Is ‘Universal Basic Capital’ the Solution to AI Job Loss?

Under one plausible theory of technological development, artificial intelligence will turn the economy into a dystopian split screen. As AI becomes capable of replacing an ever larger share of human work, the companies selling it will grow astronomically, turning a handful of investors and technologists into the richest individuals in human history while creating a permanent underclass of former workers replaced by machines.To head off that scenario and the consequences it could have for our political and social order, a growing number of figures in both Washington and Silicon Valley have begun advocating a policy idea known as “universal basic capital.” The specific proposals vary, but the basic intuition is simple: If the wealth generated by artificial intelligence will accrue only to the owners of AI companies, then the way to avoid catastrophic levels of inequality is to give everyone an ownership stake in those companies. The idea has been endorsed by figures as ideologically diverse as Bernie Sanders, Gavin Newsom, Steve Bannon, Sam Altman, and even Donald Trump.Designed the right way, the policy could provide a much-needed hedge against a future AI dystopia. It wouldn’t prevent workers from losing their jobs to machines, but it could guarantee that they share in at least some of the economic upside of the technology. Unfortunately, the version of the idea with the most momentum is very much not designed the right way. Were it to be implemented, it would invite its own kind of disaster.As the name suggests, universal basic capital is a new twist on a slightly older concept: universal basic income. Under a UBI scheme, the government would raise taxes on the profits of wealthy companies and then distribute the proceeds in the form of checks mailed out to every American. During the 2020 Democratic primary, Andrew Yang became a political celebrity by running a single-issue campaign devoted to implementing the policy before mass AI-triggered job loss.But massively