Entries Tagged "democracy"

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AI and Voter Engagement

Social media has been a familiar, even mundane, part of life for nearly two decades. It can be easy to forget it was not always that way.

In 2008, social media was just emerging into the mainstream. Facebook reached 100 million users that summer. And a singular candidate was integrating social media into his political campaign: Barack Obama. His campaign’s use of social media was so bracingly innovative, so impactful, that it was viewed by journalist David Talbot and others as the strategy that enabled the first term Senator to win the White House.

Over the past few years, a new technology has become mainstream: AI. But still, no candidate has unlocked AI’s potential to revolutionize political campaigns. Americans have three more years to wait before casting their ballots in another Presidential election, but we can look at the 2026 midterms and examples from around the globe for signs of how that breakthrough might occur.

How Obama Did It

Rereading the contemporaneous reflections of the New York Times’ late media critic, David Carr, on Obama’s campaign reminds us of just how new social media felt in 2008. Carr positions it within a now-familiar lineage of revolutionary communications technologies from newspapers to radio to television to the internet.

The Obama campaign and administration demonstrated that social media was different from those earlier communications technologies, including the pre-social internet. Yes, increasing numbers of voters were getting their news from the internet, and content about the then-Senator sometimes made a splash by going viral. But those were still broadcast communications: one voice reaching many. Obama found ways to connect voters to each other.

In describing what social media revolutionized in campaigning, Carr quotes campaign vendor Blue State Digital’s Thomas Gensemer: “People will continue to expect a conversation, a two-way relationship that is a give and take.”

The Obama team made some earnest efforts to realize this vision. His transition team launched change.gov, the website where the campaign collected a “Citizen’s Briefing Book” of public comment. Later, his administration built We the People, an online petitioning platform.

But the lasting legacy of Obama’s 2008 campaign, as political scientists Hahrie Han and Elizabeth McKenna chronicled, was pioneering online “relational organizing.” This technique enlisted individuals as organizers to activate their friends in a self-perpetuating web of relationships.

Perhaps because of the Obama campaign’s close association with the method, relational organizing has been touted repeatedly as the linchpin of Democratic campaigns: in 2020, 2024, and today. But research by non-partisan groups like Turnout Nation and right-aligned groups like the Center for Campaign Innovation has also empirically validated the effectiveness of the technique for inspiring voter turnout within connected groups.

The Facebook of 2008 worked well for relational organizing. It gave users tools to connect and promote ideas to the people they know: college classmates, neighbors, friends from work or church. But the nature of social networking has changed since then.

For the past decade, according to Pew Research, Facebook use has stalled and lagged behind YouTube, while Reddit and TikTok have surged. These platforms are less useful for relational organizing, at least in the traditional sense. YouTube is organized more like broadcast television, where content creators produce content disseminated on their own channels in a largely one-way communication to their fans. Reddit gathers users worldwide in forums (subreddits) organized primarily on topical interest. The endless feed of TikTok’s “For You” page disseminates engaging content with little ideological or social commonality. None of these platforms shares the essential feature of Facebook c. 2008: an organizational structure that emphasizes direct connection to people that users have direct social influence over.

AI and Relational Organizing

Ideas and messages might spread virally through modern social channels, but they are not where you convince your friends to show up at a campaign rally. Today’s platforms are spaces for political hobbyism, where you express your political feelings and see others express theirs.

Relational organizing works when one person’s action inspires others to do this same. That’s inherently a chain of human-to-human connection. If my AI assistant inspires your AI assistant, no human notices and one’s vote changes. But key steps in the human chain can be assisted by AI. Tell your phone’s AI assistant to craft a personal message to one friend—or a hundred—and it can do it.

So if a campaign hits you at the right time with the right message, they might persuade you to task your AI assistant to ask your friends to donate or volunteer. The result can be something more than a form letter; it could be automatically drafted based on the entirety of your email or text correspondence with that friend. It could include references to your discussions of recent events, or past campaigns, or shared personal experiences. It could sound as authentic as if you’d written it from the heart, but scaled to everyone in your address book.

Research suggests that AI can generate and perform written political messaging about as well as humans. AI will surely play a tactical role in the 2026 midterm campaigns, and some candidates may even use it for relational organizing in this way.

(Artificial) Identity Politics

For AI to be truly transformative of politics, it must change the way campaigns work. And we are starting to see that in the US.

The earliest uses of AI in American political campaigns are, to be polite, uninspiring. Candidates viewed them as just another tool to optimize an endless stream of email and text message appeals, to ramp up political vitriol, to harvest data on voters and donors, or merely as a stunt.

Of course, we have seen the rampant production and spread of AI-powered deepfakes and misinformation. This is already impacting the key 2026 Senate races, which are likely to attract hundreds of millions of dollars in financing. Roy Cooper, Democratic candidate for US Senate from North Carolina, and Abdul El-Sayed, Democratic candidate for Senate from Michigan, were both targeted by viral deepfake attacks in recent months. This may reflect a growing trend in Donald Trump’s Republican party in the use of AI-generated imagery to build up GOP candidates and assail the opposition.

And yet, in the global elections of 2024, AI was used more memetically than deceptively. So far, conservative and far right parties seem to have adopted this most aggressively. The ongoing rise of Germany’s far-right populist AfD party has been credited to its use of AI to generate nostalgic and evocative (and, to many, offensive) campaign images, videos, and music and, seemingly as a result, they have dominated TikTok. Because most social platforms’ algorithms are tuned to reward media that generates an emotional response, this counts as a double use of AI: to generate content and to manipulate its distribution.

AI can also be used to generate politically useful, though artificial, identities. These identities can fulfill different roles than humans in campaigning and governance because they have differentiated traits. They can’t be imprisoned for speaking out against the state, can be positioned (legitimately or not) as unsusceptible to bribery, and can be forced to show up when humans will not.

In Venezuela, journalists have turned to AI avatars—artificial newsreaders—to report anonymously on issues that would otherwise elicit government retaliation. Albania recently “appointed” an AI to a ministerial post responsible for procurement, claiming that it would be less vulnerable to bribery than a human. In Virginia, both in 2024 and again this year, candidates have used AI avatars as artificial stand-ins for opponents that refused to debate them.

And yet, none of these examples, whether positive or negative, pursue the promise of the Obama campaign: to make voter engagement a “two-way conversation” on a massive scale.

The closest so far to fulfilling that vision anywhere in the world may be Japan’s new political party, Team Mirai. It started in 2024, when an independent Tokyo gubernatorial candidate, Anno Takahiro, used an AI avatar on YouTube to respond to 8,600 constituent questions over a seventeen-day continuous livestream. He collated hundreds of comments on his campaign manifesto into a revised policy platform. While he didn’t win his race, he shot up to a fifth place finish among a record 56 candidates.

Anno was RECENTLY elected to the upper house of the federal legislature as the founder of a new party with a 100 day plan to bring his vision of a “public listening AI” to the whole country. In the early stages of that plan, they’ve invested their share of Japan’s 32 billion yen in party grants—public subsidies for political parties—to hire engineers building digital civic infrastructure for Japan. They’ve already created platforms to provide transparency for party expenditures, and to use AI to make legislation in the Diet easy, and are meeting with engineers from US-based Jigsaw Labs (a Google company) to learn from international examples of how AI can be used to power participatory democracy.

