Everyone Take Copies – Econlib

I have a new working paper with Bart Wilson titled: “You Wouldn’t Steal a Car: Moral Intuition for Intellectual Property.” 

The title of this post, “everyone take copies,” comes from a conversation between the human subjects in an experiment in our lab, on which the paper is based. The experiment was studying how and when people take resources from one another. 

The people in the game each control a round avatar in a virtual environment, as you can see in this screenshot below. 

In the experiment, “seeds” represent a rivalrous resource, meaning multiple people can’t possess and use them at once. In other words, they operate like most physical goods. If the Almond colored player in the picture takes a seed from the Blue player, then Blue will be deprived of the seed, in the same way that if someone’s car is stolen, they don’t have it anymore. 

Thus, it is unsurprising that the players called the taking of seeds “stealing,” as you can see from the speech bubble in the picture. This result was expected, and it is in line with Bart Wilson’s previous work on the origins of physical property.

Our research question considers whether similar claims will emerge after the taking of non-rivalrous goods that we call “discs.” Non-rivalrous goods are goods that can be used by multiple people without any loss to the other users. If participants exercise the ability to take a disc, then the original disc holder still has a disc and can still consume the full value of it. 

The human subjects are not forced to interact via the chat function, but they often choose to form a community and use language to try to obtain the available surplus in the environment. The following quote from our paper indicates that the subjects do not label or conceptualize the taking of digital goods (discs) as “stealing.” 

In our paper, we write:

We encourage you to read the manuscript if you are interested in the details of how we set up the environment and mechanisms of exchange. We conclude that, contrary to the desired comparison in the “You Wouldn’t Steal a Car” advertising campaign attempted by the Motion Picture Association of America in the early 2000s, people do not intuitively view piracy as a crime. 

Humans can state that digital piracy is illegal and take measures to prevent it. However, it will be difficult to cause an individual engaging in piracy to feel guilty as they do when they believe they are directly harming another human. 

This has implications for how the modern information economy will be structured. Consider the model recently labeled “the subscription economy.” Increasingly, consumers pay recurring fees for ongoing access to products/services (like Netflix, Adobe software) instead of one-time purchases. Gen Z has been complaining on TikTok that they feel trapped with so many recurring payments and lack a sense of ownership. 

In a recent interview on a talk show called The Stream, I speculated that part of the reason companies are moving to the subscription model is that they do not trust consumers with “ownership” of digital goods. People will share copies of songs and software, if given the opportunity, to the point where creators cannot monetize their work by selling the full rights to digital goods anymore. “Everyone take copies.”

A feature of our experimental design is that, when a disc was shared, even though the creator was rarely compensated directly, the attribution of who originally created the disc was secure. A disc made by the Blue player is blue, so all can see who gets credit for providing it. The reason for this design choice was to allow the Blue player to easily see their work being passed around. 

A recent development in information technology, that of large language models, means that many idea creators are not getting credit when their original work informs the answers users are getting from tools like ChatGPT. In a recent settlement, Anthropic agreed to pay for some of the written training material that went into making Claude. The way in which human creators are (or are not) compensated for providing inputs to AI models will shape the future ideas landscape. Understanding how people think about those inputs illuminates our thinking about that process.