Why Noise
The immediate aftermath of the 2024 presidential election saw many Democratic strategists questioning the worth of their industry. Despite massive fundraising, a highly experienced and enthusiastic ground game, and the most sophisticated analytics for targeting and messaging, the country moved drastically rightwards, toward an aging, incoherent, twice-impeached, convicted felon.
Many post-mortems have questioned: How do Democrats break through the noise and get their message through the background? At Blue Noise, we are asking a different question: How can Democrats create the noise? How can we make our issues the issues that permeate the electorate?
How do we fight elections on our terms?
The goal of a campaign is to resonate with the electorate. But in many physical systems, resonance is only achieved at some level of optimal noise. We want to create that aether.
About Me.
I’ve been working adjacent to politics since the 2020 election, when I took a leave of absence from my PhD to work at BallotReady. I spent the next four years leading a data science team at MissionWired, helping to build the premier digital fundraising machine learning models that have helped Democrats build the war chests they need to win tight elections. I’ve worked with Data for Progress to analyze polls for the 2022 midterm elections and volunteered with Tech for Campaigns to help Michigan state representative Denise Mentzer win a tight re-election.
My previous life was an aspiring mathematician: I designed algorithms for representing high-dimensional data efficiently and with as little distortion as possible. You can find my PhD dissertation and Google Scholar page to see my research interests.
If there were a single theme in my career, it would be breadth. Working in the liminal space between fields puts a premium on communication and translation: understanding the problems in one field, translating those problems (and just as importantly, the intuition of experts) into math, and then back.
Political work has been the ultimate interdisciplinary challenge. There’s a deluge of data but only a handful of elections where methods can be validated, and so working closely with campaign experts is the most important skill for a data scientist. Since the 2024 election, I have devoted myself to fight against our instinct towards the McNamara Fallacy: how can we use math to solve the hardest questions in strategy rather than only posing questions that existing methods can answer?