WEBVTT - Making Transportation Systems Eco-friendly is a Solvable Problem 0:00:15.076 --> 0:00:24.436 Pushkin, this is solvable. I'm Ronald Young Junior. We are 0:00:24.436 --> 0:00:28.036 trying to push people towards decision that are less carbon intensive, 0:00:28.196 --> 0:00:32.276 so create less climate emissions from transportation. Also better for 0:00:32.676 --> 0:00:36.036 expenditures of tax dollars being more wise, as well as 0:00:36.076 --> 0:00:39.836 improving safety outcomes in transportation. For Laura Schuel, making greened 0:00:39.876 --> 0:00:42.996 decisions isn't a matter of juggling one hundred little choices 0:00:43.036 --> 0:00:47.236 like wind, unplug appliances, eat less meat, or swap out 0:00:47.236 --> 0:00:50.476 incandescent bulbs. For LEDs, choose a car that gets fifty 0:00:50.556 --> 0:00:53.276 mpg over forty mpg, you don't have to think about 0:00:53.276 --> 0:00:55.436 it as much. So like think about the big decisions 0:00:55.476 --> 0:00:57.436 that matter and like stop freaking out if you forget 0:00:57.476 --> 0:01:01.676 your cloth grocery bags. Once. As CEO of street Light Data, 0:01:01.996 --> 0:01:05.236 Shoel has the data to back this stuff up, but 0:01:06.036 --> 0:01:10.516 you won't find her postilytizing yet. I have a fundamental 0:01:10.596 --> 0:01:15.476 belief that informed decisions will arc towards changes that I 0:01:15.516 --> 0:01:18.676 want to see in the world. But we, as data providers, 0:01:19.036 --> 0:01:21.356 we have to be neutral because we're a source of truth. 0:01:21.996 --> 0:01:25.716 Street Light Data is a transportation analytics company, and Laura 0:01:25.836 --> 0:01:29.436 Schuel thinks how we move can be changed for the better. 0:01:29.996 --> 0:01:32.956 My name is Laura Schuel. I'm the CEO of street 0:01:32.996 --> 0:01:36.676 Light Data. How to monitor and mold our transportation systems 0:01:36.676 --> 0:01:47.676 into smart and environmentally friendly systems is a solvable problem. 0:01:47.716 --> 0:01:51.036 I recently watched Bishion Impossible three and Tom Cruise, who 0:01:51.036 --> 0:01:53.796 plays Ethan Hunt, is a part of the Impossible Mission force. 0:01:53.876 --> 0:01:58.316 In this one, he's actually getting married and as a result, 0:01:58.356 --> 0:02:00.996 his cover for working for the Impossible Bishion Force is 0:02:00.996 --> 0:02:03.436 that he works for the Bureau of Transportation. So he's 0:02:03.436 --> 0:02:05.956 at a party and he makes this cobbent where he goes. Yeah, 0:02:05.996 --> 0:02:08.356 traffic patterns are so crazy. It moves, it's like an organism. 0:02:08.436 --> 0:02:10.636 It's very interesting thing. And everyone kind of looks at 0:02:10.716 --> 0:02:12.956 him like this guy's kind of boring. And so what 0:02:13.036 --> 0:02:15.436 I'm thinking about our listeners, I'm thinking about them and 0:02:15.516 --> 0:02:19.036 thinking about data could beat something that's like extremely boring 0:02:19.116 --> 0:02:21.556 to them. But give me a piece of data that's 0:02:21.636 --> 0:02:24.236 excites you the most and something that you think a listener, 0:02:24.396 --> 0:02:26.996 just a casual person would find interesting when it comes 0:02:26.996 --> 0:02:30.436 to talking about transportation data. Well, first of all, that 0:02:30.516 --> 0:02:32.596 movie sounds awesome, and my company is immediately going to 0:02:32.636 --> 0:02:35.076 have a movie night about it. Second of all, he's 0:02:35.156 --> 0:02:37.196 not boring. He sounds like the most interesting person at 0:02:37.196 --> 0:02:40.796 the party. I love that. One of the things that 0:02:40.836 --> 0:02:44.316 I hope is coming with Secretary Budajes and President Biden 0:02:44.836 --> 0:02:48.156 is a demand that we calculate our transportation greenhouse gases, 0:02:48.156 --> 0:02:50.316 which we don't really do. We kind of swag it. 0:02:50.796 --> 0:02:53.076 One of the concerns with that is that then it 0:02:53.116 --> 0:02:56.876 would be bad for rural places, because rural places, especially 0:02:56.876 --> 0:02:58.836 with highways, are places where you have a lot of 0:02:58.876 --> 0:03:02.276 miles driven that have nothing to do with that rural place. 