Team Mirai has yet to prove that it can get a second member elected to the Japanese Diet, let alone to win substantial power, but they’re innovating and demonstrating new ways of using AI to give people a way to participate in politics that we believe is likely to spread.

Organizing with AI

AI could be used in the US in similar ways. Following American federalism’s longstanding model of “laboratories of democracy,” we expect the most aggressive campaign innovation to happen at the state and local level.

D.C. Mayor Muriel Bowser is partnering with MIT and Stanford labs to use the AI-based tool deliberation.io to capture wide scale public feedback in city policymaking about AI. Her administration said that using AI in this process allows “the District to better solicit public input to ensure a broad range of perspectives, identify common ground, and cultivate solutions that align with the public interest.”

It remains to be seen how central this will become to Bowser’s expected re-election campaign in 2026, but the technology has legitimate potential to be a prominent part of a broader program to rebuild trust in government. This is a trail blazed by Taiwan a decade ago. The vTaiwan initiative showed how digital tools like Pol.is, which uses machine learning to make sense of real time constituent feedback, can scale participation in democratic processes and radically improve trust in government. Similar AI listening processes have been used in Kentucky, France, and Germany.

Even if campaigns like Bowser’s don’t adopt this kind of AI-facilitated listening and dialog, expect it to be an increasingly prominent part of American public debate. Through a partnership with Jigsaw, Scott Rasmussen’s Napolitan Institute will use AI to elicit and synthesize the views of at least five Americans from every Congressional district in a project called “We the People.” Timed to coincide with the country’s 250th anniversary in 2026, expect the results to be promoted during the heat of the midterm campaign and to stoke interest in this kind of AI-assisted political sensemaking.

In the year where we celebrate the American republic’s semiquincentennial and continue a decade-long debate about whether or not Donald Trump and the Republican party remade in his image is fighting for the interests of the working class, representation will be on the ballot in 2026. Midterm election candidates will look for any way they can get an edge. For all the risks it poses to democracy, AI presents a real opportunity, too, for politicians to engage voters en masse while factoring their input into their platform and message. Technology isn’t going to turn an uninspiring candidate into Barack Obama, but it gives any aspirant to office the capability to try to realize the promise that swept him into office.

This essay was written with Nathan E. Sanders, and originally appeared in The Fulcrum.

Posted on November 18, 2025 at 7:01 AM • View Comments

Will AI Strengthen or Undermine Democracy?

Listen to the Audio on NextBigIdeaClub.com

Below, co-authors Bruce Schneier and Nathan E. Sanders share five key insights from their new book, Rewiring Democracy: How AI Will Transform Our Politics, Government, and Citizenship.

What’s the big idea?

AI can be used both for and against the public interest within democracies. It is already being used in the governing of nations around the world, and there is no escaping its continued use in the future by leaders, policy makers, and legal enforcers. How we wire AI into democracy today will determine if it becomes a tool of oppression or empowerment.

1. AI’s global democratic impact is already profound.

It’s been just a few years since ChatGPT stormed into view and AI’s influence has already permeated every democratic process in governments around the world:

  • In 2022, an artist collective in Denmark founded the world’s first political party committed to an AI-generated policy platform.
  • Also in 2022, South Korean politicians running for the presidency were the first to use AI avatars to communicate with voters en masse.
  • In 2023, a Brazilian municipal legislator passed the first enacted law written by AI.
  • In 2024, a U.S. federal court judge started using AI to interpret the plain meaning of words in U.S. law.
  • Also in 2024, the Biden administration disclosed more than two thousand discrete use cases for AI across the agencies of the U.S. federal government.

The examples illustrate the diverse uses of AI across citizenship, politics, legislation, the judiciary, and executive administration.

Not all of these uses will create lasting change. Some of these will be one-offs. Some are inherently small in scale. Some were publicity stunts. But each use case speaks to a shifting balance of supply and demand that AI will increasingly mediate.

Legislators need assistance drafting bills and have limited staff resources, especially at the local and state level. Historically, they have looked to lobbyists and interest groups for help. Increasingly, it’s just as easy for them to use an AI tool.

2. The first places AI will be used are where there is the least public oversight.

Many of the use cases for AI in governance and politics have vocal objectors. Some make us uncomfortable, especially in the hands of authoritarians or ideological extremists.

In some cases, politics will be a regulating force to prevent dangerous uses of AI. Massachusetts has banned the use of AI face recognition in law enforcement because of real concerns voiced by the public about their tendency to encode systems of racial bias.

Some of the uses we think might be most impactful are unlikely to be adopted fast because of legitimate concern about their potential to make mistakes, introduce bias, or subvert human agency. AIs could be assistive tools for citizens, acting as their voting proxies to help us weigh in on larger numbers of more complex ballot initiatives, but we know that many will object to anything that verges on AIs being given a vote.

But AI will continue to be rapidly adopted in some aspects of democracy, regardless of how the public feels. People within democracies, even those in government jobs, often have great independence. They don’t have to ask anyone if it’s ok to use AI, and they will use it if they see that it benefits them. The Brazilian city councilor who used AI to draft a bill did not ask for anyone’s permission. The U.S. federal judge who used AI to help him interpret law did not have to check with anyone first. And the Trump administration seems to be using AI for everything from drafting tariff policies to writing public health reports—with some obvious drawbacks.

It’s likely that even the thousands of disclosed AI uses in government are only the tip of the iceberg. These are just the applications that governments have seen fit to share; the ones they think are the best vetted, most likely to persist, or maybe the least controversial to disclose.

3. Elites and authoritarians will use AI to concentrate power.

Many Westerners point to China as a cautionary tale of how AI could empower autocracy, but the reality is that AI provides structural advantages to entrenched power in democratic governments, too. The nature of automation is that it gives those at the top of a power structure more control over the actions taken at its lower levels.

It’s famously hard for newly elected leaders to exert their will over the many layers of human bureaucracies. The civil service is large, unwieldy, and messy. But it’s trivial for an executive to change the parameters and instructions of an AI model being used to automate the systems of government.

The dynamic of AI effectuating concentration of power extends beyond government agencies. Over the past five years, Ohio has undertaken a project to do a wholesale revision of its administrative code using AI. The leaders of that project framed it in terms of efficiency and good governance: deleting millions of words of outdated, unnecessary, or redundant language. The same technology could be applied to advance more ideological ends, like purging all statutory language that places burdens on business, neglects to hold businesses accountable, protects some class of people, or fails to protect others.

Whether you like or despise automating the enactment of those policies will depend on whether you stand with or are opposed to those in power, and that’s the point. AI gives any faction with power the potential to exert more control over the levers of government.

4. Organizers will find ways to use AI to distribute power instead.

We don’t have to resign ourselves to a world where AI makes the rich richer and the elite more powerful. This is a technology that can also be wielded by outsiders to help level the playing field.

In politics, AI gives upstart and local candidates access to skills and the ability to do work on a scale that used to only be available to well-funded campaigns. In the 2024 cycle, Congressional candidates running against incumbents like Glenn Cook in Georgia and Shamaine Daniels in Pennsylvania used AI to help themselves be everywhere all at once. They used AI to make personalized robocalls to voters, write frequent blog posts, and even generate podcasts in the candidate’s voice. In Japan, a candidate for Governor of Tokyo used an AI avatar to respond to more than eight thousand online questions from voters.

