial sort of means fake, you know, deliberately created, passing off as something else. Is it unfair to talk about AI with the descriptor of artificial? And it reminds me of some of these really powerful tech terms that have been coined over the years.

00:32:55:02 - 00:33:14:10

So I think one of the great examples is the phenomenon of the smart city. So to call a city smart, what we mean is kind of, you know, a tech enabled data enabled city. But to use the word smart was such a clever rhetorical play, because who's going to come out and say I'm in favor of dumb cities?

00:33:14:12 - 00:33:44:05

And so artificial intelligence, it kind of sets up this huge space and this emerging area of just thought and interaction and, and, and computation, whatever you want to call it. But with this, this word that kind of undermines it or restrains it from the beginning. It is interesting and I think by saying smart cities, you're inferring that they're dumb without smartness and with artificial intelligence.

00:33:44:05 - 00:34:06:09

I mean, it really, it just makes me think of, Black Mirror. The programme Black Mirror, because mirror what if it had been called instead of artificial intelligence? It was called mirrored thinking, or it had a different phrase, and then how would we absorb that into society if it wasn't that? But the artificial bit, I think, is purposely at arm's length, isn't it?

00:34:06:09 - 00:34:35:02

Yeah. It's keep it's keeping it over there. It's kind of it's not real intelligence. And yet I'm sure there will be people that would say that that is intelligence in these systems. Well it follows some of the some like the mirrored intelligence as a I like that phrase much more because it it kind of indicates how it follows very similar, kind of dynamics to what we might think of as like organic intelligence or something.

00:34:35:04 - 00:35:05:09

But where it gets sticky, I think, is we also have like synthetic intelligence. So if you were to think about, for example, the kind of intelligence system that might arise between me and, a glacier, if we can communicate with each other somehow, if we can interact in some way. That is synthetic in the sense that it's, it's kind of connecting to previously unconnected, sort of systems to each other.

00:35:05:09 - 00:35:35:14

Yeah. But also what happens with AI and also AI is a synthetic intelligence and kind of so or we like, depending on how you want it, where you want to draw your, your lines. So I'm not sure where like if I, I'm not sure where those boundaries are really. You know, we've already used the phrase responsible use of AI and I you know, there's a lot of debate at the moment about the energy use of AI, and the environmental impact of that.

00:35:35:14 - 00:36:08:22

So on one level, we can use AI to engage with the natural world, co-design, co-create with the natural world, maybe deepen our relationship or understanding of the natural world. But the technical physical reality of doing that means, you know, using energy. And that energy use seems to be growing astronomically across the world. So how do we reconcile the carbon footprint of AI with our desire to potentially use AI to have a closer, better relationship with nature?

00:36:08:24 - 00:36:41:00

I find this in massive contradiction that's going on at the moment really difficult to to swallow. I mean, the fact that we've been, you know, for decades decarbonizing things - electric - you know, the electrification things. We're in a biomaterial revolution, everything. You know, we're trying to deplasticise things. Everything we're aiming to do for the climate emergency is just being completely overshadowed by the amount of resources that these AI, the data processing centers are needing.

00:36:41:02 - 00:37:05:11

I, I'm I'm finding it. Yeah. I'm finding it really difficult to make that okay. And I haven't found any good arguments that would say it's worth us destroying the planet because we're going to maybe find a solution to not destroying the planet. You know, I'm, I'm not sure I haven't got my head around it, but all I know is, is this massive contradiction, and it's really uncomfortable for me.

00:37:05:13 - 00:37:28:06

And the responsibility of how we use AI, whether it's for, getting closer to nature or whatever else is for me, there should be this idea, maybe, of thinking, what is our priority here? Like in models of care, in the health care system, where the patient outcome is the priority and then everything else and logistics economics is behind that.

00:37:28:08 - 00:38:04:09

Maybe the planet should be the main thing. That's our priority and then everything else is off. So before I search on GPT or I make ten zillion versions of this generative video, should I be asking, do I need to be doing it this way with these techniques? Is that the best way forward for the planet? Or you know, I know that's putting it on the individual, but I do think somehow the responsibility of using AI needs to be highlighted. To go back to the artificial thing that we were talking about, sort of the word artificial that is the basis of the word art.

00:38:04:09 - 00:38:23:12

Right. And so and like creating and creativity. And so there is this thing where you cannot create something, you cannot be an artist without putting something out into the world, which is not just there in your world, it's in everybody's world, and everybody's got to cope with it. And so every time you make something that is the case, we don't always know this.

