Governments have struggled to find a tax formula that promotes prosperity without creating extremes of wealth and poverty. Can machine learning show the way?
What’s new: Data scientists at Salesforce used reinforcement learning to develop a tax policy aimed at optimizing worker productivity and income equality.
How it works: The researchers developed a video game-type simulation in which four reinforcement learning agents worked to earn money while a fifth taxed their income.
- None of the agents had prior knowledge of the game’s economy. The workers were instructed to build wealth by either harvesting resources or building homes.
- Each virtual worker had a different skill level. The lower-skilled workers learned that acquiring and selling wood or stone was the best way for them to make money, while their higher-skilled colleagues gravitated to the more complex, higher-paying task of building houses.
- Each game ran through 10 tax periods. At the end of each period, the tax bot took a portion of each worker’s earnings, then redistributed the money among all the workers. The process was repeated millions of times.
- The researchers also tested the simulation under three human-created tax strategies: A free market approach, the current U.S. tax code, and an academic tax proposal favoring higher income equality.
Results: The system optimized the balance between productivity and inequality more effectively than the human-created strategies. Its policy counterintuitively set high tax rates for the highest and lowest earners and assigned the lowest rates to middle earners.
Yes, but: A model with four workers isn’t nearly complex enough to simulate a real economy, Blake LeBaron, an economist at Brandeis University told MIT Technology Review. The Salesforce team plans to scale up the system to 100 workers.
Why it matters: More than 70 percent of the world’s population live in nations where income inequality is rising, according to the United Nations. Tax policy is a powerful tool for building more prosperous, resilient economies.
We’re thinking: Using AI to discover good social policies? Great idea! Imposing high tax rates on the lowest earners? Not so much.