Tag: Redistricting

A Project of Many Parts

Posted on by Jerry Cayford

by Jerry Cayford

Tom Suozzi, Brian Fitzpatrick; credit: US Gov

I was going to take a break from the topic of redistricting, which has been my main focus for 2026. But then big news happened: the House Problem Solvers Caucus announced on July 1 that they have established a gerrymandering reform framework and a working group to develop legislation to end gerrymandering permanently. They explicitly list “algorithmic mapping”—what I advocate—among the reforms they would support. The Problem Solvers are a militantly bipartisan caucus, which is an important advantage for them in the election reform struggles, which I will get to below. Since not everyone may understand why this announcement is big news, I decided that a summary of the overall redistricting project would be useful: its landscape, parts, and players.

My desired endpoint in this project is national legislation mandating a single algorithm that determines all district boundaries for federal offices. (Why this is the right goal is the subject of my earlier article “Resist, Adapt, Redistrict.”) Many different groups will have to collaborate to reach that desired point. Politicians propose and pass legislation. Their staffs need academics and technical experts to produce plausible algorithms and a consensus as to which one is best. Advocacy groups mobilize support among the public and politicians. Lawyers and legal scholars refine legislation to minimize the court challenges that inevitably arise. Some of these groups will not be able to perform their functions without funding from philanthropic organizations supportive of the end goal. All of these actors influence each other; each category contains factions within it that have competing ideas; and the algorithmic redistricting that I propose is a relatively new concept to all of them.

That is a rough sketch of the terrain. Add in some dynamic factors—the gerrymander war; Supreme Court hostility to racial districting; the increased power of big data computing to game the electoral system—and you can see the forces and the resources that this project for algorithmic redistricting has to manage to end gerrymandering. Read more »

Tuesday, March 24, 2026

How Reform Fails

Posted on by Jerry Cayford

by Jerry Cayford

Hugo Sundström, CC BY 4.0, via Wikimedia Commons

“Failure is the foundation of success, and the means by which it is achieved,” says the Tao Te Ching. The current competition between our two parties to gerrymander the country—Texas, California, Virginia, Florida—is a stunning failure for democracy reform efforts. Gerrymandering transfers power from the people to the parties, and Americans hate it. By the time this year’s mid-term elections are over, huge numbers of us will have representatives who, we feel, don’t represent us and won unfairly. Many of us will live in states without a single official in Congress from our own party. Nevertheless, we all support this district grab, because we can’t let the other party seize power by gerrymandering more districts than we do. Where are the means to success in failure this big?

Spilt Milk

No one is feeling more defeated than the good-government activists who have worked so long to end gerrymandering and make our elections more fair. The need to respond to extreme gerrymanders has forced them to support the torching of their own work. They are “backpedaling furiously,” as one such activist bluntly puts it: “Decades of reformer work is going up in smoke.” Renewing forward movement will require understanding what happened. Alarmingly, there are signs that the reform community will learn nothing, that it will interpret this defeat as an aberration rather than a refutation of its past work and will return stubbornly to its failed strategy. A different response to failure, though, could build a foundation for success.

What the reform community appears to be overlooking is the golden opportunity this ugly war to gerrymander everything actually presents. It is the opportunity not only to formulate a better strategy, but also to use the power of public anger to solve the problem of creating fair districts once and for all. Redistricting has been mostly a wonkish, back-burner issue, briefly irritating to the public from time to time, but never before commanding the intensity of concern it does now. Right now—with huge amounts of money, political power, and public outrage all focused on gerrymandering—now is when reform can succeed. Read more »

Monday, November 27, 2023

Gerrymander Unbound

Posted on by Jerry Cayford

by Jerry Cayford

Avi Lev, CC BY-SA 4.0, via Wikimedia Commons

A friend of mine covers his Facebook tracks. He follows groups from across the political spectrum so that no one can pigeonhole him. He has friends and former colleagues who, he figures, will be among the armed groups going door to door purging enemies, if our society breaks into civil anarchy. He hides his tracks so no one will know he is the enemy.

That trick might work for the humans, but artificial intelligences (AI) will laugh at such puny human deceptions (if artificial intelligence can laugh). When AI knows every click you make, every page you visit, when you scroll fast or slow or pause, everything you buy, everything you read, everyone you call, and data and patterns on millions like you, well, it will certainly know whom you are likely to vote for, the probability that you will vote at all, and even the degree of certainty of its predictions.

All of that means that AI will soon be every gerrymanderer’s dream.

AI will know not just the party registrations in a precinct but how every individual in a proposed district will (probably) vote. This will allow a level of precision gerrymandering never seen before. There is only one glitch, one defect: with people living all jumbled up together, any map, no matter how complex and salamander-looking, will include some unwanted voters and miss some wanted ones. To get the most lopsided election result possible from a given group of voters—the maximally efficient, maximally unfair outcome—the gerrymanderer has to escape the inconvenience of people’s housing choices. And since relocating voters is not feasible, the solution is to free districts of the tyranny of voter location. The truly perfect gerrymander that AI is capable of producing would need to be a list, instead of a map: a list of exactly which voters the gerrymanderer wants in each district. But that isn’t possible. Is it? Read more »