Own Your Data: From Scandal to Structure
A fireside conversation between James Felton Keith and Brittany Kaiser
When Joel Telpner opened the evening by jokingly asking the audience to hand over their driver’s licenses and Social Security numbers, the room laughed. It was a sharp reminder of how casually we’ve surrendered personal information for years.
But beneath the humor was a serious premise: data has moved from the margins of business and politics to the center of both. And the question is no longer whether it is valuable. The question is who owns it—and who gets paid.
This conversation was not about personalities or partisan politics. It was about structure. The goal was to go deeper than headlines and public relations and push into the mechanics of ownership itself.
From Ad Tech to Political Shock
When Brittany and I first met in November 2016 at the Cambridge Analytica office, the conversation was about business models and the ad-tech ecosystem. At the time, data targeting was standard practice. Advertising had long operated on behavioral insights. Politics was simply catching up.
Outrage only surfaced when data use became visibly political—even though corporations had been exploiting personal data for years. That asymmetry revealed something deeper: the public didn’t object to data extraction itself. They objected when they saw its power.
Her departure from Cambridge Analytica wasn’t rooted in naïveté about data. She had worked in political campaigns since 2007–2008, including the Obama campaign, where social media data first became a serious political tool. Data wasn’t new. What was new was the scale, opacity, and consolidation of control.
The “walled garden” model—where platforms closed APIs not to protect users but to centralize monetization—made that consolidation explicit.
The model is simple:Users generate the value.Platforms capture the revenue.Institutions sell access to audiences.
And individuals receive “free” services in exchange.
Data as Property, Not Just a Byproduct
The response was the hashtag #OwnYourData. But slogans aren’t solutions. The real shift comes when the idea is grounded in property rights.
The argument is pragmatic: in American law, nothing is more protected than property. If personal data is treated as property, then established legal frameworks—transparency, consent, licensing, compensation—can apply.
A simple analogy makes it clear: Airbnb. Before someone uses your house, they disclose who they are, what they’ll do, how long they’ll stay, and how much they’ll pay. You consent, and you’re compensated.
Why shouldn’t data operate the same way?
Who wants it?
What will they do with it?
For how long?
What is the compensation?
This reframes data from a passive byproduct into an asset.
Data as Labor and Economic Participation
My position intersects with—but also extends beyond—property rights. I treat data not only as property, but as productive input.
I approach problems as an engineer. Most problems are distribution problems. And the current economy has a distribution issue: productivity has increased dramatically, but wages have not scaled with it.
If individuals are generating data constantly—through work, consumption, communication, and engagement—then they are participating in production. Yet they are not compensated for that participation.
Universal Basic Income attempts redistribution from the top down. I have argued instead for what I call Universal Basic Ownership.
Ownership scales. Welfare programs do not.
If individuals own their data—both data they generate and data derived about them—they gain an economic stake in the systems they fuel.
That changes participation from passive extraction to active transaction.
The Literacy Gap
A recurring theme in the conversation was disclosure versus comprehension.
Terms and conditions technically represent “informed consent.” But no one reads them. And even fewer understand them.
Even legislators questioning tech executives often lack fundamental data literacy. If lawmakers don’t grasp the mechanics, how can consumers?
The problem is not merely transparency. It is intelligibility.
Without data literacy, consent becomes procedural rather than meaningful.
Licensing in Reverse
One of the more practical ideas raised was reversing the licensing model.
Instead of users accepting platform terms, platforms would license data from users under clearly defined conditions.
That would mean:
Limited purpose
Time-bound use
Explicit compensation
Enforceable constraints
Blockchain and smart contracts were discussed as technical mechanisms to encode such agreements. Whether blockchain is the ultimate solution is secondary. The core idea is contractual symmetry.
Right now, contracts are one-directional. That imbalance is structural.
Inequality and Valuation
A fair concern was raised: if data is monetized, will some people’s data be worth more than others’?
The answer is uncomfortable: yes, in some markets it already is.
But transparency cuts both ways. If value disparities exist, surfacing them allows for legal and policy remedies. Hidden extraction prevents accountability.
Ownership does not automatically produce equality. But opacity guarantees inequity.
From Awareness to Market Shift
Five years ago, cybersecurity products were difficult to sell because people didn’t perceive risk. Today, breaches are common knowledge.
Language shapes markets.
Once “data ownership” enters the public lexicon, business models adapt.
The question for executives is not whether change is coming. It is whether they will build systems that:
Share value, or
Continue extracting until regulation forces recalibration.
The Core Shift
Data has been described as:
The new oil
The new currency
The new asset class
All are partially correct.
But the more precise framing may be this:
Data is productive human output in a digital economy.
If it is productive, it generates value.If it generates value, ownership matters.
This was not a call for privacy panic. It was a call for structural clarity.
We are no longer debating whether data is powerful. We are debating whether individuals will remain raw material—or become economic participants.
That is not a technical question. It is a political and legal one.
And it is now part of the lexicon.
