Did the internet let politics down, or did we? Eric sits down with his friend Katie Harbath, founder and CEO of Anchor Change and author of the new book Disrupting Politics: A Front Row Seat to the Collision of Technology and Democracy. Before spending a decade running global elections policy at Facebook, Katie built GOP.com, ran digital for Rudy Giuliani's presidential campaign and led digital at the NRSC, so she's watched this collision from both sides. Eric and Katie trace how real-time analytics pushed campaigns toward whatever got the most clicks, and why social media turned "villainous overnight" after the 2016 election. They also talk about the whiplash campaigns felt when the same tactics went from brilliant to sinister in just four years. Then they turn to AI, where the pendulum has swung the other way. Katie closes with two lessons from the book: good intentions are not safeguards, and panic responsibly.

Get the book: Disrupting Politics

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Almost everything written about AI and elections this cycle is about what it will do to voters. Paul Allen thinks the bigger story is what it can do for them. This week, Eric sits down with Paul, co-founder of Ancestry.com and founder and CEO of SOAR and Citizen Portal, who is applying the lessons of turning a huge unread archive into something personal to the records almost no one reads: local government meetings, ordinances and regulations.

They get into how Citizen Portal transcribes public meetings and links every AI-written story back to the tape; a "newspaper business in a box" meant to make one-person local newsrooms viable again; and why AI agents may be the only way clerks keep up with a flood of public records requests. Eric pushes on whether elected officials will welcome that kind of transparency or just find new places to hide — and Paul challenges the premise.

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This week, Eric Wilson is the guest. Right after Labor Day, Eric joined Prompt.io president Farz Sokhansanj on Prompt.io's Pulse Check webinar to take stock of where campaigns and technology stand heading into the midterms.

They cover the four kinds of Americans campaigns are trying to reach, and why only about 9% of them are the ones actually talking about politics. Whether 2024 really was the "podcast election," and why podcasts haven't worked down the ballot. How AI is showing up in this cycle's ads, and why it should be spice, not the whole meal. The 42% of Republicans in toss-up races who don't have an issues page on their website, even as AI search leans on those pages. Why over-targeting leaves votes on the table. What voters actually mean when they ask for a candidate who's "authentic." And why vendors need to be building case studies right now.

As Eric puts it: the winner isn't the person with the most views. It's the person with the most votes.

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Eric is joined by Dustin Tropp, founder of Republican Jobs, to unpack the 2026 Political Careers Survey — 427 political professionals on pay, benefits, and whether they're sticking around.

The headline finding: it's not the job that determines whether campaign work is a real career, it's the employer. Staff at a firm or committee report just 16% with zero benefits. Staff hired directly by a campaign? 64% with nothing. Same candidates, same work, wildly different security — and Dustin explains why campaigns can't fix it on their own.

They also get into why senior campaign hires are taking two to three months to fill this cycle, why hiring is shifting from March to November, what happens once a staffer crosses the $125K mark, and why field organizers — the least automatable job in politics — are still among the worst paid. Plus: what the survey found on AI (42% say it's changed how they work, only 12% see it as a threat), and why employers aren't paying for the extra output they're getting from it yet.

Dustin also shares real-time hiring data most surveys miss: 107 open roles, where the shortages are worst, and what he's telling clients about paying below-market rates.

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Can you trust a poll when no human ever picked up the phone? Eric sits down with Matthew Hanauer, co-founder of Civly, to unpack synthetic polling — building AI simulations of real, individually-modeled voters (using public voter file, demographic, and donation data) to predict how they'd respond to a survey. Matt walks through how Civly back-tests its models against real election results, why asking AI yes/no questions produces unrealistically extreme answers, why piling on more data (like social media) can actually make predictions worse, and how turnout modeling benefits from more than just "did they vote last time." Eric and Matt land on where AI polling actually fits into a campaign's toolkit in 2026: filling the gap for downballot races that could never afford a traditional poll, and pressure-testing messages before committing budget to the real thing.

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Opposition research has always rewarded whoever digs deepest. AI is changing who can afford to dig — and how much stays buried. This week, Eric Wilson sits down with John Artunkal, founder and CEO of Argus AI, who came to politics through open-source intelligence, trained by Bellingcat and schooled at Oxford in the social science of the internet.

They get into how AI is — and isn't — transforming the vetting business: digital footprint mapping, facial recognition, and linguistic forensics; why self-vetting is now table stakes for down-ballot candidates; and the trade-off every research tool has to make between flagging too much and missing the one thing that ends a campaign. John also makes the case that candidates shouldn't over-sanitize themselves. Voters reward authenticity — the job is knowing the difference between a rough edge and a career-ender.

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Everyone's worried about AI deepfakes in politics. Becki Wright says that's not the real story.

Becki, founder of Proximity and a former candidate and campaign manager, joins Eric Wilson to talk about what AI is actually doing in campaigns right now — mostly quiet, mostly mundane, and mostly happening on downballot races that can't afford a full-time staff. She breaks down the three failure modes of off-the-shelf AI tools (the sycophancy problem, the averaging effect, and hallucination), why voters are growing more suspicious of anything that smells AI-generated, and why the campaigns that get burned by AI are usually the ones that let it replace judgment instead of amplifying it.

Her bottom line: let AI handle scale and speed. Keep the human in the loop for everything else.

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Every pollster knows the problem: for every hundred voters you ask to take a poll, only one or two actually respond. So what if AI could just answer the questions for them? It's a seductive idea — and Ben Leff has put it to the test.

Ben is co-founder and CEO of Verasight, a survey research firm founded by academics and trusted by leading institutions and media organizations. He and his colleagues G. Elliott Morris and Peter Enns recently published a series of papers asking the question the industry is buzzing about: can AI digital twins replace human survey respondents? Their verdict, after rigorous real-world testing, is a firm — for now.

In this conversation with host Eric Wilson, Ben breaks down exactly what synthetic sampling is, how Verasight built and stress-tested it, and where it consistently fell apart. Ben sees a narrow lane where synthetic data could earn a legitimate spot in the toolkit — as a directional pre-screen, a quick and cheap starting point before committing to a full sample. But for anything requiring precision in close races, the humans still have to show up.

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