The American worker is on a productivity tear and it may have more to do with a surge in working from home than the effects of AI, according to a Stanford economist.
For the past five years, the output for non-farm businesses has increased by a sizable 2% per year, The Economist reported citing statistics from the Bureau of Labor Statistics. This is a marked increase from the 1% productivity growth per year that defined most of the 2010s, and a trend that has taken even Federal Reserve Chairman Jerome Powell by surprise.
Yet, while the hype around AI over the past several years makes it a logical candidate for the main driver behind the productivity boom, Nicholas Bloom, a Stanford economics professor who is known for explaining the Great Resignation of the early 2020s, says it’s more likely work-from-home policies since the pandemic are fueling the trend.
But think about it from the business’s perspective!
lower rent
lower utilities
distributed IT
all employee work online/archivable by default
happier/healthier employees
access to global talent pool
easier to replace employees with LLMs!
The rabid return to office push is what really convinced me that most businesses are not in the hands of people who are trying to Do their business the best. At minimum it’s extrovert CEOs, and feckless middle managers that didn’t want to adapt
Their investors also have lots of money stuck in commercial real estate. And everyone knows golden egg geese are only good to bail out failed investments.
The lower rent point is one of the problems. Many of these businesses own the real estate or lease for many years at a time. If the space is 70% unused, that increases costs and looks bad.
Turning out the lights would help, but how does an unused building increase costs? There is for sure minimum cost to maintain the building for sake or later use, but unless they’re giving remote employees stipends for home office space, it should still cost less than back to work.
The big problem is still managers that want to feel important or intimidate underlings, and the same managers who have no clue how to measure productivity. Code line commit counts being a prime example.