Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: "Heretical Thoughts on AI" by Eli Dourado, published by DragonGod on January 19, 2023 on LessWrong.

Abstract

Eli Dourado presents the case for scepticism that AI will be economically transformative near term.

For a summary and or exploration of implications, skip to "My Take".

Introduction

Fool me once. In 1987, Robert Solow quipped, “You can see the computer age everywhere but in the productivity statistics.” Incredibly, this observation happened before the introduction of the commercial Internet and smartphones, and yet it holds to this day. Despite a brief spasm of total factor productivity growth from 1995 to 2005 (arguably due to the economic opening of China, not to digital technology), growth since then has been dismal. In productivity terms, for the United States, the smartphone era has been the most economically stagnant period of the last century. In some European countries, total factor productivity is actually declining.

Eli's Thesis

In particular, he advances the following sectors as areas AI will fail to revolutionise:

Housing

Most housing challenges are due to land use policy specifically

Housing factors through virtually all sectors of the economy

He points out that the internet did not break up the real estate agent cartel (despite his initial expectations to the contrary)

Energy

Regulatory hurdles to deployment

There are AI optimisation opportunities elsewhere in the energy pipeline, but the regulatory hurdles could bottleneck the economic productivity gains

Transportation

The issues with US transportation infrastructure have little to do with technology and are more regulatory in nature

As for energy, there are optimisation opportunities for digital tools, but the non-digital issues will be the bottleneck

Health

> The biggest gain from AI in medicine would be if it could help us get drugs to market at lower cost. The cost of clinical trials is out of control—up from $10,000 per patient to $500,000 per patient, according to STAT. The majority of this increase is due to industry dysfunction.

Synthesis:

I’ll stop there. OK, so that’s only four industries, but they are big ones. They are industries whose biggest bottlenecks weren’t addressed by computers, the Internet, and mobile devices. That is why broad-based economic stagnation has occurred in spite of impressive gains in IT.

If we don’t improve land use regulation, or remove the obstacles to deploying energy and transportation projects, or make clinical trials more cost-effective—if we don’t do the grueling, messy, human work of national, local, or internal politics—then no matter how good AI models get, the Great Stagnation will continue. We will see the machine learning age, to paraphrase Solow, everywhere but in the productivity statistics.

Eli thinks AI will be very transformative for content generation, but that transformation may not be particularly felt in people's lives. Its economic impact will be even smaller (emphasis mine):

Even if AI dramatically increases media output and it’s all high quality and there are no negative consequences, the effect on aggregate productivity is limited by the size of the media market, which is perhaps 2 percent of global GDP. If we want to really end the Great Stagnation, we need to disrupt some bigger industries.

A personal anecdote of his that I found pertinent enough to include in full:

I could be wrong. I remember the first time I watched what could be called an online video. As I recall, the first video-capable version of RealPlayer shipped with Windows 98. People said that online video streaming was the future.

Teenage Eli fired up Windows 98 to evaluate this claim. I opened RealPlayer and streamed a demo clip over my dial-up modem. The quality was abysmal. It was a clip of a guy surfing, and over the modem and with a struggling CPU I got about 1 fra...