Columns

XXVI.1 January - February 2019
Page: 22
Digital Citation

Fair fares and the digital divide


Authors:
Jonathan Bean

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As middle-class life becomes increasingly saturated with information technology, our collective expectations of what constitutes a normal existence continue to shift. Five years ago, only sports fans, crazy people, and those with strong political beliefs yelled at their radios. Now many homes have smart speakers—exactly how many, we do not know, in part because of the lack of transparency from Amazon, Apple, and Google. These companies have little incentive to disclose sales figures and every reason to create the expectation that talking to the Internet is, and should be, a routine part of life.

In my own home, the past year has brought an additional smart speaker that allows me to fulfill the essential life function of talking to the Internet in the shower. The house has also acquired a WiFi-equipped thermostat and a few other connected odds and ends, which precipitated the purchase of a new and more powerful router. I made my unease with IoT lighting clear in my last column, but it’s likely there are a few WiFi switches, outlets, and light bulbs in my future. And my home—at least in comparison with those of many friends and colleagues—seems thoroughly normal, if not a bit behind the times. In addition to smart speakers, it’s not unusual at all for televisions, thermostats, garage-door openers, and light bulbs to be online, even in a modest house. The Internet of Things is no longer just for nerds.

What got my attention is not the alarming creep of devices capable of watching, listening, and recording me in the most private realms of my own home, but rather the concomitant deluge of assumptions about a future where technology is ubiquitous. For those charged with implementing the future, including our planners, government officials, and employees at tech companies with valuations that exceed the GDP of some industrialized nations, the saturation of domestic technology makes it easy to imagine a brave new future revolving around the smartphone, smart speaker, and other forms of Internet-based AI. And in many places beyond our homes, that future is already here. In the city where I live, it’s not possible to pay for a ride on the streetcar without a credit card or smartphone. The assumption that everyone is connected also extends to the municipal agency responsible for waste collection. Citing concerns about the environmental cost of the printed doorknob flyers that alerted citizens about special pickup days for yard waste and bulky items, officials recently announced the printed flyers would be discontinued in favor of some to-be-determined technological solution. Never mind that those door flyers usually ended up in a useful place—on the fridge, where they served as a visible reminder to a household that it’s time to tidy up the yard. Or that barriers imposed by technology, economics, or language will likely mean the new communications reach fewer residents. Elsewhere, cities are using taxpayer dollars to develop Alexa skills with the expectation that residents will be able to simply ask their smart speaker about trash or recycling collection, alternate-side parking, or other routine tasks, freeing up city staff to take on other duties (if the staff aren’t simply laid off).

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Is this fair? Putting aside the question of what happens to the displaced labor, it’s worth thinking through the systematic effects of all of this automation. Think about the last time you encountered a customer-service phone system that insisted on identifying the reason for your call before connecting you to a real live human being—ostensibly so that the system can get you to someone with the skills, knowledge, and access to solve your problem. This process makes absolute sense when viewed as a wireframe, flowchart, or PowerPoint slide, with comforting statistics such as “98 percent of customers are able to find their own answers to their questions.” But that 98 percent, of course, reflects only the percentage with the patience and tenacity to navigate the system, while conveniently overlooking those who hang up in frustration. Older adults and those with limited hearing, speaking, or vision abilities are also removed from the equation.

Transportation researchers are wrestling with the equity implications of the expectation that we’ll all be connected as well. This is because there’s a huge question of equity in public transportation specifically and transit policy more broadly that screams out for the capabilities of smartphones. This conundrum is at the heart of a recent call for research proposals from the National Institute for Transportation and Communities, and it’s worth thinking about as the Internet of Things and technology in general continue to transform our built environment. For example, one issue is that public transportation, like most other things related to settlement patterns, functions far more efficiently at higher densities. Density makes things like subways, frequent service, and dedicated lanes for bus rapid transit practical. One of the best ways to encourage density is to charge people more money for traveling longer distances. To some degree this disincentive is built into the cost of car travel; choose a longer commute and you’ll pay more in gas and insurance. But it’s been long established that the problematic flat fare is the norm for most urban public transportation systems in the U.S. [1]. Since it’s usually less expensive to live farther from the city center, a flat fare creates an economic incentive for people to move farther away. This means the transport provider must transport more people over longer distances while generating no additional fare revenue—and you don’t need an MBA to know that’s not an appealing business model. Furthermore, flat fares tend to decrease the capacity of transit systems at peak hours because the same seat that could serve two or three short-haul passengers is occupied by one heading all the way out to the last stop on the line.

