Data value added

How and why everyone could benefit from its personal data if we consider existing definitions of property?

Google’s opinion to data ownership

All of us produce valuable data by writing posts, using chat programs, watching videos, buying goods, driving cars, opening smart fridges, clicking links and even just carrying a smartphone in the back pocket of our jeans. This data is a resource, capital and commodity produced by users of data-driven products and services. Personal data has been repeatedly called oil of the 21st century. Who owns and controls the value of this resource?

This essay is focused on how the value derived from the asset of personal data could be distributed more equitably, under what principles and the most important: among whom.

Personal data

The definition of “personal data” ¹ suggests that it can only be protected if it can be identified with the person who produced it. However, even if unidentifiable with this person when stored, the origin of data is tied to its producer — the user. Thus, throughout we use the term “personal data” to mean any data produced by an individual, even though that individual has neither had access to, nor control over it. We understand this existing data to be a commodity. One that is currently owned, controlled and used by organizations, companies and governments.

Data security: the third way

Obviously, society responds to the rapid development of information technology. Data influences, and is discussed in the cultural and political realms. Concerning the issue of the control exercised over personal data, two main currents can be distinguished in the discourse:

  1. The ability of IT and telecom corporations to obtain and use personal data gives them great power over individuals, communities and society in general. Such ability and power could be restricted by law. If the law does not protect the rights of users, new legislation is required.
  2. A consequence of data monitoring technologies is that governments are granted powerful surveillance techniques. If individuals are obliged to relinquish the rights to their data in exchange for a service, the service provider must have a right to reject unjustifiable requests from institutions to bypass data security protections. In fact, the FBI–Apple encryption dispute² is one of the most famous cases on this topic.

The third possible way to discuss and solve the ambiguities of personal data’s state of affairs starts from considering the “user” to be a “producer” of personal data. This seems a fair and reasonable perspective. Indeed, one that represents actuality. From this perspective, the user of a product and the producer of data cannot be separated as they are in the current nomenclature. There is simply no (established) term to describe the “user-producer” entity. Henceforth, we will refer to this entity with the term “produser” ³.

Produsage implies that data is the result of production; something that produsers must be aware of and should be able to seize. This does not contradict any of the above discussions, it only supplements them.

Conflict

Personal data is an integral part of data-driven business models. Its role can be seen in targeted ads, related and suggested content and pricing optimizations. Produsers, meanwhile, have neither access to the profits derived from data use, nor, as a rule, do they grasp that they actually produce. Is data not comparable with property, skills, experience or ability, the application of which, by an individual, results in remuneration to which they are fully entitled? If it is, are contemporary data-driven business models unregulated exploitation?

Own your own data

Private property or ownership is the personal or common possessing of property: objects, land or intellectual property ⁴. Property can be purchased, traded, received as a gift, earned or produced. The owner of any property also has rights to the economic benefits of that property. Ownership is fundamental to contemporary economics. Ownership law is complex and intricate, but profound and rational. In order to gain these qualities, political and economical thought has progressed through massive historical and social processes, ethical questioning and logical reasoning. To respect the principles of ownership is, by the rules of our society, to respect the work of humanity.

“Produser”: a field or a worker?

John Locke, one of the most influential enlightenment thinkers, argued that private property is a natural right: something to which every human being is entitled. He believed that God gave the earth to humans to hold in common, but, when a human being combines their labor with features of the earth, it becomes their private property.

By working the land, it becomes an asset of the worker ⁵.

If we apply this argument to data-driven business models, there appears to be a conflict of data ownership. Data is produced by some and cultivated by others. In fact, when we consider that companies essentially “harvest” a user’s data much like a “field”, the conclusion follows, that these business models are fair. Entrepreneurs cultivate an asset, so they deserve to reap the crop. The problem is, along entrepreneurs, users are also “men”, and personal data is “their property“.

Means of production

In comparison to Locke, Karl Marx’s understanding of production processes was more nuanced. The result of combining labour with the earth is no longer property, rather a „commodity“ ⁶. A commodity made by many workers is not shared between them as property. It belongs, not to workers, but, to those who own the means to produce the commodity. The means of production are the non-labour components of economic value; these include facilities, machinery and land. Concentrated private ownership of the means of production leads to the accumulation of commodities in the hands of those owners. Thus: “the rich get richer and the poor get poorer”.

On this basis, Marx argues that private ownership has been used throughout history to exploit the workers. While the means of production evolve, exploitation is a constant. Who, then, are the “workers” of so-called Industry 4.0? Obviously the crowd of the Mechanical Turk, UBER drivers, Deliveroo bikers and artists on Spotify. But, why not also those whose use of technology produces valuable data which is then exploited by companies?

If this is indeed the case, then the exploiters of today are data-driven business companies, who put the personal data of the workers into value chains circulation.

Types of property for data

Having evaluated different conceptions of the definition of property, the question arises: Who has the right to profit from data, and under what conditions? In other words, who is the owner of data? In order to understand the advantages for produsers of data, and the checks and balances with which each model protects their property rights, we will next consider personal data as possible subject to:

  1. Public ownership
  2. Corporate ownership
  3. Intellectual property

Mining data mines — public ownership

Mining is an extraction of valuable minerals or other geological materials from the earth, usually from an orebody, lode, vein, seam, reef or placer deposits. Mining is required to obtain any material that cannot be grown through agricultural processes, or created artificially. Mining in a wider sense includes the extraction of any resource ⁷. The term “data mining” connotes the discovery nature of obtaining value from an environment constructed of data. The knowledge and information (patterns, associations, or relationships within the data) are the extractable minerals of data mining.