00:38:23:13 - 00:38:40:17

And I'm like, well, let's deal with that as well. It is I mean but but yeah, it's it's true though right? I mean, there is this sort of part of us that wants to create and wants to make and take it to an extreme that, you know, can go all sorts of terrible places, but also lots of wonderful places.

00:38:40:17 - 00:39:08:22

And so it's very difficult to know. But we're straying into, into the territory of, you know, of, of choices we make so responsible AI, ethical AI, it's about asking, you know, under what conditions, how and why do we use this technology? And it might be the environmental impact. It might be the social, psychological, emotional impact. It might be the effect on governance or politics.

00:39:08:24 - 00:39:42:07

There are various lenses we can apply to think about ethical uses of AI. But if we were to, flip that a little bit, instead of me asking you what's the right way and the good way to use AI, if you could think a little bit about recommendations that you could make to governments, to regulators, to the tech companies, what are some of the things that you think we need to start putting in place out there in the world to help our use of AI, achieve the goals that we might want it to achieve, such as saving the planet.

00:39:42:09 - 00:40:09:04

Well, one thing that I would say is I think transparency is hugely important. So the companies that are currently holding kind of most of the cards when it comes to AI, like it's a few kind of, entities really. There is there's two levels of, of kind of, opacity, I guess for the average person for the first level is just what is going on in those companies.

00:40:09:06 - 00:40:29:22

And then within that there's like the black box of what's actually happening in AI itself. It's the idea that we don't really know how I works. We have a sense of it, but we don't really know exactly what's going on there. So there's that part. And then there's the fact that what could be known, there are a lot of proprietary kind of, guardrails around that.

00:40:29:24 - 00:40:49:02

And so I think that would be the first thing I would say is that that I should be a publicly owned, thing that everybody should have access to everything there is to know about AI so that more people can be contributing and testing. And now that does open up floodgates for for usage as well. In some different ways.

00:40:49:02 - 00:41:21:14

It would be challenging. But for me transparency is the first kind of big step. Yeah. And and really important as well. I think there are a few things like, you know, high quality data for training AI. So rather than just grabbing all in everything smaller, high quality data using smaller models that are really finely tuned and adapted to the task in hand rather than this, at the moment there's a lot of, I want to know how to write a sentence to get me out of a parking ticket.

00:41:21:14 - 00:41:49:21

Let's search the entire English language to do that. Do I need to do that? So some barriers may be to be in place education like you saying, and transparency go hand in hand. And then I think there are, you know, optimistically things like quantum technology, things like these, amazing new chip technologies that do a lot more processing, but output less heat and then therefore use less energy and require less water.

00:41:49:23 - 00:42:09:02

Some of those sort of future hardware development. Yes, but it is it is about being a bit more restrictive. So a lot of the organizations that allow us to use a certain AI tools that are out there get everybody kind of hooked and engaged, so they want to use it, and then it's integrated into nearly everything we're doing online.

00:42:09:04 - 00:42:34:17

And that was a deliberate technique. It can't stay like that forever. So I think eventually there will be some barriers, probably financial barriers, I don't know to to we can't always access everything we want which might reduce the the more frivolous use of it. Yeah. Financial barriers and also energy barriers. Yeah. We might hit the threshold of those sooner than than we think.

00:42:34:19 - 00:42:53:22

There's people new. I mean, if, if, if there was something that said, yeah, you can, you can send that query in or you can generate that video, this is the this is the resource it's using would be, you know, it would be interesting. I don't think that would be super difficult thing to do. Yeah. Little carbon calculator that can just help you.

00:42:53:22 - 00:43:17:12

Or you could start with the carbon credit. In lots of aspects of life, including your use of the internet and I, yeah. Can I comment on that though? I mean, so that that is an interesting thing that you've just said because we - I love the idea of having a kind of, some way of showing us, what the cost is of like one search or something.

00:43:17:14 - 00:43:42:09

But I must have read or heard recently that the way that we think about that or talk about that, the people who are often having these conversations are, are feeling guilty about using it actually, the amount of, damage that's being done in terms of like if we were to, to count in terms of carbon, like the amount of damage that's being done is much less than you do by driving your car or like it's it's.