Outside of public politics, labor organizers are also leveraging AI to build power. The Worker’s Lab is a U.S. nonprofit developing assistive technologies for labor unions, like AI-enabled apps that help service workers report workplace safety violations. The 2023 Writers’ Guild of America strike serves as a blueprint for organizers. They won concessions from Hollywood studios that protect their members against being displaced by AI while also winning them guarantees for being able to use AI as assistive tools to their own benefit.

5. The ultimate democratic impact of AI depends on us.

If you are excited about AI and see the potential for it to make life, and maybe even democracy, better around the world, recognize that there are a lot of people who don’t feel the same way.

If you are disturbed about the ways you see AI being used and worried about the future that leads to, recognize that the trajectory we’re on now is not the only one available.

The technology of AI itself does not pose an inherent threat to citizens, workers, and the public interest. Like other democratic technologies—voting processes, legislative districts, judicial review—its impacts will depend on how it’s developed, who controls it, and how it’s used.

Constituents of democracies should do four things:

  • Reform the technology ecosystem to be more trustworthy, so that AI is developed with more transparency, more guardrails around exploitative use of data, and public oversight.
  • Resist inappropriate uses of AI in government and politics, like facial recognition technologies that automate surveillance and encode inequity.
  • Responsibly use AI in government where it can help improve outcomes, like making government more accessible to people through translation and speeding up administrative decision processes.
  • Renovate the systems of government vulnerable to the disruptive potential of AI’s superhuman capabilities, like political advertising rules that never anticipated deepfakes.

These four Rs are how we can rewire our democracy in a way that applies AI to truly benefit the public interest.

This essay was written with Nathan E. Sanders, and originally appeared in The Next Big Idea Club.

EDITED TO ADD (11/6): This essay was republished by Fast Company.

Posted on October 31, 2025 at 7:08 AM • View Comments

Rewiring Democracy is Coming Soon

My latest book, Rewiring Democracy: How AI Will Transform Our Politics, Government, and Citizenship, will be published in just over a week. No reviews yet, but you can read chapters 12 and 34 (of 43 chapters total).

You can order the book pretty much everywhere, and a copy signed by me here.

Please help spread the word. I want this book to make a splash when it’s public. Leave a review on whatever site you buy it from. Or make a TikTok video. Or do whatever you kids do these days. Is anyone a Slashdot contributor? I’d like the book to be announced there.

Posted on October 13, 2025 at 12:36 PM • View Comments

AI and the Future of American Politics

Two years ago, Americans anxious about the forthcoming 2024 presidential election were considering the malevolent force of an election influencer: artificial intelligence. Over the past several years, we have seen plenty of warning signs from elections worldwide demonstrating how AI can be used to propagate misinformation and alter the political landscape, whether by trolls on social media, foreign influencers, or even a street magician. AI is poised to play a more volatile role than ever before in America’s next federal election in 2026. We can already see how different groups of political actors are approaching AI. Professional campaigners are using AI to accelerate the traditional tactics of electioneering; organizers are using it to reinvent how movements are built; and citizens are using it both to express themselves and amplify their side’s messaging. Because there are so few rules, and so little prospect of regulatory action, around AI’s role in politics, there is no oversight of these activities, and no safeguards against the dramatic potential impacts for our democracy.

The Campaigners

Campaigners—messengers, ad buyers, fundraisers, and strategists—are focused on efficiency and optimization. To them, AI is a way to augment or even replace expensive humans who traditionally perform tasks like personalizing emails, texting donation solicitations, and deciding what platforms and audiences to target.

This is an incremental evolution of the computerization of campaigning that has been underway for decades. For example, the progressive campaign infrastructure group Tech for Campaigns claims it used AI in the 2024 cycle to reduce the time spent drafting fundraising solicitations by one-third. If AI is working well here, you won’t notice the difference between an annoying campaign solicitation written by a human staffer and an annoying one written by AI.

But AI is scaling these capabilities, which is likely to make them even more ubiquitous. This will make the biggest difference for challengers to incumbents in safe seats, who see AI as both a tacitly useful tool and an attention-grabbing way to get their race into the headlines. Jason Palmer, the little-known Democratic primary challenger to Joe Biden, successfully won the American Samoa primary while extensively leveraging AI avatars for campaigning.

Such tactics were sometimes deployed as publicity stunts in the 2024 cycle; they were firsts that got attention. Pennsylvania Democratic Congressional candidate Shamaine Daniels became the first to use a conversational AI robocaller in 2023. Two long-shot challengers to Rep. Don Beyer used an AI avatar to represent the incumbent in a live debate last October after he declined to participate. In 2026, voters who have seen years of the official White House X account posting deepfaked memes of Donald Trump will be desensitized to the use of AI in political communications.

Strategists are also turning to AI to interpret public opinion data and provide more fine-grained insight into the perspective of different voters. This might sound like AIs replacing people in opinion polls, but it is really a continuation of the evolution of political polling into a data-driven science over the last several decades.

A recent survey by the American Association of Political Consultants found that a majority of their members’ firms already use AI regularly in their work, and more than 40 percent believe it will “fundamentally transform” the future of their profession. If these emerging AI tools become popular in the midterms, it won’t just be a few candidates from the tightest national races texting you three times a day. It may also be the member of Congress in the safe district next to you, and your state representative, and your school board members.

The development and use of AI in campaigning is different depending on what side of the aisle you look at. On the Republican side, Push Digital Group is going “all in” on a new AI initiative, using the technology to create hundreds of ad variants for their clients automatically, as well as assisting with strategy, targeting, and data analysis. On the other side, the National Democratic Training Committee recently released a playbook for using AI. Quiller is building an AI-powered fundraising platform aimed at drastically reducing the time campaigns spend producing emails and texts. Progressive-aligned startups Chorus AI and BattlegroundAI are offering AI tools for automatically generating ads for use on social media and other digital platforms. DonorAtlas automates data collection on potential donors, and RivalMind AI focuses on political research and strategy, automating the production of candidate dossiers.

For now, there seems to be an investment gap between Democratic- and Republican-aligned technology innovators. Progressive venture fund Higher Ground Labs boasts $50 million in deployed investments since 2017 and a significant focus on AI. Republican-aligned counterparts operate on a much smaller scale. Startup Caucus has announced one investment—of $50,000—since 2022. The Center for Campaign Innovation funds research projects and events, not companies. This echoes a longstanding gap in campaign technology between Democratic- and Republican-aligned fundraising platforms ActBlue and WinRed, which has landed the former in Republicans’ political crosshairs.

Of course, not all campaign technology innovations will be visible. In 2016, the Trump campaign vocally eschewed using data to drive campaign strategy and appeared to be falling way behind on ad spending, but was—we learned in retrospect—actually leaning heavily into digital advertising and making use of new controversial mechanisms for accessing and exploiting voters’ social media data with vendor Cambridge Analytica. The most impactful uses of AI in the 2026 midterms may not be known until 2027 or beyond.

The Organizers

Beyond the realm of political consultants driving ad buys and fundraising appeals, organizers are using AI in ways that feel more radically new.

