Lily Maxwell, smart cities content writer for iomob.net, interviews Susan Shaheen PhD, a pioneer in future mobility strategies. She was among the first to observe, research, and write about changing dynamics in shared mobility and is an internationally recognized expert in mobility and the sharing economy.
As the “mother” of shared mobility and someone who is well-known for working in sustainable transportation – what inspired you to work in this field?
My desire to work professionally in environment and tech goes all the way back to high school. Sustainability, recycling and climate change were not so accepted back then and I clearly remember thinking: why does it have to be so hard to do the right thing?
So I went to college and took as many environmental classes that I could, before doing a masters in public policy where I specialised in the environment. Then I went to washington DC to “save the world”, but I quickly realised that I wasn’t even close to saving the world there and decided that I need a higher degree.
I wanted to figure out how we could better connect society, technology and policy, with the idea of finding alternatives that would be competitive with the existing options. It was at this point – when I decided do a PhD – that I moved towards transportation.
I was assessing doctoral programmes and advisors in order to choose the right one for me, and I met Dan Sperling. He was doing some cool stuff in transportation and we really clicked. When he talked to me about transportation, I considered that I hadn’t really thought about this field before, but I was still a little unsure about being so specific to transportation. So I tried out some classes – actually undergraduate classes – taught by his graduates.
And, there, I had my ‘a-ha’ moment: I thought to myself “this is it: this is the right application for what I want to do”. So I didn’t actually go into transportation until I started my PhD in 1993, but when I did, I knew it was the right thing.
You say that certain concepts that we hold to be true now – such as climate change – were not so mainstream when you were beginning your career. What gave you the tenacity to carry on working in this field even when you were going against the tide and not many people were onboard?
Honestly, it’s been a long road. I have only felt in the last 5 years or so that the concepts that I’ve been working on for the last 25 years have begun to be embraced in a mainstream and widespread way.
Ultimately, I think it’s really key that I have been motivated by the same principles since I was a teenager. I work with a lot of masters and phd students and I say to them, “find your passion, find that thing that you really connect to, because there are going to be days that are really hard, and you’re gonna feel like you’re alone sometimes, particularly when you pick up on ideas that are really cutting-edge”.
You have to have that deep feeling of conviction that what you’re doing is right: that’s what has gotten me through.
For someone of my age – a ‘millenial’ – living in Europe, environmentalism and sustainability are very much mainstream. It’s funny to imagine a time when they weren’t – but we forget that their acceptance is very recent – particularly in the US, where there continues to be climate-skepticism.
Yes, the mainstream acceptance is new. Nowadays, the NY times, the washington post, the european journals all talk about tech innovation and climate change regularly – the media contact me all the time.
For the first time I’m not telling them about it: they’re telling me about it. This role-reversal is fascinating: it used to be me saying “these transport innovations are real and they’re disrupting already and we need better policies and research and understanding”. Now I sit in meetings and government officials say to me, “we need research on this, we can’t implement without a better understanding of this phenomenon”. It’s wonderful that this is happening.
A lot of people compare the different sectors and say the public-sector is behind and slow, and the private-sector is the space of innovation. Obviously this is simplistic – but how do you think we can increase cooperation between different sectors in order to drive change? And is this the thing that will drive change?
I think this is already happening – the evolution in the relationships between academia, government and businesses is already happening and increasing in its pace. In the ‘80s, PPPs were still a bit of a stiff concept: the different sectors mechanically worked together. Now it’s becoming more of a continuum: one thing I talk about in some of my presentations is the blurring of the lines between what is private and what is public.
I think we’ve actually reached a stage where we’re all trying to understand this – governments in particular. I don’t agree with the idea that government is standing in the way of innovation. Government has certainly challenged some recent ideas, but in many cases, they’ve said “let’s do pilot programmes, let’s give you a year long agreement to do this or that”.
Now the US government is starting to stand back a bit and saying “we get this now, and we might put some caps on what you’re doing, but we’re still going to let you experiment”.
Approaches also vary depending on the city: some cities are more conservative, others more welcoming towards technology. But there is no doubt that technology will outrun public policy – what tech can do has gone beyond the traditional boundaries of public transport policy already. So it’ll be interesting to see how this plays out.
How do you feel about the smart cities concept? How do we ensure that “smart” or new technologies are actually beneficial to everyone in the city and are not just profit-driven?
When I started my PhD, I took a class on sustainability, where we tried for 10 weeks to define what it was. It was a big concept and people had a lot of hopes and dreams tied up in it. I think smart cities is the same: it’s one of those big terms that people put a lot of hope into and use when they’re writing a paper because then everyone will read it.
We have to be cautious of words like this, the “hot topic” words of the day. It’s not that we need get rid of these terms, but we need to reach deeper and work hard to define what they mean. With sustainability we did this fairly successfully with, for example, the Brundtland Report, through defining the 3 pillars of sustainability.
We haven’t done this fully yet with smart cities. What I’ve concluded from the last 5 years of working on this topic is that smart cities are the people who live in them. It’s not about big data, the internet of things etc. – it’s about people and connecting people with the life they want to lead.
Tech can play a big role in this, but if we don’t use it in the proper ways, and guard against any negative outcomes, it can lead to isolationism, to further divides between people of different economic backgrounds, races, and education and ability levels. Some might argue that tech is bringing about gentrification, making cities nicer and better but for the elite but driving out the people who have stayed in their cities through thick and thin.
Focusing on people and quality of life should, therefore, be the driver for defining what a smart city is. If we do this, we’ll be less likely to produce the unintended consequences that occur when we don’t think holistically, when we don’t consider possible policy ‘gaps’ or if we’re leaving someone behind.
You talk a lot about how shared mobility is dominated by certain groups – the socio-economically privileged, for example. How do you think we can diversify mobility and shared mobility, in particular?