0:03:02.356 --> 0:03:05.556 Right people are cutting through min DOT Minnesota DOOT used 0:03:05.556 --> 0:03:09.116 our data to do a version of greenhouse gas emission 0:03:09.316 --> 0:03:13.196 that attribute the miles driven to the destination of the 0:03:13.236 --> 0:03:15.436 car in the truck. And what that does is it 0:03:15.516 --> 0:03:19.876 properly demands payment, so to speak, from the cities from 0:03:19.876 --> 0:03:21.716 the fact that they cause all this driving to and 0:03:21.796 --> 0:03:25.796 from them, and doesn't put disproportionate cost in carbon on 0:03:25.836 --> 0:03:29.076 the rural areas. That sort of data driven approach could 0:03:29.116 --> 0:03:31.716 reduce some of the future pushback we're going to see 0:03:31.956 --> 0:03:35.836 about carbon accounting from transportation. One interesting thing that I 0:03:35.876 --> 0:03:38.756 heard about you was that you started off as a 0:03:38.796 --> 0:03:43.516 comparative literature major. So how did you end up going 0:03:43.596 --> 0:03:50.276 for comparative literature to data analytics. Ah, it is a 0:03:50.356 --> 0:03:53.396 classic story of a great professor. So I was in 0:03:53.436 --> 0:03:56.076 college and I was majoring in comparative literature, and I 0:03:56.116 --> 0:03:59.516 assumed I would be a literature professor. That just seems 0:03:59.556 --> 0:04:03.156 my destiny. And because of distribution requirements, you had to 0:04:03.196 --> 0:04:05.796 take one science class by the end of sophomore year. 0:04:06.396 --> 0:04:10.916 So I took Introduction to Environmental Engineering just because it 0:04:10.996 --> 0:04:13.316 fit my schedule. And I came out of the final 0:04:13.396 --> 0:04:15.796 and I was like, Oh, climate change is the most 0:04:15.836 --> 0:04:19.156 important thing of my generation, and now no, I must 0:04:19.516 --> 0:04:23.076 spend my life working on this. So you founded a 0:04:23.076 --> 0:04:26.396 company called Streetlight. Tell me a little bit about what 0:04:26.476 --> 0:04:30.996 it does. Street Light is a transportation analytics company. So 0:04:31.236 --> 0:04:34.596 from the perspective of somebody making transportation decisions, like a 0:04:34.676 --> 0:04:37.996 government or an engineering firm, or somebody starting like a 0:04:38.036 --> 0:04:41.236 delivery company before street Light, they're operating a world with 0:04:41.316 --> 0:04:44.076 little data. So you have to make a decision about 0:04:44.116 --> 0:04:46.356 like should I spend two billion dollars on this highway 0:04:46.356 --> 0:04:49.916 extension or a billion dollars on this new transit line. 0:04:50.116 --> 0:04:51.796 But there was very little data to guide you. So 0:04:51.836 --> 0:04:54.076 what street Light does is we take advantage of the 0:04:54.116 --> 0:04:57.556 fact that everything that moves now is collecting data. Smartphones, 0:04:57.596 --> 0:05:03.076 connected cars, connected trucks, little scooters. There's data embedded in stoplights, everything, 0:05:03.396 --> 0:05:05.476 and we license it from all different types of places 0:05:05.476 --> 0:05:08.516 and a privacy appropriate manager and smush it together with 0:05:08.556 --> 0:05:11.036 a lot of p terry algorithms and machine learning so 0:05:11.076 --> 0:05:13.676 that you can look up a transportation fact as easily 0:05:13.716 --> 0:05:16.036 as you might look up a fact in Wikipedia. So 0:05:16.116 --> 0:05:18.076 what would you say The benefit of this data is 0:05:18.156 --> 0:05:22.476 for whom our product is not for consumers like you 0:05:22.556 --> 0:05:25.956 or me. It's for transportation professionals, and that's usually someone 0:05:25.996 --> 0:05:29.236 in government, someone an engineering firm, or someone with their 0:05:29.276 --> 0:05:34.316 own private transportation company like Uber or a private tollway 0:05:34.396 --> 0:05:36.596 or things like that. So the benefit is, instead of 0:05:36.636 --> 0:05:40.036 making decision based on somebody yelling at you and kind 0:05:40.036 --> 0:05:42.636 of your gut, you make a decision that is based 0:05:42.676 --> 0:05:45.476 on data and that is based on a real understanding 0:05:45.476 --> 0:05:49.756 of the