How can we better solve public problems with data?
by Alba Alsina Maqueda
From problems to challenges
“Managing rapid change is a key preoccupation of the early twenty-first century” – (R. Burdett, P.Rode and M.Groth, Shaping cities in an Urban Age)
Urban Age describes the current world with more than half of the population living in cities, which occupy less than 1% of the Earth’s territory1. It is the result of an unprecedented growth between 1990 and 20152, and only an intermediate stage to the forecasts that by 2050 70% of the population will live in urban environments3. These extremely rapid processes of growth and urbanization are shaped by heterogeneous societies where even minorities comprise large numbers of people4.
The intrinsic complexity of the problems that we are and will be facing in the near future has to do with the speed at which changes occur and the interdependence of the layers that interact in our globalized and digitized territories. Indeed, “every wicked problem can be considered to be a symptom of another problem”5. The challenge of new public governance is to apply responsive management models to guarantee the resilience of our territories.
From data to information
“We have this condition where digital technology is becoming increasingly smaller and distributed in the environment. In a certain sense, this is the first time ever we can describe a city in real time.” – (Carlo Ratti)
In 1854, in the midst of a serious cholera epidemic in London, Dr. John Snow drew up by hand a map that would show the potential that underlies the union of data and cartography as a management tool: by placing the cholera cases on the fabric and urban infrastructure he was able to discover that pumps were the origin of the disease. 166 years later, data is generated at the speed of 1.7MB per second per person6. The disruptive power of digital technologies allows it to be stored, correlated and interpreted. However, only if governments implement management tools and processes to access the data and constantly monitor and understand the information behind it, they will be able to formulate solutions and strategies to tackle their main challenges.
From monitoring to prevention
“If you cannot measure it, you cannot improve it.” – (Lord Kelvin)
Urban Data Science has the potential to accurately frame and describe problems, extracting the most relevant information as well as testing and verifying their origins. At the same time, it can also help anticipate emerging problems. In this sense, real-time and geolocated data monitoring over time makes it possible not only to gather empirical evidence to better understand problems but also to implement artificial intelligence and machine learning to prevent future risks. This certainly emerges as a key strategy for the public sector who needs deep understanding of complex situations at the problem definition stage to be able to propose effective solutions. To illustrate this, I will present three successfully implemented approaches:
Damp Homes is a community-led solution from The Bristol Approach7 to tackle damp, a problem affecting over 30% of homes in Bristol. Through a frog-cased sensor, co-designed and programmed by different actors such as university researchers, businesses, hackers, data specialists, artists and others, the affected renters were able to demonstrate with data the scale of the problem and bring evidence to challenge negligent landlords and lead to policy change.
The Making Sense Toolkit 8 is an initiative to empower citizens to tackle environmental pollution through digital sensing and mapping. By using the Smart Citizen Kit9, the community of the Plaça del Sol10 campaign in Barcelona was able to demonstrate through empirical data evidence the noise pollution they are exposed to on a daily basis and ask for a local government response.
Inform@Risk11 is a low-cost early-warning system based on geosensors to alert landslide risks and prevent their fatal outcomes. It targets approximately 100,000 people of Medellin that live in endangered areas due to uncontrolled urbanisation and climate change effects. Developed by a German-Colombian research group and the community of the informal settlements of the city, it demonstrates how technology-oriented and data-driven strategies can help mitigate major public problems.
These three examples have a problem in common – be it humidity, excess noise or danger of landslides – where the affected population has managed to reverse their situation, when not mitigating the excess risk, thanks to the implementation of technologies for data collection and visualization. With no doubt, the disruption of the digital sphere and the availability of data provides a wide range of opportunities for diagnosis, prediction, performance monitoring, design simulation and outcome forecast to make urban scenarios more integrated, secure, fair and adaptable. Indeed, climate action, gender equality, human rights, peace and security and governance and ethics are only some of the priorities of the 2020-22 United Nations Data Strategy for a long-term transformation to achieve that “everyone, everywhere nurtures data as a strategic asset for insight, impact and integrity”12.
Alba Alsina Maqueda a Master’s Candidate for the Class of 2021 at NYU’s Center for Urban Science and Progress.
(2) Shaping Cities in an urban age. London School of Economics and Alfred Herrhausen Gesellschaft
(4) (Rittel & webber, 1973) Dilemmas in a General Theory of Planning
(5) (Rittel & webber, 1973) Dilemmas in a General Theory of Planning