When a voter, donor, or journalist asks a chatbot about a candidate, the answer they get is now part of the campaign. These papers make the case for treating that answer as a channel worth measuring and managing, the same way campaigns already treat television, mail, and the doorstep.
The numbered papers are our own work: the framework for where AI answers fit in campaign strategy, what they cost when they go wrong, and what can and cannot be fixed. The research studies and commentary that follow are the outside evidence, the independent studies and reporting that show this is real, measurable, and already happening.
We publish them because the field is new and the stakes are concrete. A campaign that understands how AI describes its candidate can act on it. One that does not, cannot.
Six papers, building in sequence. They start with the scale of AI's reach into the electorate, connect AI presence to the mechanics of persuasion, apply it to the organizations that endorse candidates, then turn to the economics: where AI answers fit in a campaign budget, what that return looks like, and where remediation stops working. Each paper assumes the one before it.
The outside evidence. Independent studies, several from major journals and research institutions, measuring whether AI actually moves voters, how much the public trusts it, and where people now go for political information. We did not run these. We cite them because the answers are not ours to assert. External links point to the primary source.
Reporting and practitioner perspective. Working journalists and political operators describing, in their own words, a problem they did not have a name for. Less rigorous than the studies above, closer to the ground.