We all contribute to AI — should we get paid for it?

In Silicon Valley, some of the brightest minds believe that a Universal Basic Income (UBI) that guarantees people unrestricted cash payments will help them survive and thrive, as advanced technologies eliminate more careers as we know them. , from white-collar and creative jobs - lawyers, journalists, artists, software engineers - to work roles. The idea has gained enough traction that dozens of guaranteed income programs have launched in US cities since 2020.

Yet even Sam Altman, CEO of OpenAI and one of UBI's biggest proponents, doesn't think it's a complete solution. As he said at a meeting earlier this year, “I think that's a small part of the solution. I think that's great. I think [advanced artificial intelligence] is becoming more and more involved in the economy, we should distribute a lot more wealth and resources than we have and that will be important over time. But I don't think that will solve the problem. I don't think it's going to make sense to people, I don't think it means people are going to completely stop trying to create and do new things and whatever. So I would consider this as an enabling technology, but not as a blueprint for society. »

The question posed is what a plan for society should look like then, and computer scientist Jaron Lanier, a founder in the field of virtual reality, writes in this week's New Yorker that the "dignity of data" could be an even more important part of the solution.

Here's the basics: right now, we mostly give away our data for free in exchange for free services. Lanier argues that in the age of AI, we need to stop doing this, that the powerful models currently making their way through society should instead "be connected with the humans" who give them so much to ingest and learn first.

The idea is that people “get paid for what they create, even when filtered and recombined” into something unrecognizable.

The concept isn’t entirely new, with Lanier first introducing the notion of data dignity in a 2018 Harvard Business Review article titled “A Blueprint for a Better Digital Society.”

As he wrote at the time with co-author and economist Glen Weyl, "[t]he rhetoric from the tech sector suggests a wave of underemployment to come due to artificial intelligence (AI) and automation". But the predictions of UBI proponents "only leave room for two outcomes," and they're extreme, Lanier and Weyl observed. “Either there will be mass poverty despite advances in technology, or much of the wealth will have to be brought under central and national control through a social wealth fund to provide citizens with a universal basic income. "

The problem is that both "hyper-concentration of power and undermines or ignores the value of data creators", they wrote.

Of course, giving people the right amount of credit for their countless contributions to anything online is no small challenge. Lanier acknowledges that even data-dignity researchers can't agree on how to sort out all that AI models have absorbed or how granular an accounting should be.

Yet he thinks it could be done - gradually. "The system wouldn't necessarily account for the billions of people who made ambient contributions to large models — those who added to a model's simulated proficiency with grammar, for example." But starting with a "small number of special contributors", over time "more people could be included" and "begin to play a part".

Alas, even if there is a will, a more immediate challenge - lack of access - looms. Although OpenAI has released some of its training data in previous years, it has since shut down the kimono completely. When Greg Brockman described to TechCrunch last month the training data for OpenAI's newest and most powerful extended language model, GPT-4," he said it came from a "variety of sources. licensed, created and publicly available data, which may include publicly available data. personal information,” but declined to offer anything more specific.

As OpenAI stated when it released GPT-4, there are too many downsides for the outfit to reveal more than it does. "Given both the competitive landscape and t...