As I sit in this session “Defining Smart City Governance — Architectures of Co-creation and Integration” hosted by Georgia Tech’s Serve Learn Sustain we discussed how to frame smart cities and connected communities. This session was apart of the Integrated Network for Social Sustainability 2017 Conference. We collaborated with live feeds from conference sites in Lima, Peru; Baltimore, Maryland; Atlanta, Georgia; and Charlotte, North Carolina. We are faced with the challenges of utilizing big data to build better communities but if were not careful the data can further marginalize frontline communities. How do we avoid system failure? How do we know the difference between good data and bad data? What is the objective of the data accumulation and who owns the data and has access to it? The “machines”, all these millions of sensors connected to the internet of things are monitoring everything from our movement in the cities, the impacts of climate change to geosurveillance. The data gathered from the machines present outcomes to decision makers who often are driven by economic outcomes not human outcomes.
We live, work and play in cities that are ever increasingly driven by data. The Internet of things and the millions of sensors connected in a network across systems in our cities is how we measure how “Smart” a city can be. It reminds me of the movie the Matrix where the machines monitored and controlled human existence, the system relentlessly sought efficiency. The machines and sensors and the aggregation of data is how they see people they don’t see the humanity. Sadly the system does not properly compute the human quotient. This is problematic because humans are “wired” to react to stimuli often in emotional ways. Police brutality, lead poisoning, climate change are stimuli we have a emotional reaction to but the leadership in our cities look to the “machines” to give them cold emotionless data to address our needs. We have to reconcile the need for economic gains and efficiency and the gains that humanity receives from this modernization.
EQUITY, DATA AND SMART CITIES
We have to look holistically at how data can be used systematically to create outcomes that can be detrimental to different stakeholders. One example is the issue of the wealth gap between black families and white families in America in these cities. In 2009, the median black family’s net worth was one tenth of the median white family’s, resulting in a wealth gap of $236,500 (Shapiro 2013). As we deal with computing equity in our smart cites one must consider home ownership and home values. Do housing values drop when black families move in? How will the decision makers look at this data? Will this lead to less investment in a community because the property values are down? The data may suggest a property value depressed area needs community revitalization but that often creates gentrification which in turn increases the property values for the new residents but how was equity addressed?
“the market penalizes integration: the higher the percentage of blacks in the neighborhood, the less the home is worth, even when researchers control for age, social class, household structure and geography.” Dorothy Brown, Professor of Tax Law Emory University
How does the data compute for long time systemic racism? Understanding how to offset inherent system bias will be critical to creating equity in smart cities. When we implement geosurveillance systems what communities and populations will to subject to the kinds of monitoring that leads to more interaction with the police? For instance if the sensors pick up a gunshot in a part of town that has historical data for high crime will the data sway the interaction the police have with the citizens?
“Continuous geosurveillance relies on the production of spatial big data, and in particular the notion of the “smart city” takes center stage, that is, urban landscapes that can be monitored, managed and regulated in real-time using ICT infrastructure and ubiquitous computing. Such instrumented cities are promoted as providing enhanced and more efficient and effective city services, ensuring safety and security, and providing resilience to economic and environmental shocks, but they also seriously infringe upon citizen’s privacy and are being used to profile and socially sort people, enact forms of anticipatory governance, and enable control creep, that is re-appropriation for uses beyond their initial design.” – Rob Kitchen
Will there be an over dependence on data with real time ubiquitous computing systems? There is an argument being made in the sports world today about the use of analytics to predict performance but old school players say the machines cannot measure human emotion. Will the superstar player shrink under pressure or rise to the occasion and sink the big shot. The machines cannot measure the “heart” of a player like Michael Jordan who may have a terrible shooting night and then all of the sudden score the last 10 points to win the game.
If we are serious about creating equity in our smart cities then we must allow input from all stakeholders. We must include the input of traditionally marginalized and frontline communities. We have to make the data accessible for everyone. How will grassroots organizations and everyday citizens be able to digest and leverage the data to be able to give input to the system? For example during COP 21 and the subsequent Paris Agreement leaders decided on 2.0 Celsius as the maximum global rise in temperature based on the data. Yet the same data to citizens that represent frontline communities advocate for 1.5 degree temperature rise because a 2.0 rise has catastrophic effects on countries in the Caribbean.
“for us in small island developing states, climate change requires a redirection of development towards resilience and sustainability in the face of increasing temperatures, more extreme meteorological events, sea level rise, biodiversity loss and the progressive disappearance of critical potable water resources.” – Minister of State for the Environment Simon
The end results was that equity prevailed and small island nations and developing nations were able have 1.5 degrees as the new target. This is an excellent example of how stakeholder engagement should operate in Smart Cities. During the Paris Accord small countries that do not have economic or political clout but still had their voice heard and got their inputs to the system addressed. If we’re to create smart equitable cities we must commit to holistic evaluation and application of the data so that all community stakeholders have input and get their needs addressed. Sustainable Development cannot be done in a vacuum or focused on aspirational projects like autonomous vehicles. Smart cities are about connectivity and access but what happens when more machines are connected than people? Over half of working class families in America are disconnected. Smart Cities will have to commit to addressing the digital divide.
“Disparities in health, education, and employment are exacerbated by lack of access to online resources.” – James Walker, Founder CEO of Informative Technologies.
Equity must be at the core of Smart Cites and Sustainable Development that provides access and connectivity for all social economic groups. Big data is not inherently bad but we must make sure the data serves the needs of all stakeholders and not exclude or further marginalize stakeholders in our communities. When communities have access to the data they can properly voice their needs and can move towards policy change through legislation that benefit the communities.