Opportunities for AI for Federal, Public Sector & Nonprofits

Traditionally, the public sector has lagged behind private industry when it comes to technological advancement, and data science (including machine learning and - by extension - deep learning and AI) has been no exception.

As data science technologies shift from novelty to necessity, more governments have started to pour  resources into developing these capabilities. And it makes sense – the public sector is brimming with potential when it comes to applying machine learning-based techniques, with the potential for agencies to more effectively serve their citizens in critical areas like health, safety, housing, public services (including education), defense, and justice.

High-Value Use Cases

Providing better social services: The sheer amount of data at the fingertips of entities in the public sector means that in addition to improving existing services, data science can be used to provide new services and new opportunities to better forward their missions and benefit their citizens.

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Heightened safety: Whether it’s insider threat detection, counter-intelligence, cyber security, disease monitoring or detection/spread of hazardous materials, machine learning supports humans in the combination of massive and varied data sources to find outliers – that would likely go undetected by humans – to identify or predict threats to safety, whether physical or virtual.

“In September 2016, the National Institute of Justice launched a Real-Time Crime Forecasting Challenge to predict crime hotspots in the city of Portland, Oregon. Our team made a submission to the challenge. Our goal was to use both geospatial and temporal data to understand underlying factors of crime and predict future hotspots. All of the data are open source, making the project fully reproducible. And in the end, we are very excited to have been announced as one of the winners of the challenge!”

-Jorie Koster-Hale, Lead Data Scientist at Dataiku; read more in Data from the Trenches

 

Fraud detection: Advanced, machine learning- and AI-based fraud detection has revolutionized the financial services industries, and it has the potential to do the same in the public sector. From tax fraud to social services fraud and everything in between, combining massive datasets from across different sources allows for more accurate (and less costly) fraud identification.

 

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Smarter resource allocation (operational efficiency): When there are limited resources, there is always the question: where (and how) to apply them? From allocating border patrol or police forces to performing inspections to deploying street maintenance crew, machine learning and predictive analytics can take any number of data sources and restrictions into account to analyze all factors (even those that a human wouldn’t necessarily consider) for the best possible allocation of those resources.

More accurate economic projections and better revenue management: Private industry has been using data science for years to provide more accurate forecasting. Subtle trends in data can allow for machine learning-based predictions that more accurately capture shifts that could go undetected by a human’s analysis.

More effective city planning: With the internet of things (IoT), local governments have opportunities to improve the layout and flow (including traffic) of cities or larger regions overall, analyzing the massive quantities of data from sensors to make more informed decisions for the future.

 

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Challenges

The public sector faces increasing budget cuts and restriction of resources. But in many ways, this has started to bring about the shift toward machine learning and AI. Faced with having to do more with less, these organizations are beginning to spin up data teams and leverage cutting-edge tools to bring change more quickly and easily. The biggest challenges in this sector are:

  • Resource constraints
  • Extreme competition among businesses to hire data scientists
  • Small data teams
  • Unorganized, multiple-source data
  • Fairness and bias in machine learning models
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Dataiku & The Public Sector

Given these challenges, and in order to move forward in the age of AI, public sector entities need a tool that can enhance the skills of a small team and truly democratize the use of data throughout the organization.

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The Dataiku Nonprofit Program

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Dataiku is the centralized data platform that moves organizations along their data journey, allowing them to dive in and get moving quickly on analytics, data science, and machine learning at scale. By providing features for technical and non-technical staff alike, a repository of best practices, shortcuts to machine learning and AI deployment/management, and a centralized, controlled environment, Dataiku is the perfect solution to put agencies and entities in the public sector on their path to AI.

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