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Monday, July 10, 2023

Artificial Intelligence vs. Hayek: Can an AI Best a Market Economy?

Can an AI overcome market imperfections without sacrificing the enormous benefits markets bring?

There are some good considerations of this question. For example James Pethokoukis (also here), and also Byrne Hobart expands on one of the arguments Pethokoukis makes.

I think the major problem with these analyses is that they're not imaginative enough. Pethokoukis focuses mostly on current LLMs and that they don't have the huge amount of information to be able to coordinate a market. That's absolutely true, but the question is whether an AI that has or could potentially have that information, and with it, could produce better results.

The Main Argument Against an AI Central Planner

Hayek's original argument against a command economy was novel and powerful: a central planner has to simultaneously act on the preferences (revealed and unrevealed) of every consumer, the production technologies available, the labor force available including skills, and the availability of resources. No person, or even a group of people can know anything close to enough to achieve this, and realize that they'd need to be doing this continuously, every second of every day forever.

But to be more precise, Hayek argued that prices of goods and services represent all the knowledge above, pulled up by scarcity and consumer preferences, and pulled down by other products and availability. We don't think of prices as dynamic representations of all of this information, but they are.

The question becomes whether an AI could have as much information as is contained in a price, and even more interestingly, could it have enough information to allocate goods even better than a market system. The answer to the former question, in theory, I believe is yes. Can you imagine a simulation of Earth that is an exact replication of Earth, including the resources, humans, and the human preferences? Considering AI can surely surpass human intelligence, I don't see, in theory, why this would not be conceivable.

But if the answer to that question is no, the next question becomes, can an AI get close enough? Imagine it has data on every exchange for the past fifty years, and every person that was part of the exchange, every parameter of the exchange. Could it create a model from that that would be 99% accurate going forward? 90%? 75%? How close do you think it would come?

The Argument For an AI Central Planner

Now, you should realize that as amazing as prices are, they are not perfect. They don't encompass all information. For one, consumers aren't all-knowing. They probably don't know that there's a sale on a product somewhere where they could obtain a good more cheaply. They may not know there's a good that they might prefer, at a higher price. And getting more complex, even if they did know the availability and price of every possible iteration of what they're looking for, they don't spend days calculating what combination of purchase + shipping would be cheapest to them.

Prices do not encompass all information, and hence, can be improved upon.

That's an example of how AI could improve allocation from a market system. In addition to that, consumers have biases that AI could circumvent. Maybe a person hates Amazon because it reminds them of the rainforest and they despise humidity. AI could suppress where the good was coming from. Perhaps someone dislikes a particular brand because their great grandparent had a bad experience.

Perhaps an AI could not exactly replicate the prices in a free market because it couldn't possibly determine all of the many factors that get, but the real question at issue here is how close an AI could get to replicating the a market allocation and if the problems it could solve in the current allocation would be enough to produce an even better outcome.

Some Other Interesting Things to Consider with an AI Central Planner

• Would we still need "discovery" processes for new goods? What about marginal value of money and goods?
• Would there need to be prices at all?
• How would careers work? Would you need to work? Would you need a salary? Would you choose or would AI choose for you? Would AI choose a set of options, or a career "path"?
• Several have pointed out the complication that the more sophisticated an AI is, the more sophisticated it makes the world and the more complicated it will be to find an optimal path for its denizens.

Friday, February 3, 2023

When Competition Goes Wrong

A recent paper provides a good example of how most people's view of competition, and the benefits it produces is slightly flawed. Understanding these examples helps ensure that competition is applied correctly. In the paper, researchers learn that as more health providers were allowed to prescribe treatment, more treatments, specifically opioids, were overprescribed to the point of harming patients. If you think about this for a moment, you realize it is because the competition between health providers was driving them to provide what consumers wanted--more opioid prescriptions. So, this is a case where competition is harmful, but it helps elucidate what competition actually does.

Many people think competition produces low costs, low prices, high quality goods and services and is unconditionally beneficial, but what competition actually does is push producers and sellers toward whatever the consumer desires. For most goods and services the desires of the consumer are beneficial to her and to society: high quality, low price cars, groceries, homes, computers, etc. In the case of opioids and other products that are beneficial in limited quantities yet are harmful in higher quantities, competitive forces benefit neither. This is due to the addictive nature of opioids. Consumers desire more than is good for them and so competition among providers results in what those consumers mistakenly desire.

Vehicle Inspections

This phenomenon is not limited to opioids. When I was in graduate school, I learned this concept from a fellow student whose Ph.D. thesis analyzed vehicle emissions inspections. He found that more inspectors led to more cheating. The reason was the same. While the inspectors were meant to be acting as agents of the state, their true customers were the vehicle owners. The vehicle owners' goals were not to have low emissions but to get a Pass from the inspector and so the more inspectors there were, the more they were driven to give consumers what they wanted to the detriment of state regulations.

News Media

The history of media consumption in the United States is an extremely illustrative example of this. From the advent of television until the 1990s, there were a handful of broadcasters vying for ratings. Up until the expansion brought on by cable, they fought with each other to appeal to the broadest possible audience. This focus on the highest possible rating coupled with journalists' ideology led to a slightly left-of-center framing of news.

Seeing an opportunity to provide audiences, particularly conservative audiences, with less available news and opinion, Fox News was created and quickly attracted a huge contingent of conservatives across the country. This led to the creation of its doppelganger MSNBC which appealed to liberal audiences. Then, the internet ushered in the further fracturing of the media landscape and ever more gradations of content to satisfy extremists and moderates of both sides (though notably, nothing to appeal to people who want objective journalism). Competition between news media companies has thus created a spectrum of information providers that reflect the biases, particularly confirmation bias, and whims of the entire electorate.

Artificial Intelligence

The next battlefield over which competition may eventually do us in is AI. Several companies have been working on AI for several years, but have been reluctant to offer AI-based services to consumers. Now, with Microsoft purchasing Chat GPT, which is already offered to the public, and also planning to integrate it into its offerings, other companies will feel the pressure to do the same. This will certainly kick off a zealous competition between these companies to further the capabilities of AI in an effort to provide their customers with an amazing product for a low price, meaning an ever-more advanced artificial intelligence that could potentially rival or surpass our own.

Many have pointed out the risks of AI advancement, but for the past ten years, development has been slow and of low concern. Now that companies have entered a new era of competition to provide it to consumers, though, growth will take off. Hopefully, not to our ruin.