AIが、世界経済の司令塔になる時代が到来するかもしれない。

Deepmind’s New AI May Be Better at Distributing Society’s Resources Than Humans Are

By Edd Gent / July 4, 2022 / SINGULARITY HUB

わたしのnoteにおいては、最新の科学・経済・社会等の問題に関して、英語の記事を引用し、その英文が読み易いように加工し、「英語の勉強ツール」と「最新情報収集ツール」としてご利用頂くことをmain missionとさせて頂きます。勿論、私論を書かせて頂くこともしばしです。

How groups of humans working together collaboratively should redistribute the wealth they create is a problem that has plagued philosophers, economists, and political scientists for years. A new study from DeepMind suggests AI may be able to make better decisions than humans.

AI is proving increasingly adept at solving complex challenges in everything from business to biomedicine, so the idea of using it to help design solutions to social problems is an attractive one. But doing so is tricky, because answering these kinds of questions requires relying on highly subjective ideas like fairness, justice, and responsibility.

[For an AI solution to work it] needs to align with the values of the society it is dealing with, but the diversity of political ideologies that exists today suggests that these are far from uniform. That makes it hard to work out what should be optimized for and introduces the danger of the developers’ values biasing the outcome of the process.

The best way human societies have found to deal with inevitable disagreements over such problems is democracy, in which the views of the majority are used to guide public policy. So now researchers at Deepmind have developed a new approach that combines AI with human democratic deliberation to come up with better solutions to social dilemmas.

To test their approach, the researchers carried out a proof-of-concept study using a simple game in which users decide how to share their resources for mutual benefit. The experiment is designed to act as a microcosm of human societies in which people of different levels of wealth need to work together to create a fair and prosperous society.

The game involves four players who each receive different amounts of money and have to decide whether to keep it to themselves or pay it into a public fund that generates a return on the investment. However, the way this return on investment is redistributed can be adjusted in ways that benefit some players over others.

Possible mechanisms include strict egalitarian (平等主義の/igæ̀litέəriən), where the returns on public funds are shared equally regardless of contribution; libertarian, where payouts are in proportion to contributions; and liberal egalitarian, where each player’s payout is in proportion to the fraction of their private funds that they contribute.

In research published in Nature Human Behavior, the researchers describe how they got groups of humans to play many rounds of this game under different levels of inequality and using different redistribution mechanisms. They were then asked to vote on which method of divvying up (分け合う) the profits they preferred.

This data was used to train an AI to imitate human behavior in the game, including the way players vote. The researchers pitted (競争させる) these AI players against each other in thousands of games while another AI system tweaked (微調整する) the redistribution mechanism based on the way the AI players were voting.

At the end of this process, the AI had settled on a redistribution mechanism that was similar to liberal egalitarian, but returned almost nothing to the players unless they contributed roughly half their private wealth. When humans played games that pitted this approach against the three main established mechanisms, the AI-designed one consistently won the vote. It also fared better (うまくやる) than games in which human referees decided how to share returns.

The researchers say the AI-designed mechanism probably fared well because [basing payouts on relative (rather than absolute) contributions] helps to redress initial wealth imbalances, but forcing a minimum contribution prevents less wealthy players from simply free-riding on the contributions of wealthier ones.

Translating the approach from a simple four-player game to large-scale economic systems would clearly be incredibly challenging, and whether its success on a toy problem like this gives any indication of how it would fare in the real world is unclear.

The researchers identified several potential issues themselves. One problem with democracy can be the “tyranny of the majority,” which can cause existing patterns of discrimination or unfairness against minorities to persist. They also raise issues of explainability and trust, which would be crucial if AI-designed solutions were ever to be applied to real-world dilemmas.

The team explicitly designed their AI model to output mechanisms that can be explained, but this might get increasingly difficult if the approach is applied to more complex problems. Players were also not told when redistribution was being controlled by AI, and the researchers admit this knowledge may impact the way they vote.

As a first proof of principle, however, this research demonstrates a promising new approach to solving social problems, which combines the best of both artificial and human intelligence. We’re still a long way from machines helping set public policy, but it seems that AI may one day help us find new solutions that go beyond established ideologies.

資本主義と社会主義・共産主義とのイデオロギー対立において、資本主義は経済活動を自由な市場の機能に委ねてきたのに対し、社会主義・共産主義においては、経済活動を、国家により管理することで、経済をコントロールしようとしてきた（社会主義と共産主義とでは国家の関与の度合いは異なるが）。そして、計画経済をうまくコントロールすることができずに、共産主義国家の代表であったソ連は、経済の低迷により、崩壊するに至った。しかし、今後、AIが、自由な市場の機能に代わって、経済のコントロールができるようになれば、景気循環を防ぎ、国家の機能を大幅に削減しながら、経済活動の最適化が可能となる時代が来るかもしれない。