context. That's the fundamental benefit. Now, then there's 0:05:49.756 --> 0:05:51.636 a bigger question, which is what is the benefit of 0:05:51.676 --> 0:05:54.116 making a good decision? And we are trying to push 0:05:54.116 --> 0:05:57.716 people towards decision that are less carbon intensive, so create 0:05:57.836 --> 0:06:02.476 less climate emissions from transportation. Also better for expenditures of 0:06:02.476 --> 0:06:05.956 tax dollars being more wise, as well as improving safety 0:06:05.956 --> 0:06:11.156 outcomes in transportation. This all sounds very noble, and I'd 0:06:11.196 --> 0:06:17.396 be interested to know how you picked this specific lane. 0:06:17.436 --> 0:06:19.436 I would say, when well, I guess lane, we're talking 0:06:19.476 --> 0:06:23.196 about translation lane. How would you pick this specific lane 0:06:24.156 --> 0:06:26.316 when it comes to trying to solve for climate change? 0:06:27.076 --> 0:06:30.076 The climate community is paying less attention to transportation than 0:06:30.116 --> 0:06:32.636 to other parts of the climate crisis. So really I 0:06:32.636 --> 0:06:35.636 could have chosen anything, because it's all worth a lifetime, 0:06:35.956 --> 0:06:37.356 But I was like, well, I got to pick something. 0:06:37.796 --> 0:06:41.876 Transportation I think has less people, so it deserves my attention. 0:06:42.076 --> 0:06:44.836 And also it's just interesting. I mean, where people go, 0:06:45.596 --> 0:06:48.556 how they think about the new round about in their city, 0:06:48.876 --> 0:06:51.036 how they think about their commute. I have. As soon 0:06:51.076 --> 0:06:53.756 as you say you're in transportation, your cocktail party conversations 0:06:53.756 --> 0:07:02.156 are covered because everybody wants to talk about it. You're 0:07:02.156 --> 0:07:05.596 a for profit company, so how do you control or 0:07:05.636 --> 0:07:08.196 and how can you really give guidance the folks to 0:07:08.276 --> 0:07:10.516 make why is the cis when it comes to climate change? 0:07:10.796 --> 0:07:13.956 Rather than just using your data to maybe monetize or 0:07:14.556 --> 0:07:18.396 build more malls, just give more opportunities to sell things 0:07:18.476 --> 0:07:21.076 the people rather than actually doing the things that would 0:07:21.076 --> 0:07:24.596 improve the planet. That is a really good question. So 0:07:24.636 --> 0:07:26.876 before I started street Light, I had never worked at 0:07:26.916 --> 0:07:29.916 a for profit company. I had worked for nonprofits, not 0:07:30.036 --> 0:07:33.596 for profits, and geo's. I'd worked for the government. I'd 0:07:33.596 --> 0:07:36.876 been an academia. I'd been getting my PhD. With all 0:07:37.756 --> 0:07:41.436 love and respect to my nonprofit friends and colleagues and 0:07:41.476 --> 0:07:44.156 my government friends and colleagues, I had felt a little 0:07:44.156 --> 0:07:47.356 bit frustrated by the scope you can get when you're 0:07:47.396 --> 0:07:50.596 at a nonprofit and you're constantly scrambling for money. I 0:07:50.636 --> 0:07:52.516 had seen a lot of green tech companies that I 0:07:52.556 --> 0:07:56.716 thought were scaling their impact faster than I believed possible 0:07:56.756 --> 0:07:59.156 in the nonprofit sector. But there's a trade off there 0:07:59.436 --> 0:08:02.236 because we almost never tell our customer you should do 0:08:02.276 --> 0:08:04.756 this because it's greener, you should do this because it's 0:08:05.356 --> 0:08:08.716 better for asthma costing pollutants. If they ask us about that, 0:08:08.756 --> 0:08:12.516 we'll all is given the answer. But as data providers, 0:08:12.836 --> 0:08:15.196 we have to be neutral because we're a source of truth. 0:08:15.876 --> 0:08:20.796 So I have a fundamental belief that informed decisions will 0:08:20.916 --> 0:08:23.356 arc towards changes that I want to see in the world. 0:08:23.676 --> 0:08:26.036 And one of the reason the transportation world is not 0:08:26.116 --> 0:08:28.236 headed in the direction that I like is because we 0:08:28.236 --> 0:08:30.436 don't use data. We base decisions on what we've done 0:08:30.476 --> 0:08:33.676 in the past or the more powerful lobby. So there 0:08:33.756 --> 0:08:36.996 is a faith jump in choosing to go that for 0:08:37.156 --> 0:08:40.836 profit route. Do you think that's a little more optimistic 0:08:41.076 --> 0:08:44.756 than is necessary to actually solve the problem of climate change? 