Dave: Hey everyone, Dave here with Phly Tech Entrepreneurs. Our podcast will feature members of the community and their subject matter expertise. Today, I’m speaking with Peter Croche. Peter is a product lead who loves building teams to do their greatest work while having fun along the way. He Zooms in with design engineering peers, leaning on his backgrounds as a designer and software engineer, and zooms out with business leaders and users to capture the essence of their needs and goals in digital products and services. Also, talking to Peter about his work over at Probable Futures, which has a number of, if I’m not mistaken, climate change prediction models, graphs, and data visualizations.
Peter: Doing well, how are you?
Dave: Enjoying the weather. I don’t know if that’s expected or not. We’re having some great weather in October in Philly, aren’t we?
Peter: Yeah, if we could just keep this, I’d be all right with that.
Dave: Right, yeah, let’s just make this last all the way into March. But we know that’s not going to be the case. If I’m not mistaken, you know a thing or two about weather and you’re doing some interesting stuff over at Probable Futures. I was on the website earlier kind of checking it out and getting myself very nervous about the future. So, I’d like to begin every podcast getting very, very concerned. So, a little bit about what you guys are up to over there.
Peter: So, Probable Futures is a nonprofit climate literacy initiative. Climate literacy is this idea of really understanding what it means to live in a changing climate. Living in a changing climate is different from living in a stable climate, and we’ve only lived in a stable climate so far. But there are certain skills that you need to live well in a changing climate, and those are fundamental in the same ways that having a fiduciary understanding and being good with money is. Everyone needs to have some kind of understanding with money just to exist and run a business in this world. Nowadays, there’s this other literacy that everyone has to have, and that’s digital literacy.
Dave: It’s such an interesting concept. I’ve had a number of conversations so far with this podcast. This one is unique in many ways. A lot of them have the theme of planning, but planning for things like maybe selling your business or things like that. Planning for climate change is a first, and I can imagine maybe in the coming years we’ll start to see this role kind of become more formal, sort of like your climate strategist or something like that who will maybe audit your business and your exposures to various kinds of climate challenges that might be affecting your supply chain, the people that you work with. Business is so global nowadays. It’s obviously important to kind of understand what you may be in for in the next five to plus years.
Peter: Yeah, absolutely. So let’s start with a little bit of context. When we think about climate change and where we’ve been, where we’re going, humans, we’ve been around for about 200,000 years, and for most of that time, we were mobile. We lived by hunting and gathering, and when you look at this chart, you can understand why, because the climate moved around a lot. We’re looking at a chart of global average temperature. So this is a way of understanding what the climate was, and you can see that the climate moved up and down and you have all these wide ranges. So people moved around because that was the rational thing to do when the nice places didn’t stay nice. You know, you don’t have these like a place Philadelphia staying a nice place to be for a long time. But then you have this stabilization that happened about 10,000 years ago. And at this point, people settled all around the world, all in different places, all at the same time. And so why did they all do this? They weren’t able to coordinate 12,000 years ago. They didn’t have the internet. Well, turns out it’s because the climate stabilized, right? And you can see that in this chart. And so when the nice places stayed nice, people settled, and they were able to then start building up all of this civilization that we have and everything on top of it. So you had a stable climate and you had communities and cultures building in persistent places over time, then building governments and infrastructure, and then industry to build faster than ever before. And then you have all these other useful abstractions on top like software and finance and all these other things. And some people say, you know, finance is the center of the world, it is doing a lot now. Software is eating the world, right? It’s doing a lot. But both of these things are only possible because of this stability that all the rest of civilization exists on top of the stable climate. And so that context tells us that actually we need to understand some things about the way the world will be so that we can keep it stable. You know, we want to keep being able to be entrepreneurs in this changing world, and so we need to understand the way the world will be. And so we built this platform, and it helps people gain that climate literacy that understanding. So you can walk through it yourself in like a Saturday morning or something. You can read through this kind of see, maybe it’ll take you a couple hours to read through and understand like what we’re talking about when we talk about this context for climate change. Or you can watch a five-minute video. That’s a great place to start too. But then you can also use these maps. And so