Human-centered redistricting automation in the age of AI
Abstract
Redistricting—the constitutionally mandated, decennial redrawing of electoral district boundaries—can distort representative democracy. An adept map drawer can elicit a wide range of election outcomes just by regrouping voters (see the figure). When there are thousands of precincts, the number of possible partitions is astronomical, giving rise to enormous potential manipulation. Recent technological advances have enabled new computational redistricting algorithms, deployable on supercomputers, that can explore trillions of possible electoral maps without human intervention. This leaves us to wonder if Supreme Court Justice Elena Kagan was prescient when she lamented, “(t)he 2010 redistricting cycle produced some of the worst partisan gerrymanders on record. The technology will only get better, so the 2020 cycle will only get worse” (Gill v. Whitford). Given the irresistible urge of biased politicians to use computers to draw gerrymanders and the capability of computers to autonomously produce maps, perhaps we should just let the machines take over. The North Carolina Senate recently moved in this direction when it used a state lottery machine to choose from among 1000 computer-drawn maps. However, improving the process and, more importantly, the outcomes results not from developing technology but from our ability to understand its potential and to manage its (mis)use.
- Publication:
-
Science
- Pub Date:
- September 2020
- DOI:
- 10.1126/science.abd1879
- Bibcode:
- 2020Sci...369.1179C