Uber burst onto the scene as a “major transportation disruptor,” vowing to eliminate private car ownership, introduce self-driving vehicles, and revolutionize transportation. But first, they needed to illegally break up a taxi cartel, providing massively subsidized car services in locations and at times that could not possibly be profitable. They also needed to screw workers.
A decade later, ride-sharing hasn’t evolved significantly since its launch. Costs have risen as consumers now pay the actual marginal cost of their rides. hasn’t undergone a transformative shift, but we do have a slightly better taxi system.
In a conversation with my friend Jake today, it struck me that the current landscape of “AI” mirrors this trajectory. The current crop of large language models are promising to disrupt work and change the whole world. It’s cheap for end users due to massive subsidies. Models are being built off of likely illegal practices.
In ten years, I expect that LLMs won’t be that much more useful than they are today. Using these AI services will be much more expensive, because we will no longer have queries massively subsidized. Work won’t have changed that much, but some select jobs and industries will be permanently impacted. We will end up with marginally better technology. We probably could have achieved similar outcomes without breaking the law, with less negative impact on workers, and less wealth creation and destruction. 1
Because there will be a boom and bust as Silicon Valley moves capital to fuel a new bubble. Although, this time, it seems established companies may fuel investment as much as venture funds. ↩︎