We have a lot of work to do: the first step is to recognise that there are gaps that need to be filled. We developed a new framework called STEPS (Spatial, Temporal, Economic, Physiological and Social) about a year ago for assessing inclusion in mobility research. When you take this framework and you organize the research literature according to its matrix, it’s amazing where you see gaps – it guides you to say, “are we missing some of the data? Are we missing something in the questions we’re asking?”
For instance, we did our own survey a year ago aiming to study equity; we applied the steps framework to our data set and realised that even we, with our focus on equity, were not asking all of the right questions.
Crucially, we really need to think carefully about what we mean by equity. We need to consider that there are factors beyond the traditional low-income, education-level “heavy-hitters” that you see in a lot of research.
We need to look at spatial dimensions; for instance, when people are displaced from the city and have longer travel times, that’s an inequity that isn’t necessarily always considered. Then there’s temporal distribution. One of gaps we have found in San Francisco (when we were carrying out research there) were temporal gaps: late-night workers in the hotels and bars had few late-night transportation options. The ones they could access were sparse and often dangerous, with only 1 – 2 buses operating in the middle of the night.
Then there are cultural factors: some cultures may be less comfortable with sharing, for example. Lyft and Uber have been very successful at using social media to overcome these cultural barriers, but, even then, some people from certain cultures are not comfortable getting into cars with strangers.
Race is also something that I don’t think we’ve looked at enough. We’ve seen interesting dichotomies coming out here: for instance, areas are getting served spatially and temporally that were not served before by taxis, often with higher ethnic minority populations, but we also see studies coming out suggesting that people are being racially profiled on these apps.
If we go into an automated future, where we have machines and AI learning from the driver, racial prejudices might be entrenched so that if you have a foreign-sounding name, your ride request is automatically rejected.
So could adaptive policy mirror the way we’re collecting real-time data and constantly learning things and AI is becoming more. Do we need “real-time policy”?
We need dynamic policy. When we think about pricing, we talk about dynamic pricing all the time. The idea you don’t flat price – that your price reflects the economics of supply and demand – has been around for a very long time.
The question is: could our transport policies be more like this? Could they take on more dimensions than just congestion and make sure that for poor people, if we’re going to price more at this time of day, we’re subsidising or giving them more public transport options?
Big data may allow us to do this. Maybe now we have the ability to start carrying out much more sophisticated analysis, we can develop policies that are more nuanced because we have a more robust understanding of where a technology is unexpectedly helping over here, but having negative consequences at this particular time of day, for this specific demographic group, for example.
Policy can, therefore, become more robust and more dynamic because we can say, “ok we don’t need to regulate this late at night, but we do during the day; or maybe late at night we need additional safety and security policies in place instead of regulation”.
I also think the more dynamic you become, probably the more local you become too – so the more context-specific policy can be. A one-size-fits-all policy is no longer the way to go, and frameworks like STEP can really help us to make sure that we get this adaptive, inclusive policy making and research right.
You’ve had a big influence on the creation of iomob.net – do you think this kind of technology, facilitating decentralised, app-based urban transport, is the future of urban mobility?
In some places yes, in other places maybe not. For a long time I’ve talked about shared mobility apps as the holy grail of mobility and of the utopian vision of mobility as seamless and integrated, with one interface (as iomob does) for routing, booking, and payment.
Here, there’s no monopoly – the mobility vision is driven by the public good. But from working for 25 years in this space, it seems hard to imagine that one universal platform will come about. In some places – places like China perhaps – we will achieve that, but it likely that the reality in most cities will be a spectrum of different choices.
In some cases we’ll probably end up seeing platforms created and branded according to a specific image: this may appeal to a lot of people, just like high end cars appeal to people for their luxury and safety. Choice is good, so this isn’t necessarily a bad thing: as an ecologist, we fundamentally don’t want systems where there is no choice, because that isn’t sustainable.
In Europe a lot of people are talking about mobility as a service – this may ultimately end up in some kind of subscription package that’s largely driven by the public good and the desires of government and society. Will it definitely be achieved? I don’t know: we can only hope.
What does ultimately worry me is the potential inequities created by the new sharing technologies, which we’re not considering that much right now.
With autonomous vehicles, for example, what happens when you have some cars that are safer than others? What happens to people who can’t afford the safety? What happens when the vehicle has to decide who lives and who dies?
The question is: are we again creating inequities and unintended consequences with the systems we’re designing, even though we may start out with the public good as the driving force behind these things? All the work I’ve seen with car-sharing and decentralised mobility was genuinely motivated by social and environmental good but when you look at the data about the users, it still isn’t helping the people who could benefit from it. Despite the great public good “inherent” in the design of many new urban mobility concepts, most haven’t translated into true equity yet.
So the technology is nearly there, but we’re not?
Well we need to better define what questions we have to be asking during the design of shared mobility research and concepts. Things like: what kind of data do we need to be collecting to make sure that the machine learning isn’t taking something in a direction that we don’t want it to go? How do we guard against all of these unintended consequences in a tremendously data-driven, electronic and wireless world?
The wonderful thing is that there are many people out there, like Boyd Cohen, who are really driven by the public good. But all of us working in this space, trying to make mobility more equitable and decentralised and democratic, are fallible; for all our well-intentioned motivations, we could still be doing things that result in displacement, or producing the very inequities that we’re trying to guard against. That’s the thing that keeps me up at night – asking myself, “am I asking the right questions? Am I missing anything?”
Ultimately, we have to keep looking at the data and assessing which direction it’s going in; if it’s going somewhere we didn’t expect or don’t like, we have to know how to correct for that. It’s not going to be easy, but we just have to always think about the “gaps”; hopefully, through the STEPS framework and the work of iomob and others, we can continue to fill them in future.