James Felton Keith is CEO at Inclusion Score Inc. and Labor Economist at Keith Institute. His latest book is #DataIsLabor.
In late 2018, I was in Washington, D.C., to meet with Congress members to discuss an initiative to create an “Internet Bill of Rights”. The most comprehensive conversation I had was with a representative who was tasked with creating it. I tried to explain that the internet is not a technology but an expanding space, and, therefore, it’s difficult to regulate. Similar to outer space, a rocket is a technology that gives us access to it, but space would exist whether or not we could access it.
Around this time, there were also calls to create a “Digital Bill of Rights,” but what is “digital” anyway? It’s a genre, not an asset or tangible thing. I tried to explain that the technology we are transacting in digital space or over the internet is data, and all data types are tied to peoples’ personal data if we trace them back far enough. The Congress members I spoke with understood, but this initiative was a low priority during and following our talks. At the time, our attempt was to find American politicians who could communicate the big idea of how our economy was beginning to work, so smaller local regulators could start to consider how to control the distribution of value that the internet of data transactions creates.
Today, as artificial intelligence sprawls in tandem with income inequality, I’m finding elected officials are more available to hear about how the internet of value works. I’m just getting back to New York from Washington, D.C., again. This time, my team met with elected officials and labor leaders on my book, which discusses data as labor, and to consider Europe’s General Data Protection Regulation as a benchmark for rights. We discussed core rights that could allow our market economy to consider both the “fair use” of people’s data and the legal allocation of value from productivity.
These are the six rights I identified as a result of this conversation, which I call the “data bill of rights.”
1. The right to erasure, “the right to be forgotten.”
2. The right to portability, “the right to move data.”
3. The right to restrictive processing, “the right to say ‘stop.’”
4. The right to redress, “the right to adequate settlement in any legal suit.”
5. The right to education, “the right to understand the terms.”
6. The right to ownership, “the right to the means of production.”
From my point of view, European and American leaders are still talking about data from a privacy standpoint, but in practice, many people will trade away their data as a nescient property for the convenience that it can produce for them. The general transparency of modern life suggests that we only consider our privacy once we can identify harm.
Business leaders need to move on from the privacy debate and consider how to distribute all the value created by the voluntary or involuntary sharing of personal data. I believe we are missing a market opportunity to include people in the normal economy. By “normal economy,” I mean tying people’s incomes, not wages, to the growth in productivity. We should look at wages as a retainer for people’s time, and if that time is increasingly productive after their toiling, we should provide them with a productivity dividend or, in the case of the data rights listed above, a “data dividend” for their unit of contribution.
This is something that we can calculate, as Claude Shannon first estimated the entropy of information, specifically the entropy of the English language, in his 1948 paper titled “A Mathematical Theory of Communication.” I know that this is pretty deep in the weeds, but consider this: A lack of predictable data (entropy) is where we learn things about the market demand of our “data subjects.” That’s what the GDPR calls people who provide data. Whether the information on people is very or not-so-very predictable determines how valuable it is, but it all has some value in the creation of new goods (products and services).
With the sixth right, the right to ownership, I believe we can distribute universal basic income to people, not just because it’s the right thing to do but because they are owed it. We can calculate productivity per every corporation and the broader economies of the world. We can also calculate this outside the for-profit arena at municipal and non-profit corporations. Everything regulated is incorporated.
With this in mind, business decision-makers can take two steps:
1. Create a stakeholder class to distribute a productivity dividend.
2. Join a stakeholder union to invest revenues alongside peer companies.
Organized labor decision-makers can also take two steps to become custodians of this enhancement in labor:
1. Negotiate income as a class that includes both waged labor and other input (data) labor.
2. Start negotiating both employee labor and data-subject labor.
Don’t take my word for it; heed the warning of billionaires like David Rubenstein, Paul Tudor Jones, II and Ray Dalio. If we don’t upgrade our conversations about equality with a distribution of equity, we may find ourselves in an increasingly tense socio-economic state. Our employees and consumers need to know how they are valuable. They cannot assume that AI, a derivative of their data, is valuable but they are not. AI, and whatever it spawns, must work for us.
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