0:08:44.796 --> 0:08:46.796 Because I think that people, when they have more information 0:08:46.916 --> 0:08:50.076 make better decisions. I think that's true, but it also 0:08:50.316 --> 0:08:52.156 means that we have to trust the person making the 0:08:52.196 --> 0:08:55.996 decision that they'll make the right one. In general, I 0:08:56.036 --> 0:08:59.956 am skeptical about people just because they have better information 0:08:59.996 --> 0:09:03.556 always making the right decision. But in transportation in particular, 0:09:04.036 --> 0:09:07.156 what we are dealing with is this immense inertia of 0:09:07.276 --> 0:09:11.596 building more highways to facilitate more cars going fast. Biking 0:09:11.596 --> 0:09:16.516 and walking are hugely important parts of solving transportation climate emissions. So, 0:09:16.836 --> 0:09:20.396 as one example, a lot of attention before COVID and 0:09:20.476 --> 0:09:22.676 during COVID has been drawn to the fact that bicycle 0:09:22.716 --> 0:09:26.116 and pedestrian deaths are on the up and if people 0:09:26.116 --> 0:09:28.036 are dying and it's getting a lot of press. A. 0:09:28.276 --> 0:09:30.516 I do not want people to die, and B it's 0:09:30.156 --> 0:09:33.716 also a challenge for our bigger goal of a more 0:09:33.836 --> 0:09:38.476 climate friendly transportation world. One of the major issues that 0:09:38.516 --> 0:09:42.276 came up is nobody knows like bike bike deaths per 0:09:42.316 --> 0:09:44.836 what Like nobody knows how many bike trips there are 0:09:45.276 --> 0:09:47.876 in the US or in a neighborhood or in a city. 0:09:48.156 --> 0:09:50.596 And we had that data available and that has become 0:09:50.596 --> 0:09:53.796 one of our top use cases in under eighteen months. 0:09:54.356 --> 0:09:56.796 I think many states and cities are make much more 0:09:57.556 --> 0:10:01.956 wise and informed decisions about bicycle and pedestrian safety, which 0:10:02.276 --> 0:10:05.036 a is good for humans and b is good for climate. 0:10:05.556 --> 0:10:08.276 As a data driven person, you're putting a lot of faith. 0:10:09.676 --> 0:10:12.836 Are you seeing more of people making good decisions based 0:10:12.836 --> 0:10:15.436 on this data than you are of them making profitable 0:10:15.556 --> 0:10:19.636 or capitalistic decisions based on this data. I don't know 0:10:19.676 --> 0:10:22.356 if I've ever calculated the ratio, but I always say 0:10:22.636 --> 0:10:24.556 streetlight is not a magic box that tells you what 0:10:24.636 --> 0:10:27.556 to do. It's a tool to help smart people do 0:10:27.636 --> 0:10:30.756 what they want to do more effectively. Now, those smart 0:10:30.796 --> 0:10:34.036 people could want to be doing capitalistic things. But one 0:10:34.076 --> 0:10:37.036 thing that has been huge in my industry and transportation 0:10:37.036 --> 0:10:40.356 and urban planning is the people who are coming into 0:10:40.356 --> 0:10:43.356 the industry do not look like and are not motivated 0:10:43.396 --> 0:10:45.356 by the same things that the people who came in 0:10:45.636 --> 0:10:47.996 ten years ago or twenty years ago or fifty years ago, 0:10:48.036 --> 0:10:51.116 many of whom are still just starting to retire. And 0:10:51.196 --> 0:10:55.196 this generation of people coming into it are very motivated 0:10:55.196 --> 0:10:56.836 by the right decisions, and we're trying to give them 0:10:56.876 --> 0:10:58.316 tools so they can get done what they want to 0:10:58.316 --> 0:11:02.036 get done. And I also will say with the government clients, 0:11:02.916 --> 0:11:05.156 most of them that I meet, even if they are 0:11:05.316 --> 0:11:08.316 very dedicated to say highway expansion, which is something that 0:11:08.476 --> 0:11:10.036 if I had to some arise my life goal, it 0:11:10.036 --> 0:11:12.476 would be to stop highway expansion in the United States. 