The hypothetical potential of AI to drive political movements was illustrated in 2022 when a Danish artist collective used an AI model to found a political party, the Synthetic Party, and generate its policy goals. This was more of an art project than a popular movement, but it demonstrated that AIs—synthesizing the expressions and policy interests of humans—can formulate a political platform. In 2025, Denmark hosted a “summit” of eight such AI political agents where attendees could witness “continuously orchestrate[d] algorithmic micro-assemblies, spontaneous deliberations, and impromptu policy-making” by the participating AIs.

The more viable version of this concept lies in the use of AIs to facilitate deliberation. AIs are being used to help legislators collect input from constituents and to hold large-scale citizen assemblies. This kind of AI-driven “sensemaking” may play a powerful role in the future of public policy. Some research has suggested that AI can be as or more effective than humans in helping people find common ground on controversial policy issues.

Another movement for “Public AI” is focused on wresting AI from the hands of corporations to put people, through their governments, in control. Civic technologists in national governments from Singapore, Japan, Sweden, and Switzerland are building their own alternatives to Big Tech AI models, for use in public administration and distribution as a public good.

Labor organizers have a particularly interesting relationship to AI. At the same time that they are galvanizing mass resistance against the replacement or endangerment of human workers by AI, many are racing to leverage the technology in their own work to build power.

Some entrepreneurial organizers have used AI in the past few years as tools for activating, connecting, answering questions for, and providing guidance to their members. In the UK, the Centre for Responsible Union AI studies and promotes the use of AI by unions; they’ve published several case studies. The UK Public and Commercial Services Union has used AI to help their reps simulate recruitment conversations before going into the field. The Belgian union ACV-CVS has used AI to sort hundreds of emails per day from members to help them respond more efficiently. Software companies such as Quorum are increasingly offering AI-driven products to cater to the needs of organizers and grassroots campaigns.

But unions have also leveraged AI for its symbolic power. In the U.S., the Screen Actors Guild held up the specter of AI displacement of creative labor to attract public attention and sympathy, and the ETUC (the European confederation of trade unions) developed a policy platform for responding to AI.

Finally, some union organizers have leveraged AI in more provocative ways. Some have applied it to hacking the “bossware” AI to subvert the exploitative intent or disrupt the anti-union practices of their managers.

The Citizens

Many of the tasks we’ve talked about so far are familiar use cases to anyone working in office and management settings: writing emails, providing user (or voter, or member) support, doing research.

But even mundane tasks, when automated at scale and targeted at specific ends, can be pernicious. AI is not neutral. It can be applied by many actors for many purposes. In the hands of the most numerous and diverse actors in a democracy—the citizens—that has profound implications.

Conservative activists in Georgia and Florida have used a tool named EagleAI to automate challenging voter registration en masse (although the tool’s creator later denied that it uses AI). In a nonpartisan electoral management context with access to accurate data sources, such automated review of electoral registrations might be useful and effective. In this hyperpartisan context, AI merely serves to amplify the proclivities of activists at the extreme of their movements. This trend will continue unabated in 2026.

Of course, citizens can use AI to safeguard the integrity of elections. In Ghana’s 2024 presidential election, civic organizations used an AI tool to automatically detect and mitigate electoral disinformation spread on social media. The same year, Kenyan protesters developed specialized chatbots to distribute information about a controversial finance bill in Parliament and instances of government corruption.

So far, the biggest way Americans have leveraged AI in politics is in self-expression. About ten million Americans have used the chatbot Resistbot to help draft and send messages to their elected leaders. It’s hard to find statistics on how widely adopted tools like this are, but researchers have estimated that, as of 2024, about one in five consumer complaints to the U.S. Consumer Financial Protection Bureau was written with the assistance of AI.

OpenAI operates security programs to disrupt foreign influence operations and maintains restrictions on political use in its terms of service, but this is hardly sufficient to deter use of AI technologies for whatever purpose. And widely available free models give anyone the ability to attempt this on their own.

But this could change. The most ominous sign of AI’s potential to disrupt elections is not the deepfakes and misinformation. Rather, it may be the use of AI by the Trump administration to surveil and punish political speech on social media and other online platforms. The scalability and sophistication of AI tools give governments with authoritarian intent unprecedented power to police and selectively limit political speech.

What About the Midterms?

These examples illustrate AI’s pluripotent role as a force multiplier. The same technology used by different actors—campaigners, organizers, citizens, and governments—leads to wildly different impacts. We can’t know for sure what the net result will be. In the end, it will be the interactions and intersections of these uses that matters, and their unstable dynamics will make future elections even more unpredictable than in the past.

For now, the decisions of how and when to use AI lie largely with individuals and the political entities they lead. Whether or not you personally trust AI to write an email for you or make a decision about you hardly matters. If a campaign, an interest group, or a fellow citizen trusts it for that purpose, they are free to use it.

It seems unlikely that Congress or the Trump administration will put guardrails around the use of AI in politics. AI companies have rapidly emerged as among the biggest lobbyists in Washington, reportedly dumping $100 million toward preventing regulation, with a focus on influencing candidate behavior before the midterm elections. The Trump administration seems open and responsive to their appeals.

The ultimate effect of AI on the midterms will largely depend on the experimentation happening now. Candidates and organizations across the political spectrum have ample opportunity—but a ticking clock—to find effective ways to use the technology. Those that do will have little to stop them from exploiting it.

This essay was written with Nathan E. Sanders, and originally appeared in The American Prospect.

Posted on October 13, 2025 at 7:04 AM • View Comments

AI in the 2026 Midterm Elections

We are nearly one year out from the 2026 midterm elections, and it’s far too early to predict the outcomes. But it’s a safe bet that artificial intelligence technologies will once again be a major storyline.

The widespread fear that AI would be used to manipulate the 2024 US election seems rather quaint in a year where the president posts AI-generated images of himself as the pope on official White House accounts. But AI is a lot more than an information manipulator. It’s also emerging as a politicized issue. Political first-movers are adopting the technology, and that’s opening a gap across party lines.

We expect this gap to widen, resulting in AI being predominantly used by one political side in the 2026 elections. To the extent that AI’s promise to automate and improve the effectiveness of political tasks like personalized messaging, persuasion, and campaign strategy is even partially realized, this could generate a systematic advantage.

Right now, Republicans look poised to exploit the technology in the 2026 midterms. The Trump White House has aggressively adopted AI-generated memes in its online messaging strategy. The administration has also used executive orders and federal buying power to influence the development and encoded values of AI technologies away from “woke” ideology. Going further, Trump ally Elon Musk has shaped his own AI company’s Grok models in his own ideological image. These actions appear to be part of a larger, ongoing Big Tech industry realignment towards the political will, and perhaps also the values, of the Republican party.

Democrats, as the party out of power, are in a largely reactive posture on AI. A large bloc of Congressional Democrats responded to Trump administration actions in April by arguing against their adoption of AI in government. Their letter to the Trump administration’s Office of Management and Budget provided detailed criticisms and questions about DOGE’s behaviors and called for a halt to DOGE’s use of AI, but also said that they “support implementation of AI technologies in a manner that complies with existing” laws. It was a perfectly reasonable, if nuanced, position, and illustrates how the actions of one party can dictate the political positioning of the opposing party.

