Practical AI – "How is AI Shaping Democracy?"
January 27, 2026
Host: Daniel Whitenack & Chris Benson
Guest: Bruce Schneier, Fellow at Berkman Klein Center, Harvard & author of "Rewiring Democracy: How AI Will Transform Our Politics, Government and Citizenship"
Episode Overview
This episode delves into the critical intersection of AI and democracy, exploring how artificial intelligence is both disrupting and potentially enriching political structures, policy, and citizenship around the world. Host Daniel Whitenack and co-host Chris Benson are joined by renowned security technologist Bruce Schneier to discuss his new book, “Rewiring Democracy,” with a focus on tangible, practical use cases (beyond just deepfakes), how power structures are shifting, and what the future may hold for citizens and practitioners alike.
Key Discussion Points & Insights
Why Focus on AI & Democracy?
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Bruce Schneier shares his motivation for zooming in on democracy and citizenship, rather than just corporate or financial AI uses.
“AI is going to affect kind of every aspect of society… And we can think about them in terms of companies and consumers and workers, but we also think of it in terms of citizens.” (02:29)
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The book "Rewiring Democracy" (co-authored with Nathan Sanders) addresses the breadth of AI’s impact on all aspects of democratic systems—not just superficial concerns like deepfakes.
How AI Touches All Parts of Democracy
Schneier outlines the five major areas covered in his book:
(04:42–08:12)
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AI & Elections:
- AI avatars for interacting with voters (e.g., Japan, Brazil)
- AI-driven campaign messaging, polling, and get-out-the-vote efforts
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AI & Legislation:
- AI tools to help draft and amend laws (e.g., models in France and Chile)
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AI in Government Administration:
- Using AI to streamline government operations, benefits assessment, and audits
- Patent office workflow optimization
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AI & the Courts:
- AI for efficient case scheduling (Brazil), term analysis for judges
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AI & Citizenship:
- Tools for civic engagement and advocacy
- AI as a means to help individuals make informed democratic choices
"We have examples from all over the world. This is not a US book." (08:11)
Beyond Deepfakes: The Misconceptions of AI’s Capabilities
(09:41–12:54)
- Most people's daily interactions with AI are “algorithmic feeds” and “map apps”—predictive, not generative or chat-based.
- The technologies evolve quickly, and the key is to always ask: "Compared to what?" when judging an AI’s suitability or risks.
Memorable Example:
“Doctors are terrible at writing up what happened in the ER... The hospital experimented with having an AI that passively listened...and wrote up this after-event report... It was orders of magnitude better. The doctors loved it.” (10:13)
AI as a Force Multiplier—For Good or Ill
(04:42–13:40)
- AI is a power-enhancing technology, taking the stance of its wielders (not inherently democratizing or authoritarian).
- Tech can centralize or decentralize power—the outcome depends on our choices and regulatory frameworks, not the tech itself.
Information, Free Speech, and the Real Problems
(12:54–16:23)
- Many perceived “AI problems” (like astroturfing, misinformation amplification) predate AI and reflect systemic issues.
- AI may exacerbate but rarely cause these problems; solutions are often political, not technical.
Example:
“Germany has had a system... for decades where the government summarized political parties for voters. Last year they experimented with a chatbot… Younger voters like that.” (14:37)
The Centralization of Power & Pathways Toward “Public AI”
(17:41–22:07)
- Current AI research is driven by resource-rich corporations, raising concerns about centralization.
- Schneier advocates for “public AI”—models developed outside the corporate profit motive (“not built on the profit motive, no illegally-stolen training material, no poorly-paid third-world labor” (19:48)).
- The recent public Swiss AI model (ETH Zurich) is highlighted as a successful case.
“There is nothing in the tech. These are corporate decisions… We can make other choices.” (21:39)
Building Grassroots AI Ecosystems
(22:07–27:22)
- US political and economic structures make large-scale public AI development difficult; elsewhere, nations (e.g., Switzerland, Canada, Singapore, France, Taiwan) are building models tailored to local needs and languages.
- As models become cheaper and more specialized, grassroots innovation is likely to accelerate.
Agents, Access, & Infrastructure
(27:22–31:53)
- True AI impact emerges from integration into real-world "agentic systems"—not just core models, but data, APIs, and how humans interact.