0:11:13.196 --> 0:11:15.756 That would be it. Even if they are they are 0:11:15.836 --> 0:11:20.076 motivated by something they perceive as good, like they perceive 0:11:20.116 --> 0:11:22.436 it as good for their community, and they perceive it 0:11:22.476 --> 0:11:24.996 as good for jobs in their community. People who go 0:11:24.996 --> 0:11:27.316 into government don't go into government to get rich, right, 0:11:28.676 --> 0:11:30.756 And I'm not talking about the electeds. I don't deal 0:11:30.756 --> 0:11:32.396 with electeds all that off, and I deal with staff. 0:11:32.876 --> 0:11:35.076 And even if I don't agree with their definition of good, 0:11:35.356 --> 0:11:37.476 we both agree we're trying to do something for our community. 0:11:37.516 --> 0:11:44.556 So there's a commonplace to start talking. Tell me a 0:11:44.596 --> 0:11:46.956 little bit about where you get your data from. We 0:11:47.036 --> 0:11:49.236 use lots of different types of data. We're like a 0:11:49.356 --> 0:11:51.916 surfer and we're surfing the wave of data, and data 0:11:52.036 --> 0:11:55.396 is this always changing thing, and whatever data we use today, 0:11:55.396 --> 0:11:57.076 it'll be different six months from now, in a year 0:11:57.076 --> 0:11:59.836 from now. But right now, the main data we use 0:11:59.916 --> 0:12:02.996 that's the most important is from smartphones. So we have 0:12:03.196 --> 0:12:05.956 an opt in process, which is a much more privacy 0:12:06.036 --> 0:12:09.636 pro privacy process where people can work with one of 0:12:09.676 --> 0:12:12.836 our four hundred and so AT partners and opt into 0:12:13.036 --> 0:12:16.076 deidentified locational tracking in the background. And what that means 0:12:16.156 --> 0:12:18.156 is we don't know you're Ronald. You have a hash 0:12:18.196 --> 0:12:20.556 to identifier, and so we never get any what's called 0:12:20.596 --> 0:12:22.836 personally identifiable information, and we don't know your name, your 0:12:22.836 --> 0:12:25.796 phone number, anything like that. We also get data from 0:12:25.796 --> 0:12:28.876 connected cars that have GPS tooling in them, as well 0:12:28.876 --> 0:12:33.196 as fleet management systems, which are truck management systems. Trucks 0:12:33.276 --> 0:12:35.476 rip up the road and cause safety impacts in a 0:12:35.556 --> 0:12:37.796 very different way than cars, so it's important to study 0:12:37.836 --> 0:12:40.596 them separately. But the deep benefit of the phones is 0:12:40.636 --> 0:12:43.716 that they cover all the modes of transportation and one 0:12:43.756 --> 0:12:48.076 of street lights core missions and sort of differentiators. One 0:12:48.116 --> 0:12:50.036 of the things we've done that's really new is we 0:12:50.116 --> 0:12:54.196 measure all the modes car, truck, bike, ped riding, a train, 0:12:54.356 --> 0:12:58.996 riding a bus, riding a ferry, eventually, jetpack whatever. And 0:12:59.076 --> 0:13:01.516 that is something that has never really been available before. 0:13:01.556 --> 0:13:03.676 And that's one of the reasons that cars keep getting 0:13:03.676 --> 0:13:05.716 this hegemony is because they're the only things that are 0:13:05.716 --> 0:13:10.956 consistently measured. So we have all those breadcrumbs floating around, 0:13:11.476 --> 0:13:14.716 and then we mix it with data from embedded sensors 0:13:14.716 --> 0:13:17.196 in the roadways that help us calibrate. We mix it 0:13:17.196 --> 0:13:21.156 with bite counter data, padcounter data, data from bus ridership 0:13:21.556 --> 0:13:24.556 data that says, you know, low income people live here, 0:13:24.676 --> 0:13:26.316 high income people live here, this is a road with 0:13:26.316 --> 0:13:28.236 fifty mile per hour speed limit, this is the ocean, 0:13:28.276 --> 0:13:31.516 all sorts of contextual data to turn it into actionable 0:13:31.556 --> 0:13:35.596 and aggregate analytics. One of the drawbacks to a data 0:13:35.596 --> 0:13:38.316 company like street Light is that you guys are selling 0:13:38.356 --> 0:13:40.916 your data to people that could pay. It's not something 0:13:40.916 --> 0:13:44.516 that's free to public, but it's information about public movements. 