These shifts are driven more by political dynamics than by ideology. Big Tech CEOs’ deference to the Trump administration seems largely an effort to curry favor, while Silicon Valley continues to be represented by tech-forward Democrat Ro Khanna. And a June Pew Research poll shows nearly identical levels of concern by Democrats and Republicans about the increasing use of AI in America.

There are, arguably, natural positions each party would be expected to take on AI. An April House subcommittee hearing on AI trends in innovation and competition revealed much about that equilibrium. Following the lead of the Trump administration, Republicans cast doubt on any regulation of the AI industry. Democrats, meanwhile, emphasized consumer protection and resisting a concentration of corporate power. Notwithstanding the fluctuating dominance of the corporate wing of the Democratic party and the volatile populism of Trump, this reflects the parties’ historical positions on technology.

While Republicans focus on cozying up to tech plutocrats and removing the barriers around their business models, Democrats could revive the 2020 messaging of candidates like Andrew Yang and Elizabeth Warren. They could paint an alternative vision of the future where Big Tech companies’ profits and billionaires’ wealth are taxed and redistributed to young people facing an affordability crisis for housing, healthcare, and other essentials.

Moreover, Democrats could use the technology to demonstrably show a commitment to participatory democracy. They could use AI-driven collaborative policymaking tools like Decidim, Pol.Is, and Go Vocal to collect voter input on a massive scale and align their platform to the public interest.

It’s surprising how little these kinds of sensemaking tools are being adopted by candidates and parties today. Instead of using AI to capture and learn from constituent input, candidates more often seem to think of AI as just another broadcast technology—good only for getting their likeness and message in front of people. A case in point: British Member of Parliament Mark Sewards, presumably acting in good faith, recently attracted scorn after releasing a vacuous AI avatar of himself to his constituents.

Where the political polarization of AI goes next will probably depend on unpredictable future events and how partisans opportunistically seize on them. A recent European political controversy over AI illustrates how this can happen.

Swedish Prime Minister Ulf Kristersson, a member of the country’s Moderate party, acknowledged in an August interview that he uses AI tools to get a “second opinion” on policy issues. The attacks from political opponents were scathing. Kristersson had earlier this year advocated for the EU to pause its trailblazing new law regulating AI and pulled an AI tool from his campaign website after it was abused to generate images of him appearing to solicit an endorsement from Hitler. Although arguably much more consequential, neither of those stories grabbed global headlines in the way the Prime Minister’s admission that he himself uses tools like ChatGPT did.

Age dynamics may govern how AI’s impacts on the midterms unfold. One of the prevailing trends that swung the 2024 election to Trump seems to have been the rightward migration of young voters, particularly white men. So far, YouGov’s political tracking poll does not suggest a huge shift in young voters’ Congressional voting intent since the 2022 midterms.

Embracing—or distancing themselves from—AI might be one way the parties seek to wrest control of this young voting bloc. While the Pew poll revealed that large fractions of Americans of all ages are generally concerned about AI, younger Americans are much more likely to say they regularly interact with, and hear a lot about, AI, and are comfortable with the level of control they have over AI in their lives. A Democratic party desperate to regain relevance for and approval from young voters might turn to AI as both a tool and a topic for engaging them.

Voters and politicians alike should recognize that AI is no longer just an outside influence on elections. It’s not an uncontrollable natural disaster raining deepfakes down on a sheltering electorate. It’s more like a fire: a force that political actors can harness and manipulate for both mechanical and symbolic purposes.

A party willing to intervene in the world of corporate AI and shape the future of the technology should recognize the legitimate fears and opportunities it presents, and offer solutions that both address and leverage AI.

This essay was written with Nathan E. Sanders, and originally appeared in Time.

Posted on October 6, 2025 at 7:06 AM • View Comments

How Cybersecurity Fears Affect Confidence in Voting Systems

American democracy runs on trust, and that trust is cracking.

Nearly half of Americans, both Democrats and Republicans, question whether elections are conducted fairly. Some voters accept election results only when their side wins. The problem isn’t just political polarization—it’s a creeping erosion of trust in the machinery of democracy itself.

Commentators blame ideological tribalism, misinformation campaigns and partisan echo chambers for this crisis of trust. But these explanations miss a critical piece of the puzzle: a growing unease with the digital infrastructure that now underpins nearly every aspect of how Americans vote.

The digital transformation of American elections has been swift and sweeping. Just two decades ago, most people voted using mechanical levers or punch cards. Today, over 95% of ballots are counted electronically. Digital systems have replaced poll books, taken over voter identity verification processes and are integrated into registration, counting, auditing and voting systems.

This technological leap has made voting more accessible and efficient, and sometimes more secure. But these new systems are also more complex. And that complexity plays into the hands of those looking to undermine democracy.

In recent years, authoritarian regimes have refined a chillingly effective strategy to chip away at Americans’ faith in democracy by relentlessly sowing doubt about the tools U.S. states use to conduct elections. It’s a sustained campaign to fracture civic faith and make Americans believe that democracy is rigged, especially when their side loses.

This is not cyberwar in the traditional sense. There’s no evidence that anyone has managed to break into voting machines and alter votes. But cyberattacks on election systems don’t need to succeed to have an effect. Even a single failed intrusion, magnified by sensational headlines and political echo chambers, is enough to shake public trust. By feeding into existing anxiety about the complexity and opacity of digital systems, adversaries create fertile ground for disinformation and conspiracy theories.

Testing cyber fears

To test this dynamic, we launched a study to uncover precisely how cyberattacks corroded trust in the vote during the 2024 U.S. presidential race. We surveyed more than 3,000 voters before and after election day, testing them using a series of fictional but highly realistic breaking news reports depicting cyberattacks against critical infrastructure. We randomly assigned participants to watch different types of news reports: some depicting cyberattacks on election systems, others on unrelated infrastructure such as the power grid, and a third, neutral control group.

The results, which are under peer review, were both striking and sobering. Mere exposure to reports of cyberattacks undermined trust in the electoral process—regardless of partisanship. Voters who supported the losing candidate experienced the greatest drop in trust, with two-thirds of Democratic voters showing heightened skepticism toward the election results.

But winners too showed diminished confidence. Even though most Republican voters, buoyed by their victory, accepted the overall security of the election, the majority of those who viewed news reports about cyberattacks remained suspicious.

The attacks didn’t even have to be related to the election. Even cyberattacks against critical infrastructure such as utilities had spillover effects. Voters seemed to extrapolate: “If the power grid can be hacked, why should I believe that voting machines are secure?”

Strikingly, voters who used digital machines to cast their ballots were the most rattled. For this group of people, belief in the accuracy of the vote count fell by nearly twice as much as that of voters who cast their ballots by mail and who didn’t use any technology. Their firsthand experience with the sorts of systems being portrayed as vulnerable personalized the threat.

It’s not hard to see why. When you’ve just used a touchscreen to vote, and then you see a news report about a digital system being breached, the leap in logic isn’t far.

Our data suggests that in a digital society, perceptions of trust—and distrust—are fluid, contagious and easily activated. The cyber domain isn’t just about networks and code. It’s also about emotions: fear, vulnerability and uncertainty.

Firewall of trust

Does this mean we should scrap electronic voting machines? Not necessarily.

Every election system, digital or analog, has flaws. And in many respects, today’s high-tech systems have solved the problems of the past with voter-verifiable paper ballots. Modern voting machines reduce human error, increase accessibility and speed up the vote count. No one misses the hanging chads of 2000.

