The AI Daily Brief: Artificial Intelligence News and Analysis
How AI Can Help Democracy Work Better
28 Mar 2026
Chapter 1: What is the main topic discussed in this episode?
Today on the AI Daily Brief, how AI can help democracy work better. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. All right, friends, quick announcements before we dive in. First of all, thank you to today's sponsors, KPMG, Robots and Pencils, Blitzy, and Super Intelligent.
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Chapter 2: How is AI influencing political discourse today?
If you are interested in sponsoring the show or want to know really anything else about the broader AIDB ecosystem, check it out at aidallybrief.ai. All the fun things we've got cooking are always going to be listed there. Now today we are doing something which I hope to be able to do a lot more of in the months to come.
It is quite clear at this point that AI is rising in significance as a broader societal and political issue. More and more people are understanding that it's going to impact them at work, impacts at work are understood to be impacts on the economy, and things that impact the economy are understood to be political inherently, whether we'd like them to be or not.
Now, in this climate, a lot of the reactions and emergent political discourse is quite negative. It's increased chatter about x-risk, declarations and proposals for moratoriums on data centers. And even among those who reject those policies, it sometimes feels like every day a new politician pulls a new number out of a hat to get press for how many people they think that AI is going to employ.
And yet, believe it or not, not everyone is so dreary about what AI can mean for the world. I think it's likely that as the negative discourse increases, we also start to see some voices emerge who are telling a different story. Now, as you well know, we have these long reads slash big think type episodes every weekend, which is a great chance to highlight some of those voices.
Today, we are doing a good old-fashioned actual long read, reading a piece from Stanford professor Andy Hall. Andy wrote an essay that we are going to read a number of excerpts from called Building Political Superintelligence. and he introduced it on Twitter in this way.
He writes, Amidst understandable concerns of AI dystopia, no one is offering a positive vision for how we can use AI to remake our institutions and reinvent how we govern. That's what I try to offer today. My argument is that we need an explicit research agenda to build political superintelligence.
The window for building these structures is narrow, and the right response is not to slow AI down, but to speed up how fast we build the institutions that keep us free as AI grows more powerful. He ends his tweet with the quote that actually begins his essay. As Thomas Paine wrote in 1776, we have it in our power to begin the world over again.
So let's read what Andy is arguing about how we should think about the opportunity for AI and, as he calls it, political superintelligence. Andy writes, Right now is a weird time to be a political economist. AI is straining our already brittle political institutions.
We might lurch into a dystopia in which we live in the grips of a techno-leviathan, forced by our employers to train our own AI replacements, then kick to the curb in a society organized to the benefit of a tiny number of people who control the machinery that controls the world. It's also an electric time to be a political economist.
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Chapter 3: What is the concept of political superintelligence?
Some of his suggestions for a concrete research agenda include better evals for how AI handles political questions. Importantly, Andy argues that this is something that political scientists should be working on. Second, he suggests using geopolitical forecasting as a hard test case.
He writes, If we can get AI to predict geopolitical problems and do well trading in prediction markets, that would be strong evidence that we're achieving high degrees of political reasoning.
Third, and maybe obviously, he argues we need to get AI access to the best news sources, specifically saying we need to study ways to create new economic models that give journalists and news outlets a way to make money while making their content available to AI. And finally, he suggests building AI for policymakers.
The best way to improve AI, he argues, is to try it out in important environments, see how it goes, and iterate. Which brings Andy to layer two, the representation layer. He continues, By making information cheap and distributing it far and wide, the printing press didn't only make people smarter, it actually changed the political equilibrium.
With more people understanding more about politics, government had to evolve.
Reflecting on the path from the printing press to the Enlightenment to the American Revolution, Condorcet again marveled at the, quote, example of a great people throwing off at once every species of chains and peaceably framing for itself the form of government and the laws which it judged would be most conducive to its happiness.
Now, importantly, Andy argues that Condorcet did not just credit this to a change in attitudes among the people, but also the use of political science and the study of politics to improve governance. And this is the theme that Andy picks up next. We all know that representative democracy is imperfect. We don't have time to get super informed about what our representatives are up to.
This frees them up to pursue their own ends, to follow their own ideology instead of ours, or to make deals with special interests. or to grandstand and prioritize flashy things that sound good to inattentive voters but don't actually improve our welfare or simply to get lazy.
Political superintelligence might help solve this monitoring problem by giving each of us a tireless, automated delegate always serving us in the political sphere. Seb Krier, the AGI policy dev lead at Google DeepMind, just talked about this idea, which he called advocate agents. Coming back to Andy, he continues, the possibilities are extraordinarily broad.
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Chapter 4: How can AI enhance citizen engagement in democracy?
I think model competition matters. I think we're going to see a lot more model sovereignty over time. And I think basically the model companies will eventually have to look a lot more like public utilities than they do today, where at least the intelligence that they're serving, the models themselves in other words, are bought and consumed and distributed very differently.
than the way we think of SaaS products today, for example. Already, even as this agent inflection takes hold, the fact that we have this open alternative in OpenClaw, which yes, of course, relies theoretically on the model companies, but which can move in and out of models as the owners so choose, already shows that there is going to be a counterweight to the pure centralization.
Anyway, like I said, the big point is not any one of these thoughts. It's the collection of them and what they represent in terms of where I hope the discourse goes. I'm excited to see folks like Andy thinking through these things and writing these pieces, and I will continue to highlight them as they come up on this show.
For now, that is going to do it for today's AI Daily Brief, a true Long Read Sunday edition. Appreciate you listening or watching, as always. Until next time, peace.