Who Owns Data? The Data as Property Debate in the Gen AI Era

With AI and surveillance capitalism reshaping the economy, the question of who actually owns data has never been more urgent — or more complicated. Kiwi Futures CEO Chip Block examines the legal, technological, and economic dimensions of data as property.

The Federal Trade Commission (FTC) is debating dramatic new rules on how data is collected and shared about consumers. This follows new legislation across multiple States on privacy and, in general, how data is to be handled by companies across almost all markets.

Two major factors are driving this focus on data: Artificial Intelligence and data brokering/surveillance. Generative AI engines are crawling the internet collecting massive data sets to create large language models (LLMs) that can do everything from prescribing medicine to driving cars. Simultaneously, the explosion of surveillance capitalism is creating models that predict everything from what each person is going to buy to how they are going to vote.

With all of this focus on data, there is a fundamental question that has to be asked: Who owns data?

The Complexity of Data Ownership

This is a question most people think they know the answer to. After a few more questions, however, it becomes much more complicated. For example, do you own your social security number (SSN)? Most people answer “yes.” Except the Social Security Administration gave that number to you — so don’t they own it? If you share your SSN with an employer, do they now own it or are they just borrowing it?

For most of the last 40 years of technology advancement, there has been a general concept of “my hardware, my data.” If data is on your servers or laptops, you own that data. It is what has made Google, Facebook, Microsoft, Amazon and others multi-billion dollar companies. If you post something on their servers, they can use that to sell advertising and generate monetary gains.

The “my hardware, my data” concept began crumbling with the advancement of limitless and remote internet. The Generative AI and surveillance explosion is now bringing data ownership to a battle frenzy. A bill submitted in Congress in January 2024, H.R. 6943 — the No AI Fraud Act — stated: “Every individual has a property right in their own likeness and voice.” If my image and voice is property, what other data about me is my property? My medical records? My location?

The Only Viable Option — Encryption at the Micro Level

For the last 40 years the basic concept of handling data has been intrinsically tied to the systems, networks and devices that store, move and process it. But the demise of “my hardware, my data” defeats this approach because data is constantly moving. Being encrypted at one location is quickly lost when moved to third-party applications, shared over social media or stored in cloud buckets.

The only viable option is that data is encrypted independent of where it is stored, moved or shared — encrypted at a micro level, such as file by file. The control of the encryption must be managed by the data owner. As the author of an article, I should control who sees it regardless of where it moves. I should determine if it should be consumed by Generative AI engines. I should control its geographic location and how long it should exist.

The Economic Upheaval of Data Ownership

The internet economy is built around the ability of companies to monetize the data of others. Moving data control to its owners would dramatically upset this economic model. Data owners could restrict who can access their data or gain monetary value from it.

In a recent landmark ruling in X Corp. v. Bright Data Ltd., the court stated that “X's users hold the rights in the content” — clearly implying ownership rests with users, not the platform. The concept of data ownership extends to medical records, intellectual property, insurance, and national security. Which brings us back to the basic question: Who Owns Data?

Chip Block is the CEO of Kiwi Futures LLC. The views and opinions in this article are his personal views.

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