The Future of AI For the Public Sector: The Challenges and Solutions

Submitted by on Tue, 01/07/2025 - 14:30

How best to take advantage of the promise of AI while mitigating risks was a primary topic at a gathering of 30 AI experts last year.  The first installment of a four-part series drawn from this conversation focused on the benefits of AI.  Our second blog began the conversation of the roundtable’s views on key challenges and solutions that need to be addressed to achieve such benefits.

Happy Holidays from The IBM Center for The Business of Government

Wishing you the gift of cheer

this holiday season.

 

 

Driving Digital Transformation

Submitted by on Thu, 12/19/2024 - 12:56

I had the pleasure of hosting Alexis Bonnell, chief information officer (CIO) and director of the Digital Capabilities Directorate at the Air Force Research Laboratory (AFRL) on The Business of Government Hour. She develops and executes the AFRL information technology strategy, leading the strategic development of highly advanced next generation technologies and platforms for AFRL.

Digital Modernization for Government: An Implementation Framework

Submitted by on Thu, 12/19/2024 - 09:49

This challenge is compounded when officials seek to create value for the public from digital modernization when those technologies have evolved via different strategies, including “waterfall” approaches that often take longer to implement than “agile” approaches.

Envisioning the Future of Government

Submitted by on Thu, 12/19/2024 - 09:21

Adapted from chapter 14 in Anticipatory Governance: Shaping a Responsible Future, edited by Melodena Stevens et al, World Scientific Publishing, forthcoming.

How can governments secure implementation of advanced technologies and enable government to use data to make more informed decisions, promote transparency, and improve outcomes in an increasingly complex and uncertain world?

The Mindset of Collaborative Engagement

Submitted by on Tue, 12/17/2024 - 12:25

In the first blog post, six aspects of public engagement were introduced.  Drawing on examples from the William D.

Strategies and Insights for Leading Through the Unexpected - The NAPA Fall Meeting Series

Submitted by on Mon, 12/16/2024 - 10:38
Join host Michael Keegan for a Special Edition of The Business of Government Hour – The National Academy of Public Administration FALL MEETING SERIES. This first in a series of conversations focuses on leading through the unexpected and unanticipated. Michael welcomes NAPA Fellow Chris Mihm to discuss strategies for helping governments prepare for future shocks. He also speaks with Cristina Cabelle, Global Government leader at IBM Consulting on future trends in government.
Broadcast Date: 
Monday, December 16, 2024 - 10:35
Author: 
Michael J. Keegan
Audio: 
Audio icon napa2024_mihm_caballe_broadcast_abcd.mp3

Weekly Roundup: December 9-13, 2024

Submitted by on Fri, 12/13/2024 - 15:16

Leadership

Leaders Shouldn’t Try to Do It All. Many leaders think they can get more done if they simply work harder and longer. But in due course they tire, their overall productivity falls, and they risk burning themselves out and exiting. In this article the authors, drawing on their own experience and that of CEOs they have advised, explain how to escape that trap.

Developing an AI Strategy within a Defense Intelligence Context

Submitted by on Fri, 12/13/2024 - 11:04

Artificial intelligence (AI) has become a critical and strategic capability for defense organizations around the world, offering immense benefits such as improved efficiency, accuracy, and decision making. It has the potential to revolutionize military operations to improve mission outcomes and gain decision advantage.

Nation-State Activity in the Age of Artificial Intelligence and Quantum Computing

Submitted by on Wed, 12/11/2024 - 12:45

Seldom has there been a simultaneous evolution of two powerful and complementary technologies—artificial intelligence (AI) and quantum computing (QC).

AI refers to machines programmed to mimic human intelligence. These systems use algorithms to analyze data, recognize patterns, and make decisions. Generative AI is a subset of AI that creates new content from learned data. It generates original material across various mediums (text, images, audio, etc.). Traditional AI analyzes existing data, but generative AI goes beyond by generating new content.

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