AI and Government Communications

This post first appeared on IBM Business of Government. Read the original article.

Tuesday, October 31, 2023

Huge Together If We Can Manage The Risks

This is the eighth in a series of articles stemming from the National Academy of Public Administration’s Standing Panel on Technology Leadership as part of its Call to Action on Responsibly Using AI to Benefit Public Service at all Levels of Government. Please see our first blog, “A Call to Action: The Future of Artificial Intelligence and Public Service” second blog, “Artificial Intelligence and Public Service: Key New Challenges,” third blog “Making Government AI-Ready Begins with an AI-Ready Workforce,” fourth blog “Artificial Intelligence and Public Service: Key New Challenges,” fifth blog “Digital innovation: from ‘tech problems’ to ‘redesigning governance’,” sixth blog “Generative AI in Public Education,” and seventh, How Can AI Improve The Regulatory Process?

Societies have always been shaped by communications. Plus government communications with citizens, with other government entities, with the private sector are key to its effective operations. Now, quite recently, such communications are being dramatically reshaped by AI. The results could be wonderful, but we clearly need to protect against some very dangerous and growing problems.

Let’s look briefly at how things have evolved and how we could better manage the risks and returns of moving from big picture new ideas to the realities and negotiations of new actions.


Past. Until roughly 2015, traditional progress in communications and AI created steady new capabilities. The results were notable. But they have also brought dangerous threats for the future.

  • Communications progress has been extremely influential over long period of time. The sweep of human history has brought increasing specialization and scale enabled by language, writing, accounting, art, printing, newspapers/magazines, railroads/telegraph, radio, television, the Internet, etc. We’ve moved from coordinating with well-known individuals and nearby groups to the diversity and anonymity of far flung metropolitan and larger populations. On the technology front, communications have built increasingly large networks for supply chains, marketing, and customer services including fundraising for non-market transactions (e.g., religious groups and elections).
  • Meanwhile, AI has emerged as a powerful agent for change, including in how we communicate. AI formally began in the 1950s, followed by waves of interest and disinterest until the machine learning explosion enabled by powerful computers and very large databases. Today, AI pattern recognition offer pervasively useful applications like voice recognition, text translation, photo recognition, autonomous driving, etc.

Future. By 2030 (if not sooner), AI-augmented communications will have made public sector impacts the top concern for society and decision makers.

  • Communication, as has been true forever, will remain essential for managing weapons of destruction, climate change and pandemics, and other conflicts like those between authoritarian and democratic governance. It will require formal rulemaking at the level of industries and jurisdictions. Perhaps even more important, it will require deeper understanding, support, and action by individuals on a global basis.
  • Meanwhile, the new power of AI will bring capabilities essential for efficient personalized communications. Computing grew a million times more powerful from 1970 to 2010, then another 33 million times by 2020 (the decade of amazing progress with machine learning for text, sound, and photo recognition). By 2030, it will be a billion times more powerful than in 1970. The upsides AI will provide for targeting, delivering, and personalizing communications will be enormous, but the downsides will be extremely dangerous if the new powers are improperly controlled.

Communications for digital reforms have focused historically on individual institutions for the actors to be reached, motivated, and monitored. For future innovation across larger and more independent communities, however, AI-based communications will need to influence more people as individuals and members of cross-boundary communities.


AI-augmented communication will be needed for issues that have long gotten attention. New attention, however, must also go to issues and people not getting the engagement they will need. What follows are some of the issues, AI-related options, and example sources of information for assessment.

  • Issue 1: Continually eroding trust in authority. In the mid 1960s, roughly 80% of Americans felt that those in authority did the right things “most of the time or all of the time.” While the percentage varies from year to year, it has fallen dangerously and is now in the low teens. One option to better manage trust:


The standard learning curve moves naturally to gain knowledge for the next steps required. The earliest work focuses on communications and analysis to gain situational awareness. We identify the problem, a range of relevant options to explore, and possible sources of information required to estimate results. Getting insights from the experience of experts is particularly helpful.

At some point we move to action, usually testing our ideas and hopes via small steps. Progress can be slow before reaching the “take off” productivity that justifies full scale commitment and investment.

In some cases, work from early analysis to full-scale commitment becomes a barrier that kills future progress. That’s often because the high-level early analysis works with high-level costs and benefits. It misses the complex real-world realities and interests of diverse stakeholders, often because stakeholders feel they are safer by keeping things secret.

These problems tend to be worked out in three waves. First the awareness or problem definition wave. Then the getting started with testing and small steps wave. And finally the full commitment “as far as it makes sense” wave.

Those activities typically involve important meetings for thought leadership, then for program or project design, and finally for implementation and operation.

The multiple meetings typically include one-on-one sessions interspersed with groups sessions. That makes the process quite expensive if the meetings need to be in person.

Today, however, it’s often possible to use the awareness work to allow people to become aware of others who could be worked with remotely for the “small steps” and “implementation” waves.

It’s important to understand and succeed with what’s required to move from early ideas to successful action.


In a world shaped by specialization and scale, new possibilities are opening through AI-based big data analytics and communications. We are using computers to augment workers and, hopefully, to create new jobs meeting new needs. A serious shift from incremental to transformational change has – for many institutions, industries, and jurisdictions – not taken a clear direction and shape.

In general, the private sector is taking the new realities of AI-augmented communications seriously. But the public sector – particularly for issues of equity and trust in authority — needs to successfully use AI to get new stakeholders and leaders ready for the future. That has been a focus of this series on AI and the Public Sector; we hope we have spurred discussion and debate on this most important topic.

Image by macrovector_official on Freepik

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