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Involve the Public in Data Collection for Better Results

Involve the Public in Data Collection for Better Results

PSPL methods take Gehl employees and partners into the streets to engage with members of the community about their city. (Gehl)

Principles for making cities smart—for the people in them.

What if the design and programming of public spaces could be informed by the needs of the local community—even including people typically excluded from traditional engagement processes? What if large data sets could be combined with fine-grained information about lived experience to make neighborhoods safer, cleaner, and healthier? What if city governments could partner with private entities to use residents’ data to make their lives better—rather than to sell them more products? The answers to these questions illustrate what a “people-first smart city” would look like. Unfortunately, across all the cities currently committed to being “smart,” I cannot point to a single example of one being smart for people.

I recently spoke with someone from a city government who excitedly told me how the city was partnering with a company that would use cell phone data to count the number of people in public spaces throughout the city. He told me this kind of measurement and tracking would enable advertisers to send targeted ads to people who opt in to use certain apps—for example, if you had just bought a coffee, the app could direct you to a nearby store to buy a doughnut.

I was astonished by this answer. Is this really the highest and best use of publicly collected data? Do I want my city to be gathering extensive and invasive amounts of data about me so that a third party can sell me a doughnut? When pressed about the privacy issue, he told me that the company assured him that the data was anonymized. (Hmm.) When I asked him if the company was considering any sort of community engagement about this project or even an announcement that they were doing it, he said no. (Yikes!)

This, to me, is a classic example of a trend that is quite prevalent: a desire for data (great!) without a clear public benefit (not great), and without thinking through the potential repercussions or hacks down the line (really bad).

As in many industries, the proliferation of technology solutions within real estate and the built environment has been transformative. I cannot open my email without seeing an announcement of a new proptech conference or a smart cities seminar. The opportunities to use big data to build better, faster, and more flexible cities are dizzyingly exciting, but also deeply concerning.

At Gehl, data is in our DNA. Our founder, Jan Gehl, started collecting data about how people use public space back in the 1960s. He used this understanding to inform design and to strategize for more public life such as enjoying the outdoors, people-watching, and safely crossing the street, and to counter poor urban environments that force people to run when crossing a street or to be sandwiched on narrow sidewalks.

To make visible these typically invisible behaviors, we developed a Public Space Public Life (PSPL) survey, which looks at the city from spatial and people perspectives. We map and measure these two elements over time, which allows us to see the relationship between space and life. This knowledge helps us make decisions about something as large as planning an entire city to something as small as planning a pocket park.

Having worked in more than 250 cities around the globe, we have collected an enormous data set that gives us insights into what makes cities work. Our methods helped former New York City mayor Michael Bloomberg and his administration incrementally test the pedestrianization of Times Square, which led to an entire redesign of this major public space.

This data set has also helped us work with smaller cities. In Nashville, for instance, we explained to business owners in the Lower Broadway neighborhood that, at night, they were experiencing pedestrian traffic patterns that rivaled those in Shanghai. This blew their minds and enabled bold decision-making about street improvements that will lead to a safer, more comfortable pedestrian experience in this vital economic area.

We love data. We know that leaders today—mayors, developers, and major companies—need data to make thoughtful decisions about the future of our cities. We know that good public spaces invite everybody. We know that understanding how public spaces function gives us the information needed to help them function better, and we know that you need to observe and measure to make this possible. We know that (in the words of Jan) “we measure what we care about,” and that organizations that measure are better at achieving their goals.

And we know there are new ways to capture this data. Back when Jan Gehl first developed the methods used in the PSPL survey, it was a data-rich but analog process involving people on the street with counters and clipboards. We are now working with companies such as SpringBoard and Numina to use sensors in the public realm to capture pedestrian and vehicular flow data. The data that public-realm sensors can gather is astounding.

Click to zoom: The CommuniSense app, a prototype of how to engage the public about data collection in the public realm. (Gehl & IDEO)

The Human Element

There are two points that I want to raise about this sort of big-data collection in the public realm. The first is a note of caution about these new tools and the accuracy of the data that they provide.

We know from our work that sensors alone cannot be the holy grail of understanding public life. It is only when you combine that data with the ethnographic data from being on the street that you get a truly representative and enhanced understanding of public life. If we rely on sensors alone, we are missing nuances in the data that give us important clues about what is actually happening in cities and neighborhoods. When we are on the street for our PSPL survey, we start to notice more than we are being asked to document.

Say you have a public square, with one corner that is rarely inhabited. A sensor will inform you that no one is there, but a human might notice other things. Perhaps a pile of smelly trash is always there during the day, or a neighbor plays loud music that makes it impossible to hold a conversation. These are the types of observations that make the human brain special—and uniquely qualified to be a judge of public life.

For this reason, we strongly advocate using both sensors and humans—relying on each for what it does best. Sensors can give a city a more detailed picture, but not necessarily the big picture.

The second point is that the need for data must be balanced with a thoughtful, engaged process in which we ask: What are we collecting and for what purpose? Are people—the source of our data—aware of and engaged in the collection process? Have they opted in? Do they have a say? Thanks to privacy rules such as the European Union’s General Data Protection Regulation (GDPR), every time I go to a website, I am informed that it is using cookies. But, does the same thing happen when you leave your home and step out into the street? Is the only way to opt out of the data-collection process to never leave your home?