But technology, no matter how advanced, cannot instill legitimacy on its own. It must be paired with something harder to code: public trust. In an environment where foreign adversaries amplify every flaw, cyberattacks can trigger spirals of suspicion. It is no longer enough for elections to be secure – voters must also perceive them to be secure.

That’s why public education surrounding elections is now as vital to election security as firewalls and encrypted networks. It’s vital that voters understand how elections are run, how they’re protected and how failures are caught and corrected. Election officials, civil society groups and researchers can teach how audits work, host open-source verification demonstrations and ensure that high-tech electoral processes are comprehensible to voters.

We believe this is an essential investment in democratic resilience. But it needs to be proactive, not reactive. By the time the doubt takes hold, it’s already too late.

Just as crucially, we are convinced that it’s time to rethink the very nature of cyber threats. People often imagine them in military terms. But that framework misses the true power of these threats. The danger of cyberattacks is not only that they can destroy infrastructure or steal classified secrets, but that they chip away at societal cohesion, sow anxiety and fray citizens’ confidence in democratic institutions. These attacks erode the very idea of truth itself by making people doubt that anything can be trusted.

If trust is the target, then we believe that elected officials should start to treat trust as a national asset: something to be built, renewed and defended. Because in the end, elections aren’t just about votes being counted—they’re about people believing that those votes count.

And in that belief lies the true firewall of democracy.

This essay was written with Ryan Shandler and Anthony J. DeMattee, and originally appeared in The Conversation.

Posted on June 30, 2025 at 7:05 AM • View Comments

The Voter Experience

Technology and innovation have transformed every part of society, including our electoral experiences. Campaigns are spending and doing more than at any other time in history. Ever-growing war chests fuel billions of voter contacts every cycle. Campaigns now have better ways of scaling outreach methods and offer volunteers and donors more efficient ways to contribute time and money. Campaign staff have adapted to vast changes in media and social media landscapes, and use data analytics to forecast voter turnout and behavior.

Yet despite these unprecedented investments in mobilizing voters, overall trust in electoral health, democratic institutions, voter satisfaction, and electoral engagement has significantly declined. What might we be missing?

In software development, the concept of user experience (UX) is fundamental to the design of any product or service. It’s a way to think holistically about how a user interacts with technology. It ensures that products and services are built with the users’ actual needs, behaviors, and expectations in mind, as opposed to what developers think users want. UX enables informed decisions based on how the user will interact with the system, leading to improved design, more effective solutions, and increased user satisfaction. Good UX design results in easy, relevant, useful, positive experiences. Bad UX design leads to unhappy users.

This is not how we normally think of elections. Campaigns measure success through short-term outputs—voter contacts, fundraising totals, issue polls, ad impressions—and, ultimately, election results. Rarely do they evaluate how individuals experience this as a singular, messy, democratic process. Each campaign, PAC, nonprofit, and volunteer group may be focused on their own goal, but the voter experiences it all at once. By the time they’re in line to vote, they’ve been hit with a flood of outreach—spammy texts from unfamiliar candidates, organizers with no local ties, clunky voter registration sites, conflicting information, and confusing messages, even from campaigns they support. Political teams can point to data that justifies this barrage, but the effectiveness of voter contact has been steadily declining since 2008. Intuitively, we know this approach has long-term costs. To address this, let’s evaluate the UX of an election cycle from the point of view of the end user, the everyday citizen.

Specifically, how might we define the UX of an election cycle: the voter experience (VX)? A VX lens could help us see the full impact of the electoral cycle from the perspective that matters most: the voters’.

For example, what if we thought about elections in terms of questions like these?

  • How do voters experience an election cycle, from start to finish?
  • How do voters perceive their interactions with political campaigns?
  • What aspects of the election cycle do voters enjoy? What do they dislike? Do citizens currently feel fulfilled by voting?
  • If voters “tune out” of politics, what part of the process has made them want to not pay attention?
  • What experiences decrease the number of eligible citizens who register and vote?
  • Are we able to measure the cumulative impacts of political content interactions over the course of multiple election cycles?
  • Can polls or focus groups help researchers learn about longitudinal sentiment from citizens as they experience multiple election cycles?
  • If so, what would we want to learn in order to bolster democratic participation and trust in institutions?

Thinking in terms of VX can help answer these questions. Moreover, researching and designing around VX could help identify additional metrics, beyond traditional turnout and engagement numbers, that better reflect the collective impact of campaigning: of all those voter contact and persuasion efforts combined.

This isn’t a radically new idea, and earlier efforts to embed UX design into electoral work yielded promising early benefits. In 2020, a coalition of political tech builders created a Volunteer Experience program. The group held design sprints for political tech tools, such as canvassing apps and phone banking sites. Their goal was to apply UX principles to improve the volunteer user flow, enhance data hygiene, and improve volunteer retention. If a few sprints can improve the phone banking experience, imagine the transformative possibilities of taking this lens to the VX as a whole.

If we want democracy to thrive long-term, we need to think beyond short-term wins and table stakes. This isn’t about replacing grassroots organizing or civic action with digital tools. Rather, it’s about learning from UX research methodology to build lasting, meaningful engagement that involves both technology and community organizing. Often, it is indeed local, on-the-ground organizers who have been sounding the alarm about the long-term effects of prioritizing short-term tactics. A VX approach may provide additional data to bolster their arguments.

Learnings from a VX analysis of election cycles could also guide the design of new programs that not only mobilize voters (to contribute, to campaign for their candidates, and to vote), but also ensure that the entire process of voting, post-election follow-up, and broader civic participation is as accessible, intuitive, and fulfilling as possible. Better voter UX will lead to more politically engaged citizens and higher voter turnout.

VX methodology may help combine real-time citizen feedback with centralized decision-making. Moving beyond election cycles, focusing on the citizen UX could accelerate possibilities for citizens to provide real-time feedback, review the performance of elected officials and government, and receive help-desk-style support with the same level of ease as other everyday “products.” By understanding how people engage with civic life over time, we can better design systems for citizens that strengthen participation, trust, and accountability at every level.

Our hope is that this approach, and the new data and metrics uncovered by it, will support shifts that help restore civic participation and strengthen trust in institutions. With citizens oriented as the central users of our democratic systems, we can build new best practices for fulfilling civic infrastructure that foster a more effective and inclusive democracy.

The time for this is now. Despite hard-fought victories and lessons learned from failures, many people working in politics privately acknowledge a hard truth: our current approach isn’t working. Every two years, people build campaigns, mobilize voters, and drive engagement, but they are held back by what they don’t understand about the long-term impact of their efforts. VX thinking can help solve that.

This essay was written with Hillary Lehr, and originally appeared on the Harvard Kennedy School Ash Center’s website.

Posted on May 22, 2025 at 7:06 AM • View Comments

Reimagining Democracy

Imagine that all of us—all of society—have landed on some alien planet and need to form a government: clean slate. We do not have any legacy systems from the United States or any other country. We do not have any special or unique interests to perturb our thinking. How would we govern ourselves? It is unlikely that we would use the systems we have today. Modern representative democracy was the best form of government that eighteenth-century technology could invent. The twenty-first century is very different: scientifically, technically, and philosophically. For example, eighteenth-century democracy was designed under the assumption that travel and communications were both hard.

