Lily Maxwell, smart cities content writer for iomob.net, interviews Susan Shaheen Ph.D., a pioneer in future mobility strategies. She was among the first to observe, research, and write about changing dynamics in shared mobility and the likely scenarios through which automated vehicles will gain prominence. She 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 the area of the environment and technology goes back to high school. Sustainability, recycling, and climate change were not as popularized back then, and I clearly remember thinking: why does it have to be so hard for people do the right thing and support the environment in their choices?
When I went to college, I took as many environmental classes as I could, before completing a master’s degree in public policy, where I specialized in environmental policy. Then I went to Washington DC to “save the world”, but I soon realized that I wasn’t even close to saving the world from a policy perspective. So I decided that I need a higher degree and came to California.
I wanted to connect society, technology, and policy in my research, fostering the idea of developing alternatives that would be competitive with existing options. It was at this point — when I pursued a Ph.D. — that I focused on transportation.
In selecting a doctoral program, I looked for environmental programmes and advisors that were the right fit for me. During this process, I met Professor Dan Sperling at the University of California, Davis. He was doing some interesting work in alternative fuels in transportation.
At UC Davis, I had my ‘a-ha’ moment: I thought to myself “transportation is the right application for what I want to do”. So, I didn’t focus on the energy and environmental impacts of transportation until I started my Ph.D. in 1993.
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 5–7 years that the concepts that I’ve been working on for the last 20 years have started to be embraced in more of a mainstream and widespread way.
Ultimately, I have been motivated by the same principles since I was a teenager. It is important to “find your passion”, because there are going to be days that are really hard, and you might feel like you’re isolated sometimes, particularly when you are focusing on cutting-edge ideas.
It is important to have a deep feeling of conviction: that’s what has gotten me through all these years.
For someone of my age — a ‘millennial’ — who is living in Europe, environmentalism and sustainability are very much mainstream concepts. 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, this mainstream acceptance is new. Nowadays, the NY Times, the Washington Post, and many other media outlets all talk about tech innovation and climate change regularly — the media contact me frequently, which is an honor.
Today, I’m no longer telling the media about innovative mobility: they’re telling me about it. This role-reversal is fascinating: it used to be me saying “these transport innovations are real, and we need better policies and research 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 occurring.
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 taking place and increasing in pace. In the ’90s, public-private partnerships were an emerging concept: the different sectors worked together a bit more mechanically. Now it’s becoming more of a continuum. There is now a blurring of the lines between what is private and what is public.
I think we’ve reached a stage where we’re all trying to understand what is public and what is private in terms of mobility services — governments in particular. The government has certainly challenged some innovations, but in many cases, they’ve said: “let’s do pilot programmes, let’s explore a year-long pilot to experiment”.
Approaches also vary depending on the city: some cities are more conservative, others more welcoming to innovation. There is no doubt that technology has outpaced public policy. 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 Ph.D., 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 to it. I think smart cities is similar: it’s one of those big terms that people put a lot of hope into.
We have to be cautious of words like this, the “hot topic” words of the day. We need to reach deeper and work hard to define what they mean. With sustainability, we did this fairly successfully, for example, with the Brundtland Report, in 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 so much about big data, the internet of things — it’s more about people and connecting them with the lives they want to live.
Tech can play a big role in this, but if we don’t use it in helpful ways, and guard against any negative outcomes, it can lead to isolationism, to further divides between people of different economic backgrounds, races, education, and ability levels. Some might argue that tech is bringing about gentrification, making cities nicer and better for the elite but driving out the people who have stayed in their cities despite suburbanization.
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 face the unintended consequences that occur when we don’t think more holistically, when we don’t consider possible policy ‘gaps’ or if we’re leaving vulnerable groups 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 recognize that there are gaps that need to be filled. We developed a new framework called STEPS (Spatial, Temporal, Economic, Physiological and Social) in partnership with the US Department of Transportation about a year ago for assessing inclusion in mobility research. When you apply this framework, it can help you to identify any gaps — it guides one to ask: “are we missing key metrics and data? Are we missing something in the questions we’re asking?”
Furthermore, 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 are temporal effects. One of the notable gaps we identified in San Francisco (when we were conducting our smart cities work) 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 sharing a vehicle with a stranger, for example. Lyft and Uber have been very successful at using social media to overcome these cultural barriers, but some people still have concerns that stem from their cultures.
Race is also something that I don’t think we’ve looked at enough. We’ve seen interesting dichotomies in some of the recent research: for instance, some areas are getting served better that were less well served by taxis, but we also see studies suggesting that people can be racially profiled on apps.
If we enter an automated future, where we have machine learning and artificial intelligence learning from the driver, racial prejudices could get embedded into the algorithms.
So could adaptive policy mirror the way we (and machines) are constantly collecting and learning from real-time data? Do we need “real-time policy”?
We need dynamic policy. When we think about pricing, we often talk about dynamic pricing. The idea is that your price reflects the economics of supply and demand. This concept has been around for a very long time.
The question is: could our transport policies be more dynamic in terms of location and time? Could our policies take on more dimensions than just congestion and include equity, for instance?
Big data may allow us to do this. Today, we have the ability to conduct more sophisticated analysis, so we should be able to develop policies that are more nuanced. Policy can become more robust and more dynamic. For instance, we may decide that we do not need to limit the operations of private transportation services late at night, but we need to in dense areas at more congested times”. A one-size-fits-all policy may be too blunt. Frameworks like STEP can help us to develop more adaptive and inclusive policies.
You’ve had a big influence on the creation of iomob — do you think this kind of technology, facilitating decentralized, app-based urban transport, is the future of urban mobility?
In some places yes, in other places maybe not. For a long time, we’ve talked about shared mobility apps as the “holy grail” of mobility or the utopian vision of mobility as seamless and integrated, with one interface (as iomob does) for routing, booking, and payment.
With iomob, there’s no monopoly — the mobility vision is driven by the public good. It seems hard to imagine that one universal platform can be achieved — with all competitors under the same roof. In some places — like China or Europe perhaps — we can implement this. But, it is likely that there will be a spectrum of different choices in many cities.
We may see platforms created and branded according to a brand or 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 long as equitable options are also available.
In Europe a lot of people are talking about mobility as a service — this may ultimately culminate in subscription packages that are driven by the public good.
What troubles me is the potential inequities created by innovative technologies, which we’re not considering that much right now.
With automated vehicles, for example, what happens when you have some cars that are safer than others? What happens to the people who can’t afford safety? What happens when the automated vehicle has to decide who lives and who dies?
Again, are we 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? Despite the public good “inherent” in the design of many innovative mobility concepts, many have not achieved equivalent access.
So the technology is nearly there, but we’re not?
We need to better define what questions we should ask in designing shared mobility innovations and research. What kind of data do we need to collect to ensure that machine learning does not take us in a direction that we don’t want it to go? How do we guard against unintended consequences in a data-driven, electronic and wireless world?
There are wonderful people working in this space, like Boyd Cohen, who are deeply driven by the public good and fostering iomob.
Ultimately, we have to keep looking at the data and assessing which direction things are going in. Are innovations and policies taking us in a direction we didn’t expect or don’t like? Data and research can help us assess impacts. It’s not going to be easy, but we have to think about the “gaps” and unintended consequences as we envision the future of mobility.