Concern is increasing about privacy and data collection in all aspects of our lives. The New York Times, for example, has been running a series called “The Privacy Project,” which has covered deeply troubling data practices of the New York City Police Department, including having children as young as 11 in the department’s facial recognition database. There was a piece about how “anonymized” personally identifiable information (PII) that tracked people’s movements throughout the city could be quickly de-anonymized by reporters. There is growing awareness of how racial biases are built into data collection, and then exacerbated by the metrics and decision-making that follow.

The rising skepticism is legitimate. We should all be deeply troubled by this and questioning the companies offering these services, as well as the government agencies that fail to regulate them. 

It would be easy to say, “Ban all data collection! Remove all sensors and don’t let them back into our cities!” I understand that impulse, but I think it is misguided. The trick is ensuring that we don’t throw the baby out with the bathwater. Good actors need to stake their claim to data collection. If we do not, then the technology will evolve to simply be about marketing and advertising. I believe there is a strong role for regulators. There also is a real need for full-throated, open-armed, and open-hearted community engagement. One reason people are suspicious about data collection is that many of us did not (or still do not) realize how data could be monetized.

To take a non-public-realm example, everyone thought they were signing up for Facebook because it was a fun way to share photos and stay in touch with friends. Users did not understand that Facebook would use the data for marketing and other purposes. What would it look like if Facebook, governmental agencies, and all organizations that collected data about us were very open and obvious about what kind of data they are collecting and why they are collecting it? 

Many tech companies have promised us a frictionless future in which all one’s needs and desires are anticipated and seamlessly satisfied. We are seeing many examples of “disrupter” companies being challenged by the friction of government regulations and community pushback. This is a good thing because it will ensure that there is balance in deciding what our collective future looks like. Our move toward this frictionless future needs to hit some bumps along the way, and community engagement is precisely one of those useful impediments. We have found time and again in our work that a solution that is co-created with the community and responsive to actual needs is a stronger, more successful solution than one developed in a vacuum.

Collaborative Cities

At Gehl, we have been exploring this idea through a partnership with IDEO CoLab on the theme of collaborative cities. Through work with a number of private corporations, we know that the so-called smart city depends on intensive data collection that will allow the city to optimize many functions such as traffic, water management, and public safety. Without increased data literacy among the public, though, we risk losing overall support for these initiatives.

The question we asked ourselves at the beginning of a design sprint back in April was how we might increase public awareness of data collection in the public realm and engage people in a conversation about its utility. Our answer was to develop an art installation called Vanishing Point, which allows a person to visualize and compare how he or she appears within the data capture from different sources, including cameras, sensors, and cell phones. Vanishing Point also asked them to share feedback on how that visualization made them feel. We designed it this way because we wanted it to start a conversation about this process among members of the public.

In a second design sprint two months later, we pushed this idea further, building a prototype of an app that makes sensors placed in the public realm by city agencies visible on a map. Users can select a specific sensor and read about why it is there and precisely what it is measuring.

For example, say a city is trying to gauge whether it needs an additional crosswalk on a street with a high volume of cars and high instances of jaywalking. Using this tool, the city can announce the presence of the sensor, and users can “follow” certain projects. Residents can share their thoughts on the larger project and even sign up to be notified about the next public hearing on the issue.

There are already good examples of this type of open data collection in cities today. One example is the bicycle counters (cykelbarometer) in Copenhagen, which use a sensor line in the bike lanes to count each bike that passes by. A display shows the number of bicycles for the day and for the year. (Because Copenhagen is dedicated to being kind to cyclists, the cykelbarometer includes an air pump for bicycle tires.) This is a simple yet effective way to engage the public in data collection, and maybe even to generate excitement about it and pride in it.

From these projects, we developed a series of insights:

  • Make the technology understandable. The types of data gathered in the public realm are not well understood by the public. The language regarding data is not engaging or open to a layperson, making it easy for a person to get confused or upset about what is being gathered. For example, terminology such as edge and metadata needs to be clarified.
  • Define what “good” means to the public. Public and private entities are not being explicit about the reasons for collecting data, which leads to distrust and skepticism. If the data is used “for the public good,” then that “good” needs to be defined. In addition, connecting data collection to goals and projects makes conversations much more actionable and specific.
  • Proactively collaborate to avoid friction later. Companies and cities would benefit from getting ahead of a problem rather than facing the backlash later. Increased data literacy may limit data gathering and use, but it could also generate greater opportunities through collaboration. Increased understanding leads to increased participation.
  • Garner public support to harness the value of existing data. Companies (particularly energy companies) can tap into enormous amounts of data that could increase operational efficiency and cut costs, but they are not currently permitted to do so because of data privacy considerations. If companies could receive public permission through open engagement with the public on what they might use the data for and why, then all parties would benefit from the data being put to its best use.

From our conversations as part of this and other projects, we understand that it is seen as risky to be the first adopter of this type of public engagement work. Managers of public spaces are worried that drawing attention to the sensors they use would have only negative effects on them. That is why our next question is this: how can we remove the risk of being the first adopter? Increasingly, we are seeing cities such as San Francisco and Somerville, Massachusetts, prohibit certain technologies, such as facial recognition. Which cities will start the challenging—but ultimately rewarding—process of fully informing people about data collection and bringing them into the process?

If we as a society are committed to the idea of smart cities, we need to make sure we are asking “smart for what?” and “smart for whom?” I, for one, want to make sure that we are not making cities that are driven by technological possibility alone, but cities where people’s needs—for health, for safety, for happiness—are our number-one priority.

IBEN FALCONER is a director at Gehl in New York City, where she works as a strategist focusing on partnerships and investments for the firm’s Innovation Team.

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