Indeed, the very idea of representative government was a hack to get around technological limitations. Voting is easier now. Does it still make sense for all of us living in the same place to organize every few years and choose one of us to go to a single big room far away and make laws in our name? Representative districts are organized around geography because that was the only way that made sense two hundred-plus years ago. But we do not need to do it that way anymore. We could organize representation by age: one representative for the thirty-year-olds, another for the forty-year-olds, and so on. We could organize representation randomly: by birthday, perhaps. We can organize in any way we want. American citizens currently elect people to federal posts for terms ranging from two to six years. Would ten years be better for some posts? Would ten days be better for others? There are lots of possibilities. Maybe we can make more use of direct democracy by way of plebiscites. Certainly we do not want all of us, individually, to vote on every amendment to every bill, but what is the optimal balance between votes made in our name and ballot initiatives that we all vote on?

For the past three years, I have organized a series of annual two-day workshops to discuss these and other such questions.1 For each event, I brought together fifty people from around the world: political scientists, economists, law professors, experts in artificial intelligence, activists, government types, historians, science-fiction writers, and more. We did not come up with any answers to our questions—and I would have been surprised if we had—but several themes emerged from the event. Misinformation and propaganda was a theme, of course, and the inability to engage in rational policy discussions when we cannot agree on facts. The deleterious effects of optimizing a political system for economic outcomes was another theme. Given the ability to start over, would anyone design a system of government for the near-term financial interest of the wealthiest few? Another theme was capitalism and how it is or is not intertwined with democracy. While the modern market economy made a lot of sense in the industrial age, it is starting to fray in the information age. What comes after capitalism, and how will it affect the way we govern ourselves?

Many participants examined the effects of technology, especially artificial intelligence (AI). We looked at whether—and when—we might be comfortable ceding power to an AI system. Sometimes deciding is easy. I am happy for an AI system to figure out the optimal timing of traffic lights to ensure the smoothest flow of cars through my city. When will we be able to say the same thing about the setting of interest rates? Or taxation? How would we feel about an AI device in our pocket that voted in our name, thousands of times per day, based on preferences that it inferred from our actions? Or how would we feel if an AI system could determine optimal policy solutions that balanced every voter’s preferences: Would it still make sense to have a legislature and representatives? Possibly we should vote directly for ideas and goals instead, and then leave the details to the computers.

These conversations became more pointed in the second and third years of our workshop, after generative AI exploded onto the internet. Large language models are poised to write laws, enforce both laws and regulations, act as lawyers and judges, and plan political strategy. How this capacity will compare to human expertise and capability is still unclear, but the technology is changing quickly and dramatically. We will not have AI legislators anytime soon, but just as today we accept that all political speeches are professionally written by speechwriters, will we accept that future political speeches will all be written by AI devices? Will legislators accept AI-written legislation, especially when that legislation includes a level of detail that human-based legislation generally does not? And if so, how will that change affect the balance of power between the legislature and the administrative state? Most interestingly, what happens when the AI tools we use to both write and enforce laws start to suggest policy options that are beyond human understanding? Will we accept them, because they work? Or will we reject a system of governance where humans are only nominally in charge?

Scale was another theme of the workshops. The size of modern governments reflects the technology at the time of their founding. European countries and the early American states are a particular size because that was a governable size in the eighteenth and nineteenth centuries. Larger governments—those of the United States as a whole and of the European Union—reflect a world where travel and communications are easier. Today, though, the problems we have are either local, at the scale of cities and towns, or global. Do we really have need for a political unit the size of France or Virginia? Or is it a mixture of scales that we really need, one that moves effectively between the local and the global?

As to other forms of democracy, we discussed one from history and another made possible by today’s technology. Sortition is a system of choosing political officials randomly. We use it today when we pick juries, but both the ancient Greeks and some cities in Renaissance Italy used it to select major political officials. Today, several countries—largely in Europe—are using the process to decide policy on complex issues. We might randomly choose a few hundred people, representative of the population, to spend a few weeks being briefed by experts, debating the issues, and then deciding on environmental regulations, or a budget, or pretty much anything.

“Liquid democracy” is a way of doing away with elections altogether. The idea is that everyone has a vote and can assign it to anyone they choose. A representative collects the proxies assigned to him or her and can either vote directly on the issues or assign all the proxies to someone else. Perhaps proxies could be divided: this person for economic matters, another for health matters, a third for national defense, and so on. In the purer forms of this system, people might transfer their votes to someone else at any time. There would be no more election days: vote counts might change every day.

And then, there is the question of participation and, more generally, whose interests are taken into account. Early democracies were really not democracies at all; they limited participation by gender, race, and land ownership. These days, to achieve a more comprehensive electorate we could lower the voting age. But, of course, even children too young to vote have rights, and in some cases so do other species. Should future generations be given a “voice,” whatever that means? What about nonhumans, or whole ecosystems? Should everyone have the same volume and type of voice? Right now, in the United States, the very wealthy have much more influence than others do. Should we encode that superiority explicitly? Perhaps younger people should have a more powerful vote than everyone else. Or maybe older people should.

In the workshops, those questions led to others about the limits of democracy. All democracies have boundaries limiting what the majority can decide. We are not allowed to vote Common Knowledge out of existence, for example, but can generally regulate speech to some degree. We cannot vote, in an election, to jail someone, but we can craft laws that make a particular action illegal. We all have the right to certain things that cannot be taken away from us. In the community of our future, what should be our rights as individuals? What should be the rights of society, superseding those of individuals?

Personally, I was most interested, at each of the three workshops, in how political systems fail. As a security technologist, I study how complex systems are subverted—hacked, in my parlance—for the benefit of a few at the expense of the many. Think of tax loopholes, or tricks to avoid government regulation. These hacks are common today, and AI tools will make them easier to find—and even to design—in the future. I would want any government system to be resistant to trickery. Or, to put it another way: I want the interests of each individual to align with the interests of the group at every level. We have never had a system of government with this property, but—in a time of existential risks such as climate change—it is important that we develop one.

Would this new system of government even be called “democracy”? I truly do not know.

Such speculation is not practical, of course, but still is valuable. Our workshops did not produce final answers and were not intended to do so. Our discourse was filled with suggestions about how to patch our political system where it is fraying. People regularly debate changes to the US Electoral College, or the process of determining voting districts, or the setting of term limits. But those are incremental changes. It is difficult to find people who are thinking more radically: looking beyond the horizon—not at what is possible today but at what may be possible eventually. Thinking incrementally is critically important, but it is also myopic. It represents a hill-climbing strategy of continuous but quite limited improvements. We also need to think about discontinuous changes that we cannot easily get to from here; otherwise, we may be forever stuck at local maxima. And while true innovation in politics is a lot harder than innovation in technology, especially without a violent revolution forcing changes on us, it is something that we as a species are going to have to get good at, one way or another.

Our workshop will reconvene for a fourth meeting in December 2025.

Note

  1. The First International Workshop on Reimagining Democracy (IWORD) was held December 7—8, 2022. The Second IWORD was held December 12—13, 2023. Both took place at the Harvard Kennedy School. The sponsors were the Ford Foundation, the Knight Foundation, and the Ash and Belfer Centers of the Kennedy School. See Schneier, “Recreating Democracy” and Schneier, “Second Interdisciplinary Workshop.”