0:13:44.756 --> 0:13:46.636 Are you concerned to having to pay for this data 0:13:46.756 --> 0:13:50.236 hinders its ability to be truly useful. It's a great question, 0:13:51.076 --> 0:13:54.756 so I am, of course somewhat concerned. Some of the 0:13:54.756 --> 0:13:58.196 mitigation steps we take are all academic researchers who are 0:13:58.236 --> 0:14:01.636 researching something within our mission, which is climate equity safety, 0:14:02.396 --> 0:14:04.356 get free access you just failed to form. And we 0:14:04.396 --> 0:14:07.876 have like seventy five universities that we're working with who 0:14:07.916 --> 0:14:10.916 are doing totally free research based on our data. And 0:14:10.996 --> 0:14:15.276 we also have fellowships where nonprofits can apply to get 0:14:15.276 --> 0:14:17.836 free research, and we also help promote their research. But 0:14:18.316 --> 0:14:21.796 that is mitigation. That's not fixing the fundamental problem you've 0:14:21.796 --> 0:14:23.956 talked about. And I don't have a great fix. And 0:14:24.196 --> 0:14:27.436 we have a hundred staff, We spend a lot of 0:14:27.476 --> 0:14:29.436 money on the cloud, and what we do is expensive. 0:14:30.276 --> 0:14:34.596 We have to survive. And I think that in America 0:14:34.676 --> 0:14:40.236 we have consistently disinvested in government driven collection of data. 0:14:40.316 --> 0:14:43.156 But because we've made that decision that data is something 0:14:43.196 --> 0:14:47.356 that private markets are going to develop, we can't have 0:14:47.436 --> 0:14:50.876 everything online. What issues are you eager to see solved 0:14:50.876 --> 0:14:53.876 in transportation in the next five years. There's a big 0:14:53.916 --> 0:14:58.236 conversation right now in the Senate about everybody's saying in 0:14:58.276 --> 0:15:01.676 the infrastructure bill. Oh yeah, we should measure equity in transportation, 0:15:01.916 --> 0:15:04.876 And they're like, how, no one knows, there's no way, 0:15:05.196 --> 0:15:08.036 Like I mean, there's forty five thousand ways, there's no agreement. 0:15:08.396 --> 0:15:09.796 So there's going to be a lot of quick work 0:15:09.796 --> 0:15:11.556 on that. So I'm very interested in that. Street Light 0:15:11.676 --> 0:15:14.916 is working on a lot more direct carbon and equity 0:15:15.276 --> 0:15:18.036 measurements now that we have a Biden administration. That opens 0:15:18.116 --> 0:15:20.996 up the space where that could be used. So we 0:15:21.036 --> 0:15:23.676 are going to make a lot of tooling that's more 0:15:24.196 --> 0:15:28.156 mission direct in addition to our more neutral data collection efforts. 0:15:28.156 --> 0:15:31.356 So that is starting now. We need to solve the 0:15:31.476 --> 0:15:34.356 question of what does it mean to have equitable transportation 0:15:34.476 --> 0:15:36.276 and how do you define it because there's no good 0:15:36.556 --> 0:15:39.836 there's no good definition right now, and we're collaborating with 0:15:39.876 --> 0:15:43.556 some nonprofits and some advocacy organizations to get explicit measurements 0:15:43.596 --> 0:15:45.916 about that. The fact that we can measure the income 0:15:45.956 --> 0:15:49.236 and racial distribution of where people move is a huge 0:15:49.316 --> 0:15:53.036 leap forward and starting to measure transportation equity. I mean, 0:15:53.076 --> 0:15:56.076 it sounds like you're saying that transportation equity begins with data. 0:15:56.276 --> 0:15:58.996 I think everything begins with data. So take that with 0:15:59.036 --> 0:16:01.236 a grain of salt. I mean, transportation is in a 0:16:01.396 --> 0:16:05.116 bad way in America. It's dissequitable, it's destroying the climate. 0:16:05.116 --> 0:16:06.796 It kills forty three thousand people a year, and like 0:16:06.796 --> 0:16:09.596 our bridges are falling down, Like we're pretty bad. So 0:16:09.636 --> 0:16:11.756 we have to change. And to think of a massive 0:16:11.796 --> 0:16:15.556 systemic change without data, I just think that's insane. But 0:16:15.676 --> 0:16:18.276 I agree it's not data alone. We are a tool 0:16:18.316 --> 0:16:21.276 for smart people motivated by the right things to do 0:16:21.316 --> 0:16:24.716 their job more easily. How do you motivate private companies 0:16:24.716 --> 0:16:32.436 to care about public issues like climate change? There are 0:16:32.476 --> 0:16:36.516 two ways you get corporations to care about climate change. 