Civic Analytics

Analytical and data-driven decision-making represent a significant opportunity to revolutionize the efficient and equitable delivery of services and policy innovations in city government. As resources tighten and citizen expectations continue to increase, the application of improved data collection methods, new analytical tools, and better cross-sector integration is becoming the foundation for next-generation city management.  At the same time, predictive models and machine learning have the potential to exacerbate bias and discrimination and reinforce existing inequities, while the persistent surveillance associated with “smart” city technologies has created a crisis of privacy and autonomy in the public realm.

The Civic Analytics program works directly with city agencies and non-profit organizations to acquire, analyze, and derive insight from data in order to solve tangible and significant problems of city management, policy, and planning. We conduct rigorous, problem-oriented research that serves the dual purpose to advance our scientific understanding of cities and have a direct impact on public sector decision-making. We confront the computational, economic, and political challenges faced by city agencies in extracting actionable knowledge from data to achieve measurable social impact. Our goals are to bring evidence to policy-making, to democratize knowledge through information transparency, and to analyze and address the root causes and disparate impact of discrimination and bias in urban data science.

To support lasting results, we strive to build analytical capacity within our partner organizations and bring together a diverse team with subject matter experts working alongside our urban planners, data scientists, engineers, and mathematicians.

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/ Mar 31,2020

Mandatory Building Energy Audits Alone

are Insufficient to Meet Climate Goals 

by Constantine Kontokosta, Sokratis Papadopoulos, Danielle Spiegel-Feld
more on: emissions, energy

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/ Jul 13,2020

Working 9 to 5?

Measuring Hyperlocal Worker Productivity with Public WiFi Network Data

more on: data, employment

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Leader: Constantine Kontokosta