This essay was originally published in Common Knowledge.

Posted on April 10, 2025 at 8:35 PM • View Comments

AI and Civil Service Purges

Donald Trump and Elon Musk’s chaotic approach to reform is upending government operations. Critical functions have been halted, tens of thousands of federal staffers are being encouraged to resign, and congressional mandates are being disregarded. The next phase: The Department of Government Efficiency reportedly wants to use AI to cut costs. According to The Washington Post, Musk’s group has started to run sensitive data from government systems through AI programs to analyze spending and determine what could be pruned. This may lead to the elimination of human jobs in favor of automation. As one government official who has been tracking Musk’s DOGE team told the Post, the ultimate aim is to use AI to replace “the human workforce with machines.” (Spokespeople for the White House and DOGE did not respond to requests for comment.)

Using AI to make government more efficient is a worthy pursuit, and this is not a new idea. The Biden administration disclosed more than 2,000 AI applications in development across the federal government. For example, FEMA has started using AI to help perform damage assessment in disaster areas. The Centers for Medicare and Medicaid Services has started using AI to look for fraudulent billing. The idea of replacing dedicated and principled civil servants with AI agents, however, is new—and complicated.

The civil service—the massive cadre of employees who operate government agencies—plays a vital role in translating laws and policy into the operation of society. New presidents can issue sweeping executive orders, but they often have no real effect until they actually change the behavior of public servants. Whether you think of these people as essential and inspiring do-gooders, boring bureaucratic functionaries, or as agents of a “deep state,” their sheer number and continuity act as ballast that resists institutional change.

This is why Trump and Musk’s actions are so significant. The more AI decision making is integrated into government, the easier change will be. If human workers are widely replaced with AI, executives will have unilateral authority to instantaneously alter the behavior of the government, profoundly raising the stakes for transitions of power in democracy. Trump’s unprecedented purge of the civil service might be the last time a president needs to replace the human beings in government in order to dictate its new functions. Future leaders may do so at the press of a button.

To be clear, the use of AI by the executive branch doesn’t have to be disastrous. In theory, it could allow new leadership to swiftly implement the wishes of its electorate. But this could go very badly in the hands of an authoritarian leader. AI systems concentrate power at the top, so they could allow an executive to effectuate change over sprawling bureaucracies instantaneously. Firing and replacing tens of thousands of human bureaucrats is a huge undertaking. Swapping one AI out for another, or modifying the rules that those AIs operate by, would be much simpler.

Social-welfare programs, if automated with AI, could be redirected to systematically benefit one group and disadvantage another with a single prompt change. Immigration-enforcement agencies could prioritize people for investigation and detainment with one instruction. Regulatory-enforcement agencies that monitor corporate behavior for malfeasance could turn their attention to, or away from, any given company on a whim.

Even if Congress were motivated to fight back against Trump and Musk, or against a future president seeking to bulldoze the will of the legislature, the absolute power to command AI agents would make it easier to subvert legislative intent. AI has the power to diminish representative politics. Written law is never fully determinative of the actions of government—there is always wiggle room for presidents, appointed leaders, and civil servants to exercise their own judgment. Whether intentional or not, whether charitably or not, each of these actors uses discretion. In human systems, that discretion is widely distributed across many individuals—people who, in the case of career civil servants, usually outlast presidencies.

Today, the AI ecosystem is dominated by a small number of corporations that decide how the most widely used AI models are designed, which data they are trained on, and which instructions they follow. Because their work is largely secretive and unaccountable to public interest, these tech companies are capable of making changes to the bias of AI systems—either generally or with aim at specific governmental use cases—that are invisible to the rest of us. And these private actors are both vulnerable to coercion by political leaders and self-interested in appealing to their favor. Musk himself created and funded xAI, now one of the world’s largest AI labs, with an explicitly ideological mandate to generate anti-“woke” AI and steer the wider AI industry in a similar direction.

But there’s a second way that AI’s transformation of government could go. AI development could happen inside of transparent and accountable public institutions, alongside its continued development by Big Tech. Applications of AI in democratic governments could be focused on benefitting public servants and the communities they serve by, for example, making it easier for non-English speakers to access government services, making ministerial tasks such as processing routine applications more efficient and reducing backlogs, or helping constituents weigh in on the policies deliberated by their representatives. Such AI integrations should be done gradually and carefully, with public oversight for their design and implementation and monitoring and guardrails to avoid unacceptable bias and harm.

Governments around the world are demonstrating how this could be done, though it’s early days. Taiwan has pioneered the use of AI models to facilitate deliberative democracy at an unprecedented scale. Singapore has been a leader in the development of public AI models, built transparently and with public-service use cases in mind. Canada has illustrated the role of disclosure and public input on the consideration of AI use cases in government. Even if you do not trust the current White House to follow any of these examples, U.S. states—which have much greater contact and influence over the daily lives of Americans than the federal government—could lead the way on this kind of responsible development and deployment of AI.

As the political theorist David Runciman has written, AI is just another in a long line of artificial “machines” used to govern how people live and act, not unlike corporations and states before it. AI doesn’t replace those older institutions, but it changes how they function. As the Trump administration forges stronger ties to Big Tech and AI developers, we need to recognize the potential of that partnership to steer the future of democratic governance—and act to make sure that it does not enable future authoritarians.

This essay was written with Nathan E. Sanders, and originally appeared in The Atlantic.

Posted on February 14, 2025 at 8:03 AM • View Comments

Third Interdisciplinary Workshop on Reimagining Democracy (IWORD 2024)

Last month, Henry Farrell and I convened the Third Interdisciplinary Workshop on Reimagining Democracy (IWORD 2024) at Johns Hopkins University’s Bloomberg Center in Washington DC. This is a small, invitational workshop on the future of democracy. As with the previous two workshops, the goal was to bring together a diverse set of political scientists, law professors, philosophers, AI researchers and other industry practitioners, political activists, and creative types (including science fiction writers) to discuss how democracy might be reimagined in the current century.

The goal of the workshop is to think very broadly. Modern democracy was invented in the mid-eighteenth century, using mid-eighteenth-century technology. If democracy were to be invented today, it would look very different. Elections would look different. The balance between representation and direct democracy would look different. Adjudication and enforcement would look different. Everything would look different, because our conceptions of fairness, justice, equality, and rights are different, and we have much more powerful technology to bring to bear on the problems. Also, we could start from scratch without having to worry about evolving our current democracy into this imagined future system.

We can’t do that, of course, but it’s still still valuable to speculate. Of course we need to figure out how to reform our current systems, but we shouldn’t limit our thinking to incremental steps. We also need to think about discontinuous changes as well. I wrote about the philosophy more in this essay about IWORD 2022.

IWORD 2024 was easily the most intellectually stimulating two days of my year. It’s also intellectually exhausting; the speed and intensity of ideas is almost too much. I wrote about the format in my blog post on IWORD 2023.

Summaries of all the IWORD 2024 talks are in the first set of comments below. And here are links to the previous IWORDs:

IWORD 2025 will be held either in New York or New Haven; still to be determined.

Posted on January 23, 2025 at 9:58 AM • View Comments

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Sidebar photo of Bruce Schneier by Joe MacInnis.