The Nature of AI: Solving the Planet's Data Gap with Drew Purves

**Drew Purves** (0:08)
Sometimes you think that the real change can come in the long run from these moments of awakening, where people almost overnight can change their relationship with nature. If AI can help to empower that, that might in the long run be the most powerful role of AI.

**Hannah Fry** (0:26)
Welcome back to Google DeepMind to the podcast. I'm Professor Hannah Fry. Now, we focus a lot in this podcast on AI and its interactions with humans. But there is another story that's unfolding, one in which AI could help protect our planet. Think oceans and forests and deserts and fragile ecosystems, and the millions of animal species that are crawling, swimming and flying across this earth. AI has the potential to tackle one of the biggest challenges of our time, the damage to nature and ecosystems. But with a problem that's this vast, where do you even begin? Well, Drew Purves, Nature Lead at Google DeepMind is my guide to the rich terrain of AI for nature. He has got two decades of experience in ecological research and has been at Google DeepMind for almost 10 years now. Drew, thank you so much for joining me.

**Drew Purves** (1:18)
Oh, thanks, it's great to be here.

**Hannah Fry** (1:20)
I think most people probably agree by now that the environment is an important aspect of our future, something that deserves preserving and looking after. What's holding us back in this area? What's making it a difficult problem?

**Drew Purves** (1:33)
Well, the short answer to that often is lack of information. So you're right, you know, there's this groundswell now of agreement about the importance of biodiversity, ecosystems and nature. And then we have signs of action in different sectors, in the private sector and the government sector. You know, if you look at some of the numbers, for example, I mean, there are 189 countries around the world that have signed up to the 30 by 30 plan, which is to protect 30% of ecosystems on land and in the oceans by the year 2030 There's so much to feel good about, but often when it comes down to actually taking action on the ground to either protect or restore biodiversity in ecosystems, it's just a lack of basic information.

**Hannah Fry** (2:10)
So what are the big questions that AI could help answer in this space then?

**Drew Purves** (2:14)
I mean, there are a number of them, obviously. But for example, if you're thinking about a protection scenario, protecting biodiversity, you need to know where the biodiversity is. It might be focal species or it might be biodiversity hotspots and so on. It might be a particular endemic species. If it's a restoration scenario, you want to find particular places around the world that have the highest potential for ecological restoration. But for example, you might need to know which species of trees to plant or which species of animals to reintroduce. So down at this local level, it's because biodiversity is so place-specific, you need that locally relevant information for communities or whatever local action is happening to guide the action down there. And often it's just missing.

**Hannah Fry** (2:53)
Is that the big goal, then, of Google DeepMind using AI in nature, to really fill in the information gaps in the same way that we have done for the human world?

**Drew Purves** (3:02)
Well, here at Google DeepMind, we're growing a portfolio of work around AI for nature. And there are at least three key categories of AI for nature to explore. So, the first of those is AI for data. And that can mean bringing in data from the field, from things like cameras, microphones and so on. Or identifying and bringing in data from the literature, because there's a huge amount of data there. The second category, though, is taking all of that data and combining it with lots of other sources of data, like satellite data and so on, to create that derived information that decision makers need to protect or enhance nature. And then the third category, which is easy to miss, is that all the information in the world is fine, but human beings can get overwhelmed by that amount of data. So then there's this key role for active deployment of AI to help decision-making, to help people make sense of all that data and act.

**Hannah Fry** (3:49)
And that's, I guess, in part because, you know, this is sort of quite a new area, right? I mean, this hasn't been around for as long as some of the other applications of AI. It's not as obvious of how to sort of solve biodiversity as it might be to solve, you know, disease, for instance.