the maps are global, and this is actual data about the way the world will be under different climate conditions using modeled climate scenarios. That’s not data we generated. It’s data that has been created over many decades by climate scientists who have been working on this for a long time. All the data is actually open source. What we’ve done is actually built this wrapper around it, I guess you could say, this interface and experience for people because to access this data without this, you have to like FTP on a server and then download it, and then you probably need some climate science expertise to understand it, which I don’t have. We have climate science partners who like I work with, and they help me understand how to make this stuff into maps. And then my team and I, the engineers and the designers and I, we pick up on like making this usable. So we built this application and like figured out what kinds of colors we want to use and like where we want to put the bins and all these other kinds of things like what are people going to need like search to search for a place, or maybe they’re going to need to download screenshots of a place. You know, or they’re going to need to like get some embeddable maps. You know, if you want to embed these maps on your own place. So all of this stuff here is all open-sourced, and it also we have open APIs that anyone can use. So we actually offer integrations. So if you’re working on a project and you want to say, bring some data in, you want to know like how many days above 90 will there be in any place in the world in different scenarios, you can do that. And we also have total annual precipitation change in snowy days change in dry and hot days, change in the wettest 90 days, change in frequency of the one in 100 storm, change in likelihood of year-plus drought, so looking at drought and wildfire, looking at other different temperature thresholds that we could cross, average temperature, loss of like frost nights and freezing days and nights above 20. So it’s hard to sleep if it’s too hot and you don’t have AC, of course. Unfortunately, a lot of us in Philly do have AC, but in some places, they don’t have a lot of AC, and so it can really be a problem there. And then heat and humidity combinations because as the climate warms, it’s also getting more humid. So you can use these maps to explore the world and start to look at okay, what are these scenarios that we need to prepare for? And you can see how it changes, you can see how the number of days above 90 that you know, we’re increasingly getting in Philly. You can see how those change and how it would change in different worlds. You can click on the map, you can actually see this data, and when you use the API, if you’re interested in doing an integration, which we have docs that are hopefully good and would love any feedback that anyone has on these, you can actually access the API or use our maps or anything like that. The API will give you data like this, so it’ll give you like point data. You want to throw at an address, it will throw you back some information about the way the world will be in the future depending on which map you’ve asked for. So that’s what we’re offering, and that’s this is now something that people are using in a wide variety of different contexts, which I’m happy to talk about too. But yeah, I’ll leave it there. Any questions that you have?
Dave: Very neat. Yeah, I just love visual data. I could see how someone could get lost in this for hours. I’d love to hear some quick bullet points on the different ways people are using this just to kind of inspire some ideas that, you know, and so yeah, what are the current sort of client user base like?
Peter: Yeah, totally. So Finance, supply chain, we have people in education using it, Hollywood, big production companies. We’re using it to try to understand how do we tell better stories about the way the future will be because a lot of the stories are, you know, apocalypse or like we solve climate change or something, and neither of those are true. We’re actually going to have something in between. Future’s going to be different, but it’s not going to be an apocalypse in the near term. So, a lot of different contexts. Some on the finance side are very big banks, like some of the biggest in the US, who are using it to really understand like how will the world be different and how do we need to update, you know, how we think about the world based on that. Also consulting companies. We’ve worked a lot with McKinsey. So thinking about how do we bring this data and these ideas into boardrooms so that people in the executive suites can really understand how we need to make different decisions. And then also governments. So working with people in elected positions, their cabinets and stuff, of, you know, how do we need to prepare for this? So maybe we need more cooling centers or more hours allocated to cooling centers in Philadelphia. So those are some examples.
Dave: Very neat. Yeah, I mean, you sort of expect some governments maybe, you know, education things, but it’s cool to hear about the private sector leveraging the data as well. Thanks so much for sharing this with us, Peter. For people that want to get in touch with you, learn a little bit more about what you guys are up to at Probable Futures, how can they do that?
Peter: Feel free to go to probablefutures.org or reach out to me at p.croche@probablefutures.org.
Dave: Awesome, cool. Thanks so much.
Peter: Yeah, thanks.