00:43:42:14 - 00:44:00:12

So if we think about it that way, it's a different scale of problem on an individual level than it is on a kind of grand scale. So it's it's huge at the moment, but not compared to some other things that we do. So maybe this is a way for us to kind of rethink a lot of our behavior.

00:44:00:12 - 00:44:30:08

So it's kind of thinking along the same lines as you. It makes me wonder whether we should be contemplating a lower tech future. So in all of this conversation and in so much of the public debate around, the future of AI, it's just assumed that we're going to have more and more technologies, more and more embedded in aspects of everyday life and work and so on.

00:44:30:10 - 00:44:55:21

But I'm not hearing many voices thinking about what could a lower tech, maybe not low tech, but lower tech future look like? And how might that actually enable us to have a closer relationship with the natural world, you know, survive climate change, reduce inequalities and so on? So why is more tech always the answer to getting us out of the problems we have now?

00:44:55:23 - 00:45:27:10

And haven't we by now? Don't we have enough data to actually show us that less tech could actually help us? Absolutely. And also that we have like a need for that which isn't met like that. We have a need for human contact and kind of friction and a little bit of randomness in our lives, but sometimes the seamless technologies that are kind of embedded in our smart homes and our smart cities that can take some of the texture out of life.

00:45:27:12 - 00:45:56:17

I'm interested in what you how you define nature. Just going to ask that. And I'm so glad that you that you went there because what is what is nature in all of this? And how have the kind of artificial the human made, the pollution, the urbanization of our planet, you know, you know, what's what's left of nature and and what do we understand by a natural world?

00:45:56:19 - 00:46:14:16

I mean, this is like an argument that I often have with students, like right in the beginning of people, often come in and they sort of want to make work that is about nature. And that's always one of the first questions I ask them, like, okay, what's nature? Where's that? And we do have this kind of thing, like nature was invented in the sort of romantic era.

00:46:14:16 - 00:46:32:00

I think the way we think of it now, like nature with a capital N, it's like this sort of, beautiful park kind of over there. It's this gorgeous protected area, and it's like over there. And you can go into it and have your kind of experience of consuming nature, and then you come back out of it and it's, you know, beautiful and untouched.

00:46:32:06 - 00:46:55:22

And of course, that's all an illusion, right? That's all artifice. That was created by people for that purpose. So there's something about the a kind of getting in touch with nature. When you say that, what I hear is it's getting in touch with ourselves, our nature as connected with this kind of broader set of systems, which are all kind of intricately embedded within each other.

00:46:55:22 - 00:47:22:24

And that it's there's no boundaries to it, really. Yeah. For for me, nature is very much about that. It's this idea that there are all these other systems operating at all different levels, in all different ways. Some of them, most of them are wild loads of it is uncontainable and uncontrollable by the sort of this our human desire to sort of keep everything neat and tidy and to create these kind of like fake natures, or they're still nature, but there's just a different nature.

00:47:23:01 - 00:48:03:09

But that nature, as in the world, you know, the physical, the organic, the chemical worlds all around us that makes up the the sort of planet that is constantly shifting and constantly changing, that kind of idea that brings us back to being quite small and humble and remembering that we are just these small bits of a bigger system, feel like we've almost gone like the full circle from what we were talking about at the very beginning, about how AI could maybe connect with the natural world by being more of a kind of nature than the kind of human thinking.

00:48:03:11 - 00:48:27:19

We have gone full circle. And it's a circle that, to me was completely unexpected. I did not think we'd be speaking about frozen critters, listening to the gentle rumbling and grumblings of glaciers, the environmental impact of AI and how we might think about being more responsible in our use, but also low resource in our use of AI,

00:48:27:21 - 00:48:58:12

the deeply philosophical question of what is intelligence, and is it fair to use the word artificial all the way through to questioning what, where and how is nature? So I'm so grateful for such a fascinating conversation. I think Daniel and Julie, you've had brilliant insights. You've left us with so much to ponder. But what I deeply, deeply appreciated was the the kind of joy, that you that you brought to this conversation around AI.

00:48:58:12 - 00:49:37:18

And for me, that's really refreshing because we're all talking about AI. But so many of those conversations are quite anxious, quite pessimistic, and are basically living in a version of the future that looks more like RoboCop and Terminator than what you've been describing. Julie and Danielle, thank you so much for joining us, and thanks as well to our listeners, and we'll hope you'll join us soon for more episodes of the RCA podcast.

00:49:37:20 - 00:50:03:00

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00:50:03:00 - 00:50:18:00

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