0:16:37.116 --> 0:16:40.196 One is you point out to them that it will 0:16:40.236 --> 0:16:42.716 have a huge impact on their bottom line either today 0:16:42.796 --> 0:16:44.716 or in ten years. And a lot of corporations are 0:16:44.756 --> 0:16:47.316 there right, they get that. And the second way is 0:16:47.316 --> 0:16:51.916 their staff starts to throw a fit, so we help. 0:16:52.396 --> 0:16:56.236 We have helped some staff throw fits quietly. We don't 0:16:56.236 --> 0:17:00.196 do it that directly. That's what we do. Do you 0:17:00.396 --> 0:17:04.876 do you want us to include that? The main thing 0:17:04.916 --> 0:17:07.796 we point out is that staff. If all your staff 0:17:07.836 --> 0:17:10.356 have to drive their own cars fifty miles each way, 0:17:10.396 --> 0:17:13.636 like that will dwarf the climate impact of your office 0:17:13.676 --> 0:17:16.596 building within a couple of years. Gotcha, So we've we've 0:17:16.636 --> 0:17:22.956 worked on that. Okay, I think that's a good strategy. 0:17:25.676 --> 0:17:28.836 How can our listeners help, Like, what could someone who 0:17:28.916 --> 0:17:32.396 wants to be like a more responsible and better city resident? 0:17:32.716 --> 0:17:35.716 How can they help right now? And what about people 0:17:35.756 --> 0:17:37.796 that don't live in like bustling cities, people that live 0:17:37.796 --> 0:17:39.996 in more rural areas. How can we all help make 0:17:39.996 --> 0:17:45.556 it make transportation better for everyone? Well, one thing that 0:17:45.676 --> 0:17:48.436 I think is fun is to track your own data 0:17:48.476 --> 0:17:51.716 for a few days. One thing that I think sounds 0:17:51.716 --> 0:17:54.956 simple but nobody gets is that your short trips are 0:17:55.036 --> 0:17:59.476 less carbon emitting than your long trips. So I've had 0:17:59.556 --> 0:18:02.276 some friends, you know, lovely eco hippie friends who say 0:18:02.276 --> 0:18:05.236 do things to me like, well, you know, I take 0:18:05.236 --> 0:18:06.956 a bus every day to work. The only reason I 0:18:06.956 --> 0:18:08.796 have a car is for like, you know, we can 0:18:08.796 --> 0:18:11.196 advent to go hiking. And I'm like, well that is 0:18:11.236 --> 0:18:13.676 a hundred and ten mile drive. Like, I'd rather you 0:18:13.756 --> 0:18:16.836 drive to work every day and maybe car pool or 0:18:16.876 --> 0:18:19.196 take the train for you to adventures. So really think 0:18:19.236 --> 0:18:22.036 it's the length of the drip that matters, So track 0:18:22.076 --> 0:18:23.796 your own data. I think it will surprise you, it 0:18:23.876 --> 0:18:26.316 might make you more open to an electric car, and 0:18:26.476 --> 0:18:28.476 it might help you think about which trips really matter. 0:18:29.196 --> 0:18:32.156 I also think that as a citizen, as a private individual, 0:18:32.196 --> 0:18:35.876 there are three personal infrastructure decisions you make in transportation. 0:18:36.676 --> 0:18:39.236 Where you live, which car you buy, if you buy 0:18:39.236 --> 0:18:43.196 a car, and where you spend most of your days, 0:18:43.236 --> 0:18:46.436 which is usually where you work. And if you optimize 0:18:46.436 --> 0:18:49.156 those decisions a little, like if you move to an 0:18:49.156 --> 0:18:51.316 apartment that's closer to work, or choose a job that's 0:18:51.316 --> 0:18:54.276 a little closer, you've optimized your transportation footprint and you 0:18:54.316 --> 0:18:57.076 don't have to like agonize about it every day. So 0:18:57.236 --> 0:18:59.236 optimize those big You know, if you choose a car 0:18:59.276 --> 0:19:02.036 that gets fifty mpg over forty mpg, you don't have 0:19:02.116 --> 0:19:04.036 to think about it as much. So like think about 0:19:04.076 --> 0:19:06.196 the big decisions that matter, and like stop freaking out 0:19:06.236 --> 0:19:09.676 if you forget your cloth grocery bags once. Those infrastructure 0:19:09.676 --> 0:19:11.876 decisions matter more where you live, where you work, the 0:19:11.876 --> 0:19:14.036 relationship between them, and what car you drive if you 