Gerrymandering is a really scary thing when you add 'big data' and AI to the mix
By Robert Pembroke
The other night Catherine Kanter scared the bejesus out of me. Kanter is the campaign manager for Better Boundaries, which is a nonpartisan group that is dedicated to eliminating gerrymandering in the state of Utah.
Gerrymandering has been around for a long time in America. Prior to the Constitution even taking effect, Gov. Patrick Henry of Virginia persuaded his legislature to remake a congressional district that forced his political enemy, James Madison, to run against the very popular James Monroe. Madison still won the congressional seat despite Henry’s nefarious actions.
The word "gerrymander" means to make political districts in such a way that it favors a particular politician — and both of our political parties do it. The word itself was coined in 1812 because of an action by then-Massachusetts Gov. Elbridge Gerry, who created a congressional district that looked like a salamander. When I looked at the map that created this new congressional district, it looked like it was a sea monster that I had seen at Hebgen Lake, Montana.
What really got my attention, at this function that my wife had dragged me to, was when Kanter brought up the phrase “big data” in her talk. She described how both political parties were using big data to draw these gerrymandered districts that favored their candidate. In my business background, I have had some experience with interpreting and managing big data files. This tool in the hands of a politician is dynamite.
As Kanter remarked, data mining software programs can find out what magazines you read, whether or not you have a dog or a cat, whether you’re a registered Democrat or Republican, what you are looking at on the Internet and all sorts of other things that will predict the way you will vote. Now the political powers can just push a few buttons and produce a map of the district that guarantees a winner for their politician.
I personally believe that gerrymandering is unconstitutional, but the Supreme Court has yet to rule that it is. There is a case before the Supreme Court right now that will clarify the issue. But what if the Supreme Court continues to not take a definitive position on this issue? Well, I believe that what Kanter and her nonpartisan group, Better Boundaries, is doing not only makes sense but is a better long-term answer even than a favorable Supreme Court ruling.
Better Boundaries is trying to get an initiative before the Utah electorate in 2018 that forces the Utah Legislature to make changes to Utah’s election law that will take a lot of the partisanship out of redistricting. Better Boundaries’ solution is not a panacea, but it is a step in the right direction. If you want more information about the specifics of their proposal, go to their website, www.betterboundaries.org.
Now back to this phrase “big data” and what really is scary is when you add “artificial intelligence” (AI) to the mix. I have begun to piddle around with AI in one of my projects and from my limited knowledge, I know that this software will be constantly tracking what you’re up to and will be constantly learning how to be a better predictor of the way you are going to vote.
In the question-and-answer section of her talk, Kanter was asked if there are any Republicans on her board of directors and she replied, “yes” and named two of them. I kind of have to chuckle that there were some people in the audience that thought that this might be a Democratic Party trick. Well, you bet it is — but more power to them.
Kanter had one slide in her presentation that really got my attention: “Voters should choose their politicians; politicians should not choose their voters.” Technological advances are an excellent way to improve the lives of everyone, but using big data and AI to gerrymander the system is not one of them.
Robert Pembroke is chairman of Pembroke’s Inc. and considers himself on permanent sabbatical. He can be reached at pembroke894@gmail.com.