Distance-based fares are one answer to these interconnected problems; many systems in Europe and Asia operate on this principle. But as tourists can attest, these can be confusing when they operate with paper-based ticket systems because they require the user to consult a confusing matrix when traveling from one outer zone to another: If I’m going from zone 6 to zone 3, but passing through zone 1, do I need a three-zone or a six-zone ticket? This usability problem is simple to solve with the graphical interface of a smartphone. Furthermore, smartphone-based fare systems could open up a world of possibilities, such as the type of dynamic pricing made familiar by Lyft and Uber, which could in turn help distribute demand, reduce congestion, and increase capacity. Transit-agency smartphone apps could also gather data about what transportation researchers refer to as the last-mile problem, by identifying areas where people have a hard time getting from the transit stop to their destination. More data surely could help inform planners and reallocate resources so that more people would benefit from public transit. But what about gathering data on people who don’t own a smartphone? Or those who own a smartphone but who have an income situation that results in gaps in their pay-as-you go data plans? Or people who don’t bother to install a data-harvesting transit app because they don’t have a credit card or bank account to link for payment, or because their phone is too old or too full? Or who won’t trust a smartphone app with their credit card number [2]? These are otherwise invisible groups of people overlooked when we throw around statistics about smartphone ownership. The people most likely to be underrepresented in the data are the most vulnerable—but they are the very same people who stand to gain the most from increased access to public transportation. From an equity standpoint, they are the ones society should be investing in. But if the data that should form the basis for the decision can’t be gathered, then there’s no way to make an equitable decision.

There are positive examples of smartphone technology helping the blind, for example [3]. And the jury is still out on the cumulative effect of the widespread adoption of information and communication technology on transit [4]. It’s tempting to add dynamic smartphone data to the comparatively static data that has been the focus of previous efforts to optimize transit-network design [5], in an effort to improve the user experience for middle-class customers of public transportation systems. But this could have the effect of reducing the relative amount of data we have on working-class customers. This data gap is a problem in many other contexts, and an especially troubling one because it could have the tendency to accelerate the widening gap in equity. Relying on smartphone data raises the same potential issues of invisibility as the AI call-sorting system. It’s easy to believe the world you know—and to collect data that reinforces these beliefs. It is considerably more difficult to collect data about that which is not familiar.

This brings me back to the connected speaker on my bathroom counter. Never before have my expectations of what the world around me can do shifted so quickly. For those of us in the middle class, it’s easy to think of a hyper-connected world as the new normal. But it’s not. It’s important to remember that many in the U.S., and most in the world, do not enjoy the same uninterrupted access to a steady stream of income nor the constant connectivity that money enables. As we strive to make life more convenient, enjoyable, and productive for those so privileged, we should make sure that we are not pulling the plug on our less-fortunate neighbors.

back to top  References

1. Cervero, R. Flat versus differentiated transit pricing: What’s a fair fare? Transportation 10, 3 (Sept. 1981), 211–232.

2. Shirgaokar, M. Expanding seniors’ mobility through phone apps: Potential responses from the private and public sectors. Journal of Planning Education and Research (Apr. 2018).

3. Campbell, M., Bennett, C., Bonnar, C., and Borning, A. Where’s my bus stop? Supporting independence of blind transit riders with StopInfo. Proc. of the 16th International ACM SIGACCESS Conference on Computers & Accessibility. ACM, New York, 2014, 11–18.

4. Shaheen, S. and Cohen, A. Is it time for a public transit renaissance? Navigating travel behavior, technology, and business model shifts in a brave new world. Journal of Public Transportation 21, 1 (Jan. 2018).

5. Ram, S., Wang, Y., Currim, F., Dong, F., Dantas, E., and Sabóia, L.A. SMARTBUS: A web application for smart urban mobility and transportation. Proc. of the 25th International Conference Companion on World Wide Web. ACM, New York, 363–368.

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Jonathan Bean is assistant professor of architecture, sustainable built environments, and marketing at the University of Arizona. He researches domestic consumption, technology, and taste. j.bean@arizona.edu

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The Digital Library is published by the Association for Computing Machinery. Copyright © 2019 ACM, Inc.

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