Book Review: Rewiring Democracy Offers a Nuanced Examination of AI’s Impact on Our Civic and Social Fabric
Readers need not be computer science graduates to understand the critical points being made. The result is a book that speaks to policymakers, civic technologists, and public servants without burying them in jargon.
Artificial intelligence has become perhaps the top buzzword of the decade. It has become impossible to walk a block without hearing an ad, seeing a sign on a bus, or eavesdropping into a conversation without noting the presence of OpenAI’s ChatGPT, Google’s Gemini, Anthropic’s Claude, or an offering from a Silicon Valley startup.
Evident in the latest round of layoffs in greater Seattle, eager Big Tech executives are plowing ahead on a dangerous course they’ve charted. It is exhausting to find ourselves, once again, being sold every moment of our lives by a faceless corporation.
Politics and the public sector have also found themselves in the AI slop era. From deepfake election ads to climate models and the environmental impact of sprawling data centers, there are implications to society from every facet of artificial intelligence.
In Rewiring Democracy: How AI Will Transform Our Politics, Government, and Citizenship, Bruce Schneier and Nathan E. Sanders look past the panic and hype to explore what AI actually means for the machinery of democracy itself.
Their premise asks us to shift our understanding of government and see it as a machine. To them democracy is, at its core, an information system. One that gathers the inputs of voters and converts them into the outputs of laws, policies, and norms.
AI, they argue, is about to change every stage of that process.
This framing feels particularly timely in the wake of scandals as far back as Cambridge Analytica illegally scraping social media profiles and more recent ethically dubious AI generated attack ads, as seen in the desperate attempt to smear Mayor-elect Zohran Mamdani on the campaign trail. AI is influencing politics already and Schneier and Sanders depict the steps we must all take to be prepared.
Despite its complexity, Rewiring Democracy is remarkably approachable. Schneier, a renowned security technologist and public-interest advocate, brings the clarity of a veteran explainer, while Sanders adds a data-driven, civic-minded grounding. The book is divided into seven sections, each exploring a different dimension of democratic life: politics, legislation, administration, courts, and citizens, among others.
What’s refreshing is what the authors don’t do: they skip the technical minutiae of how AI works and focus instead on what it does, primarily how it reshapes power, process, and participation. You do not need to be a computer science graduate to understand the critical points being made. The result is a book that speaks to policymakers, civic technologists, and public servants without burying them in jargon.
It’s a rare feat for a topic that could easily become impenetrably dense.
The book’s central thesis is its most compelling insight.
In that view, AI’s role is to amplify both the inputs and outputs of the information system: helping citizens better understand policies, making feedback loops faster, and enabling governments to interpret public sentiment at scale.
It is decidedly positive in its messaging and relays a sense of cautious hope.
The authors describe AI as a "power-magnifying technology" that is neither inherently good or bad, but capable of strengthening whoever wields it.
In their analysis, that can mean public institutions that use AI to process feedback or deliver services more effectively. It can also mean corporations and political operatives exploiting it to manipulate voters or distort public discourse. The difference depends on governance, transparency, and accountability.
That tension runs throughout the book. As someone who has tried to contact elected officials only to have messages disappear into a staff inbox, the idea of AI systems that synthesize constituent input feels appealing. If an algorithm could translate public sentiment into something digestible like data-driven "one-pager" for lawmakers it could genuinely democratize voice. But, as the authors note, augmentation means little if it doesn’t address the deeper dysfunctions of representation itself.
To explain AI’s transformative potential, Schneier and Sanders introduce four pillars: scope, scale, sophistication, and speed. Each represents a way AI can expand government capacity by handling more complex policy modeling, managing broader datasets, or accelerating service delivery.
This framing works. The authors convincingly describe a government that could someday match the efficiency of the best firms in our private sector, even as it upholds democratic accountability. Anyone who’s ever wrestled with a malfunctioning public website (or the user experience of filing a permit online) can appreciate the appeal. If AI can make essential services not just faster but fairer, it would be a genuine boost to our public goods.
If there’s a flaw in Rewiring Democracy, it’s that its optimism sometimes outpaces its realism. Schneier and Sanders are forthright about past technological missteps and human fallibility, but their proposed solutions can feel more aspirational than achievable. Overturning Citizens United, regulating AI comprehensively, and deploying vast new accountability systems are wildly ambitious.
The idealism glosses over the entrenched political inertia and corporate influence that make such sweeping changes unlikely.
Schneier and Sanders acknowledge these structural obstacles, but their confidence in the system’s ability to correct itself feels more aspirational than practical.
To truly embrace the power of AI in a way which benefits working people there must be a massive undertaking to ensure ethical and moral guardrails are in place.
That said, Schneier and Sanders don’t surrender to techno-utopianism. They repeatedly emphasize that humans must remain at the helm. Time and again they emphasize AI should assist, not replace, human decision-making in most cases to uphold accountability. Most instances, they argue, require nuance when weighing adoption against replacement. Where accountability is required, a human must make the final call, acting more as an editor than an employee; a safeguard against AI-driven mistakes.
Interestingly, the authors suggest that human error is often more random and opaque than algorithmic error. When an AI makes a mistake, it at least leaves a trail; its logic can be traced, its parameters understood, it can be fixed. That transparency, paradoxically, could make some forms of accountability easier in an AI-assisted government.
To address these challenges, Schneier and Sanders outline a four-part strategy for guiding AI toward democratic purposes. They call for:
- resisting harmful or unethical applications of AI, such as manipulative political advertising or unchecked surveillance;
- responsibly using AI to enhance public services and accessibility;
- reforming the broader AI ecosystem through the creation of a publicly governed "Public AI" infrastructure designed for transparency and civic trust rather than profit;
- and renovating democratic institutions to better manage both the risks and opportunities of this technological shift.
It’s a compelling vision that is ambitious, comprehensive, and something in which we must strive for regardless of AI outcomes.
The book balances solid empirical grounding with creative speculation. Early chapters anchor AI in familiar territory. Automated campaign outreach, regulatory monitoring, legislative drafting are not necessarily new but later chapters venture into imaginative futures. What might AI-assisted negotiation or jurisprudence look like? How might algorithms mediate public deliberation? These questions make the book not only informative, but provocative.
By structuring the analysis around discrete civic functions like politics, legislation, administration, courts, and citizens the authors make a sweeping topic feel navigable. Rather than diluting their thesis, this compartmentalization strengthens it, giving readers practical anchors for reflection.
Ultimately, Rewiring Democracy envisions a future of stronger state capacity, smarter regulation, and more participatory citizenship.
Schneier and Sanders don’t see AI as a threat to democracy but as a mirror thus reflecting both its possibilities and its dysfunctions. If governments use AI to reduce friction between services and citizens while maintaining transparency and oversight, it could help rebuild public trust in institutions and the technology that got them there.
But the authors also acknowledge that AI cannot solve political decay.
It can process information faster, but it can’t fix apathy, polarization, or systemic barriers that keep representatives unresponsive or at the behest of corporate donors.
That’s another sobering insight from this book: technology may amplify democracy, but it cannot substitute for the human values that sustain it.
Rewiring Democracy succeeds in reframing how we think about the intersection of technology and governance. It’s thoughtful, forward-looking, and, despite occasional overconfidence, refreshingly humanistic. For readers in public service, civic tech, or policy, it offers both a warning and an invitation: AI is coming for our institutions, and it’s up to us to decide whether it strengthens or weakens them.
If nothing else, Schneier and Sanders remind us that democracy has always been a collaborative experiment in information processing. The question now is whether we can update its code without crashing the system.
Categories: Book Reviews, Rewiring Democracy, Text