Creating The Data Dividend
In a world where our digital lives are inseparable from our real lives, data has become the new currency of productivity. Whether we realize it or not, individuals are producing valuable data every time they interact with a product or service—yet the overwhelming share of that value remains with businesses and investors.
The concept of a data dividend proposes a new social contract in which all people hold an equity stake in the very data they create. To me this is not just a moral claim; it’s an economic one, rooted in the principles that gave rise to the capitalist system but adapted to 21st-century realities.
In my past articles, I’ve laid out key points on personal data ownership in the form of a data bill of rights and the five degrees of data. Below, I’ll dive deeper into how businesses can put this economic inclusion into practice.
Data As Labor And Resource
Individuals constantly produce data—whether through telecom usage, online shopping, social media engagement or even health and fitness apps. This stream of data fuels corporate profits, yet as I’ve outlined before, the people generating the data see little to none of that upside.
By recognizing that all people are "working people" in the sense that their data is labor, we open the door to a new view of economic class and productivity.
Ownership And Authority
My essay in the book #DataIsLabor argues that true data ownership means people should have the power to opt in and out of data collection and to negotiate how their data is monetized.
Without genuine ownership authority, our normal privacy conversation becomes a footnote to a larger issue: the economic exploitation of personal data in corporate transactions.
Data Dividend As A Post-Productivity Measure
A "dividend" is not a handout; rather, I see it as akin to a shareholder’s right to corporate profits. Likewise, a data dividend recognizes that individuals are co-producers in creating economic value. Corporate profits—almost $4 trillion annually in the U.S. prior to taxes—are disproportionately distributed to shareholders, while the original contributors of the raw material (i.e., data) remain uncompensated.
Moving Beyond Equality To Individualized Equity
Our blanket calls for equality often miss the nuanced truth: Each person’s data has a unique value. Egalitarianism, in this respect, is not a real possibility.
Empowering individuals to control and monetize that value fosters deeper empathy and mutual respect, and we begin to see one another as distinct contributors instead of merely faceless consumers.
Political And Technological Hurdles
While the technology for implementing data dividends (smart contracts, digital wallets, distributed ledgers) largely exists, I think the biggest challenges are political and cultural.
Convincing people that they own a resource they never realized existed—and that they are owed something for it—demands widespread education and policy engagement.
Actionable Recommendations For Business Leaders
1. Acknowledge data contributors as stakeholders.
Recognizing individuals as contributors aligns incentives and fosters trust. First, introduce a formal data-stakeholder model in annual reports or investor presentations. Show how data from customers/employees contributes to product innovations; present plans for sharing resultant value.
2. Establish transparent data use agreements.
Along with the recognition of stakeholders, transparency cultivates further user trust and reduces regulatory risk. Make sure to craft clear, accessible terms of service that explicitly describe how data is collected, analyzed and monetized. Provide a plain-language summary of these processes and update it regularly.
3. Create 'data union' partnerships.
Collective bargaining for data can lower costs and simplify compliance for companies while giving individuals more influence. Look to partner with emerging data unions—consortia of users who pool their data to negotiate better terms. This may involve developing or adopting standardized data licenses that detail payment structures for data usage.
4. Integrate micro-payment systems.
A data dividend must be easy to access. Users will not adopt complex, friction-heavy processes. Therefore, look to implement micro-payment channels (possibly blockchain-based or via traditional fintech APIs) that can automatically deposit "dividend" payouts into user accounts each time their data generates value.
5. Incentivize ethical data sharing.
I believe when users see tangible benefits, they’re more likely to share quality, accurate data—reducing your overhead for data cleaning and improving models. In this spirit, you can offer tiered reward programs (think "data loyalty points") where users who opt to share additional data get direct financial returns or service discounts. These benefits should be portable beyond your platform to maintain credibility.
6. Develop internal governance and advocacy.
Of course, a shift toward data dividends may face internal resistance or confusion if there’s no clear champion. Therefore, it can be prudent to appoint or train a "chief data dividend officer" (or incorporate into the roles of data privacy officers) to oversee compliance, manage user data rights and pioneer new data-sharing deals that return direct value to contributors.
7. Engage policymakers and activists.
In the end, political viability can make or break data dividend frameworks. Collaborate with legislators, consumer-rights groups and industry bodies to advocate for sensible regulations that can help ensure responsible data monetization and streamlined dividend processes.
The potential of a data dividend hinges on reimagining the economic contract between individuals and institutions. By acknowledging that data is labor, implementing fair compensation structures and leveraging existing technologies, businesses can usher in an era where innovation and profit are more equitably shared.
I believe the biggest challenge is not the creation of new tools—it’s the willingness to transform the status quo. If business leaders move early, they can not only differentiate themselves in a crowded market but also help redefine capitalism for the data-driven age.
JFK is currently traveling an lecturing on this topic.
If you want more details on how to actually calculate the value of laborious data read the white paper below.
Mathematical Theory of Personal Data Value
Or get the book below, or wherever you buy books.
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