The value of data is contextual and determined by how it is being used; at different stages in its production cycle, it has varying degrees of economic utility. Furthermore it is often unclear who “owns” data, and what rights and responsibilities that comes with, as data is often co-created by multiple parties as part of a digital interaction. Parsing who has claims to what is further complicated by advances in machine learning and predictive analytics. Data also comes in different types and formats, and therefore, from a technological and business perspective, much of it remains inaccessible and unusable.

There are numerous arguments both for and against the concept of “data dividends” by which companies share profits derived from the use of personal data directly with the users who provided it. In principle, if we were to be paid for use of our personal data, it could lead to fewer monopolies, clearer privacy rights, new sources of income, and unlocking large markets that are currently not possible with today’s structures. On the other hand, data dividends are difficult to implement, don’t solve the fundamental questions of consent and coercion at the root of the problems we have today, may slow down innovation, and could lead to a separate set of inequality issues.

In theory, getting paid for “our data” and profiting from the information we create might shift the digital economy to a more equitable and productive orientation. However, in practice, there numerous obstacles and concerns over how this would work and whether it would deliver sufficient improvements over today’s architectures and arrangements. Without upgrades to the way we discover the value of data, new innovations in how users access and engage with their information, and major advancements in our legal understanding of what data is, the concept of data dividends is currently too impractical to provide major benefits for users.