0:19:14.116 --> 0:19:18.156 drive a car. As citizens, citizens have a lot of 0:19:18.196 --> 0:19:22.276 power about city level urban design decisions. If you show up, 0:19:22.476 --> 0:19:26.116 there's always feedback meetings, and if you show up, you 0:19:26.156 --> 0:19:28.716 will make a difference. And I think the other thing 0:19:28.716 --> 0:19:30.316 to remember is a lot of the people show up 0:19:30.356 --> 0:19:33.316 are people who have a very vested interest in things 0:19:33.356 --> 0:19:36.796 being the same, which may be good. Sometimes it's not, 0:19:37.276 --> 0:19:41.636 or people who just assume the worst. And usually the 0:19:41.716 --> 0:19:44.876 staff at these meetings, again it's not elected, it's staff 0:19:44.876 --> 0:19:48.476 who've chosen this career. Usually they are trying really hard. 0:19:49.036 --> 0:19:51.276 And if someone calmly showed up and said, can you 0:19:51.316 --> 0:19:53.356 show me the data? Can you show me the alternatives, 0:19:53.716 --> 0:19:55.476 they would be so excited and that person would be 0:19:55.476 --> 0:19:59.276 so impactful. So showing up and showing up trying to 0:19:59.996 --> 0:20:03.996 work with the staff instead of assuming the worst of them, 0:20:04.076 --> 0:20:06.876 I think is really powerful. You have any books or 0:20:06.916 --> 0:20:10.156 movies that you think you would recommend for people to 0:20:10.196 --> 0:20:13.156 learn more about transportation and transportation equity, Well, now I 0:20:13.196 --> 0:20:17.316 want everybody to watch Mission Impossible, Three Three Angels Protocol 0:20:17.356 --> 0:20:19.756 are the best ones. So okay, now I know I'll 0:20:19.756 --> 0:20:23.436 watch them. I'll watch them tonight. My favorite book about 0:20:23.436 --> 0:20:28.956 transportation is by John McPhee. It's called Uncommon Carriers, and 0:20:29.076 --> 0:20:30.956 it's a book about the people who do the work 0:20:31.036 --> 0:20:34.636 of freight hauling. He just writes so beautifully and with 0:20:34.676 --> 0:20:38.036 such dignity about the people who do this work and 0:20:38.116 --> 0:20:41.916 the incredibleness of the machines that get our T shirts 0:20:41.996 --> 0:20:45.436 and our popcorn to our houses, like whether it's the 0:20:45.516 --> 0:20:47.916 freight boats with the giant containers or the long contructs. 0:20:47.956 --> 0:20:50.636 That book. It gave me a sense of awe and 0:20:50.796 --> 0:20:54.076 respect for the sort of societal achievement that is our 0:20:54.116 --> 0:20:57.636 transportation system. And I think that's healthy if you're thinking 0:20:57.636 --> 0:21:01.276 about changing something. The Infrastructure Bill is not called the 0:21:01.316 --> 0:21:04.196 Infrastructure Bill, It's called the American Jobs Act. And I 0:21:04.236 --> 0:21:07.436 think it is very important, especially for technologists like me, 0:21:07.996 --> 0:21:10.436 that we don't just assume that our efficient approach and 0:21:10.476 --> 0:21:14.876 it is more efficient, is neutral like to society, and 0:21:14.916 --> 0:21:19.596 to think about these industries we're disrupting. Thank you so 0:21:19.676 --> 0:21:26.596 much for being with us, Laura, My pleasure. Laura Sewell 0:21:26.716 --> 0:21:29.756 is the CEO of street Light Data. Will include linkster 0:21:29.876 --> 0:21:32.876 suggestions on ways to learn more about transportation and data 0:21:32.876 --> 0:21:36.516 analytics in our show notes. Next time on Solvable, we're 0:21:36.516 --> 0:21:41.756 talking about sugar, salt, fat, all the good stuff and 0:21:42.116 --> 0:21:44.956 how to solve food addiction. But before you turn away 0:21:44.996 --> 0:21:47.916 feeling annoyed and clinging to a bag of delicious cheese puffs. 0:21:48.356 --> 0:21:52.396 Here's a little preview. The solution is not all on you. 0:21:53.196 --> 0:21:56.396 I hope you'll join us for that conversation. Solvable is 0:21:56.436 --> 0:22:00.516 produced by Joscelyn Frank, research by David Jack, booking by 0:22:00.556 --> 0:22:04.556 Lisa Dunn. Our managing producer is Sasha Matthias, and our 0:22:04.596 --> 0:22:09.436 executive producer is Mio Lobel. I'm Ronald Young Jr. Thanks 0:22:09.476 --> 0:22:09.956 for listening.