Skip to Content
Uncategorized

A Letter to the Editor from Joshua Epstein

A clarification regarding the article “Artificial Societies and Virtual Violence.”

To The Editor:

I wish to avert a misunderstanding of my research that could arise from the review article, “Artificial Societies and Virtual Violence” by Mark Williams, which appears in the July/August issue of Technology Review. The review concerns two books: Joshua M. Epstein and Robert Axtell, 1996. Growing Artificial Societies: Social Science for the Bottom Up (MIT Press) and Joshua M. Epstein, 2006. Generative Social Science: Studies in Agent-Based Computational Modeling (Princeton University Press). The review is both favorable and well done, so I offer this as a clarification rather than a critique, but an important clarification nonetheless.

Referring to the Sugarscape model developed in Growing Artificial Societies, the article reads:

“Essentially, Epstein and Axtell found, Sugarscape functioned as a model of a hunter-gatherer society, reproducing a common feature of human societies: skewed wealth distribution. Granted, the notion that crude automata moving around a computer grid suggest that wealth inequality is an innate feature of human societies will be disliked not only by Marxists but by most of the rest of us…”

This could easily be misinterpreted. We in no way argue that “wealth inequality is an innate feature” of society. In fact, with (we thought) unmistakable disdain we wrote, “…some have argued that highly skewed wealth distributions in income and wealth represent some sort of “natural order”, a kind of immutable “law of nature.” Artificial social systems let us explore just how immutable such distributions are. We can adjust local rules–like those concerning inheritance and taxation–and see if the same global pattern emerges. ” p.36

Indeed, the book’s very Introduction skeptically notes: “As a practical matter, if such highly skewed wealth distributions are immutable laws of nature, as some have claimed, then there is little hope of greater economic equity in society. A tool like Sugarscape can function as a kind of laboratory…where we alter agent behavioral rules, such as those governing trade or inheritance, in order to see how immutable this kind of distribution really is.” (P. 7). And we did a good deal of that.

First, we demonstrated the distribution’s sensitivity to rules of inheritance, in an experiment (pp 67-68) explicitly critical of so-called “Social Darwinists.” Then we showed its sensitivity to rules of inter-agent trade (p. 122). Readers of the 2006 book under review—Generative Social Science–will also find, in connection with economic class formation, my general statement: “I am emphatically not claiming that there is anything immutable about social inequality.” (P. 25).

Dr. Joshua M. Epstein
Senior Fellow in Economic Studies
Director, Center on Social and Economic Dynamics,
The Brookings Institution
Washington, DC

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

OpenAI teases an amazing new generative video model called Sora

The firm is sharing Sora with a small group of safety testers but the rest of us will have to wait to learn more.

Google’s Gemini is now in everything. Here’s how you can try it out.

Gmail, Docs, and more will now come with Gemini baked in. But Europeans will have to wait before they can download the app.

This baby with a head camera helped teach an AI how kids learn language

A neural network trained on the experiences of a single young child managed to learn one of the core components of language: how to match words to the objects they represent.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.