- Access gaps will persist; many will interact with AI systems unknowingly (embedded in apps, services, institutions).
- Predictive and task-based AI—often unheralded—powers much of the current value.
“Chatbots make the news, but it’s the non-chat AI that... does more things.” (31:44)
Case Studies: AI for Democratic Good
(33:17–37:48)
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Japan:
– Takehiro Anno used an AI avatar for campaigning; later elected, now uses AI for constituent engagement in parliament.“He is using AI to interact with his constituents… building tech tools for all of the Japanese parliament to use.” (34:32)
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California (CalMatters):
– Political watchdogs use AI to scan vast quantities of public records; AI highlights anomalies for journalists to investigate.“The AI says, hey, look at this. And then the human researches the story and sees if there’s a story there.” (35:30)
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Brazil:
– AI streamlines court case management, reducing delays and inefficiency.
“Still, that’s a story of more justice, more democracy.” (36:38)
The Coming Upheaval: Jobs, Inequality, & Social Change
(37:48–43:01)
- AI’s disruption is likened to the Industrial Revolution—impacting highly-paid professions and apprenticeships.
- Employment structures and the intrinsic value of work may need to be reimagined.
- Urges a separation between technological change and political failure:
“AI doesn’t cause the problems, but AI takes our existing problems and makes them worse.” (42:23)
- Discusses possible responses (massive retraining, UBI, divorcing health coverage from employment).
Power, Responsibility, and the Role of Practitioners
(44:43–47:03)
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AI developers and researchers still wield significant influence.
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Calls for a stronger moral compass among tech workers (reference to Google’s Project Maven walkout).
“I want us to be more of a moral compass. I want us to say, no, we’re not going to do this.” (45:00)
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Urges practitioners to think about broader social effects as the field evolves rapidly.
Notable Quotes & Timestamps
-
On AI as a Tool:
“AI is a power-enhancing technology. If you like democracy, AI will help you make democracy better. If you hate democracy, AI will help you make democracy worse.”
– Bruce Schneier (04:50) -
On Contextual AI Capability:
“When you say, is it good enough? The question is, compared to what?”
– Bruce Schneier (11:37) -
AI's Impact Isn't New:
“We come across the problems that AI exacerbates but doesn’t cause… the solutions… are not hard technically, they’re just hard politically.”
– Bruce Schneier (15:26) -
On Public AI:
“Nothing in the tech. These are corporate decisions… We can make other choices.”
– Bruce Schneier (21:39) -
On Coming Social Upheaval:
“This is going to be bad… This will be extraordinarily disruptive… If all the junior doers of the thing are AI, how does that pyramid even work anymore?”
– Bruce Schneier (39:41) -
On Tech Worker Responsibility:
“I want us to be more of a moral compass. I want us to say, no, we’re not going to do this.”
– Bruce Schneier (45:00)
Timestamps for Key Segments
- 02:29 — Why focus on democracy & AI?
- 04:42–08:12 — Five pillars of AI's impact on democracy
- 10:13 — Context-dependent AI effectiveness (ER example)
- 13:40 — AI & information/free speech dynamics
- 17:41 — Centralization of AI power & discussion on public AI
- 19:48 — ETH Zurich “public AI” example
- 27:22 — The rise of grassroots/public AI models worldwide
- 33:17 — Case studies: Japan, California, Brazil
- 39:41 — The looming societal disruption and employment change
- 44:43 — The moral imperative for AI practitioners
Takeaways for Listeners & Practitioners
- AI’s impact on democracy and society is deep, nuanced, and global.
- Tools and models reflect the power structures, culture, and politics of their creators—nothing is inevitable about centralization.
- While the risks of abuse and inequality are clear, so too are remarkable positive outcomes when AI is purposefully designed for public benefit.
- Professionals in AI and tech are uniquely positioned to drive change, demand ethical standards, and consider not just what can be built, but what should be.
Memorable Closing Thought
“Let’s try to make [new AI paradigms] benefit humanity rather than… a bunch of white male tech billionaires in Silicon Valley.”
– Bruce Schneier (46:58)
For more, check out “Rewiring Democracy” and Bruce Schneier’s ongoing work at the Berkman Klein Center.