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Big Data and AI in Local Government

The views expressed are those of the author and do not necessarily reflect the views of ASPA as an organization.

By Matthew Teal
January 11, 2019

Local governments must radically improve their efficiency if they are to survive and successfully balance between the National Academy of Public Administration’s four pillars of public administration: economy, effectiveness, efficiency and social equity. Declining funding for government in the face of a growing list of needs, the “silver tsunami” of experienced government leaders retiring, and the decline of new public administrators entering the field will force local governments to confront the limits of the current system more quickly than most realize.

In order to meet these challenges, local governments must rapidly develop the technical capacity to utilize Big Data and Artificial Intelligence (AI). This use of advanced analytics will inform local government policymakers and empower local government leaders to make proactive, data‑informed decisions.

Governments at all levels have seen declining funding levels since the Great Recession of 2007‑2008. Tax cuts, made in the name of stimulating the economy, have only exacerbated this problem. For example, in a June 2018 report titled “The Distributional Impact of the Tax Cuts and Jobs Act over the Next Decade,” Huaqun Li and Kyle Pomerleau at the nonpartisan Tax Foundation estimated that the recent “Tax Cuts and Jobs Act” (TCJA) will reduce “federal revenues by about $1.8 trillion on a conventional basis,” even while growing the economy to “about 2.8 percent larger than it otherwise would have been in the absence of the TCJA.”

Governments are also losing some of their most experienced leaders while trying to deal with the revenue crunch. In May 2018, the Center for State and Local Government Excellence survey “State and Local Government Workforce: 2018 Data and 10 Year Trends,” found that “44 percent [of state and local governments] report that retirements in the most recently completed year were higher than the year before, and the share of retirement eligible employees postponing their retirement date has fallen by more than half since 2009 (from 44 to 21 percent).”

This loss is exacerbated by flatlining enrollment in “public service” degree areas. In a May 2017 article for Governing entitled “Fewer People Are Getting Degrees in Public Service,” Mike Maciag wrote that “several of the top government-related academic fields – including criminal justice, political science and public administration – have seen the number of degrees awarded level off or dip slightly over the past few years.”

This article is the first in a series that will examine the roll Big Data and AI can play in improving local government management and ensuring the field’s continuing relevancy in an era of declining revenue and fewer skilled public administrators. These articles will discuss numerous potential use cases for back-office and citizen-facing operational reform, as well as the various technologies needed to make the reforms happen. The articles will also outline the potential risks of using such technologies and recommend steps to mitigate those risks.

First, what do we mean when we say, “Big Data?” In his book Business Intelligence Strategy and Big Data Analytics, Steve Williams defines “Big Data” as “large amounts of rapidly generated pictures, video clips, location (geospatial) data, sensor data, text messages, document images, web logs, and machine data traditionally captured and used by social media and internet-based businesses and more recently being leveraged by early adopter mainstream businesses.” As Williams notes, Big Data differs from traditional data in three important ways: data volume, data velocity, and data variety. As hard drive storage costs have plummeted over the past 10 years, the amount of data (volume) that can be stored cheaply and easily has skyrocketed. At the same time, the rate at which data that is being generated (velocity) is growing exponentially. Williams cites the example of a utility company with 700,000 customers that, in the past, would have gotten 700,000 meter readings per month. Now, thanks to smart meters, that same utility company can get 700,000 meter readings per minute. Finally, the types of data (variety) being generated are evolving. Social media tweets, tags, and likes; drone and police bodycam footage; text messages; and computer data such as those smart meter readings are all forms of data that in many cases did not exist 20 or even 10 years ago.

If that is Big Data, what then is “AI?” In a December 2018 webinar entitled “The Impact of AI in the Workplace and Beyond,” Gartner Research Vice President and Distinguished Analyst Whit Andrews states that AI is a computer program that “emulates human performance, typically by learning; comes to its own conclusions; understands complex content; engages in natural dialogs with people; enhances human cognitive performance; [and can replace] people in execution of nonroutine tasks.” Andrews states that Gartner Research’s “super short” definition of AI is “classify and predict – (faster, more variously and in greater volume than humans can without AI).” In other words, AI finds patterns in Big Data and generates predictions based on those patterns. Critically, AI programs can learn from their mistakes and continue to refine their predictions without the assistance of humans. This ability to learn and correct predictions without human assistance differentiates AI from previous generations of “predictive analytics” software programs.

The development of Big Data and AI presents an opportunity for local governments to become more proactive by using AI-generated insights and predictions to inform day-to-day operations. The shift to more proactive operations is critical to improving operational efficiency in the face of declining revenues and the number of skilled local government administrators. The next several articles in this series will discuss specific use cases, associated risks, and steps to mitigate those risks for Big Data and AI in local government.

Author: Matthew Teal, MA, MPA; Policy Analyst; University of North Carolina at Chapel Hill; Email: [email protected]; Twitter: @mwteal

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