Data, in this case, is a raw material in the environment of the digital world.

Data and the digital world literally grow symbiotically; from data to big data, to teradata dimensions. The amount of data grows, thus the environment grows and this environment is owned by whoever owns the data. Whether it is a good idea at all to allow such ownership of data is not a special matter. The environment (in the form of land, forests, oil or water) has been owned for centuries by individuals or private and public organizations. Society has developed agreements and rules under which ownership of the environment is possible, and the rights and responsibilities of owners and society are protected by environmental law. In order to understand how value that is derived from the asset of personal data could be distributed more equitably, the history of mining law is highly relevant.

Net wealth

Nowadays, in many countries minerals are seen as a part of the net (national) wealth. In many countries around the world governments own mineral rights⁸ — the right to profit from any mining or drilling to extract minerals. This sovereign right can only be leased, not claimed or bought by private companies. Even in one of the most monsterized sectors of manufacturing and economics, the gas and oil industries, the largest companies and the largest part of resource reserves are nationalized⁹. The widely accepted logic of economic law tells us that what cannot be artificially created, cannot be freely obtained or appropriated.

The surface may belong to individual owners, but the environment, be it land or data, is the subject of public interest and so could contribute to commonwealth.

Data value chain

Value-adding activities (value chains) of oil and data-driven industries are very similar.

  1. Upstream — exploration, collection. As oil fields are explored, raw oil is gathered, so the relevant users (environment) are defined and their data is parsed and collected.
  2. Midstream — refinery, processing, transportation, storing and analysis. Factories add value to oil by refining it and adding various chemicals. Similarly, the labour of data scientists’ adds value to the data by creating clean data sets and interpreting and evaluating it. By anomaly and dependency detection, clustering, classification and summarization of the raw material, useful information is extracted from the data.
  3. Downstream — exposition of an end-product, marketing, distribution. Information becomes commodity.

Data is not oil

The infrastructure of the midstream and downstream, are often not built or owned by public companies and are the accomplishment of private interests. As we see it, the environment of data produsers adds to the value chain only in the upstream.

Thus, profits, which are made only in the upstream, could contribute to the net wealth, in contrast to the oil industry.

Another significant difference between oil and data is the fact that oil is a non-renewable resource. Products made of oil, such as fuel, are burned and are also not renewable. Data and the value extracted from it (information) cannot so easily be considered nonrenewable.

Banking data banks — corporate ownership

Data banks hold tables of facts and values. They are the biggest structured parts of a digital environment and are designed to accumulate and organize data. Actually, data banks are what is being mined, not an abstract “environment”. This is why there is a place for another approach to use modern law in the aspiration to design for justice. As the word “bank” suggests, there might be a place for corporate law too. In contrast to a fair distribution of common goods (environment), we are dealing with the governance of corporate property (banks).

Data share

By using a service like Uber, we connect to the drivers’ database, whose location is being parsed into a data set and packed into a data bank, to be retrieved, visualized and interpreted into our trip receipt, or, possibly, a model-route for a future self-driving car. Using Spotify we stream a audio file from the artists data base. An occurrence of streaming is stored in a data set associated with us, to relate it with other streamed files, in order to create a “suggestion” for us or another user. Using Google, we click the link other people have verified as relevant by clicking it before. Our own click is also saved to the data bank of verified links, so that the relevance rank of the link grows.

This is how produsage works: a user of a product is a producer of the data that shapes the product and contributes to the core which is stored in a data bank. If corporate law is applied to data banks, data becomes a share.

Shares as rights

Shareholders are not a part of the company. The primary interest of shareholders (produsers) is to invest, not to control or own part of a service or product¹⁰. As a shareholder of a data bank, we do not have a right to decide how Uber prices our ride. However, in corporate law, a certain number of rights could come with a share.

Right to dividends (or payments made by companies to their shareholders) declared by the company. To a certain extent, every user of a digital product already receives dividends: the product itself. Approaching data banks by way of corporate law could enhance the rights of users to profit. A Uber user contributes his data to the creation of a self-driving car. Spotify offers its services as an advertising space. Not all profit should accrue to the produsers. The functioning and development of the business is not conceivable without the users data share. However, given the profit motivation of capitalist economies, access to Uber, Spotify and Facebook could at least yield dividends if we are to follow the paradigm of corporate law.

In a world where corporate law governs data banks, IT corporations become much more social/political organizations. Since the data-capital of social media networks consists only of shareholders’ “investments”, Facebook, for example, becomes a syndicate, where its managers must be politicians, promising and engaging millions of people to vote for them. Such a situation would be a prerequisite, similar to the citizenship identity.

Deposited personal data is a contribution and investment. The right to vote, to actually make decisions, could foster popular understanding about the importance of personal data. Something that we currently lack.

Data as intellectual property

We use Amazon to buy and sell for example books and domestic commodities. The act of purchasing a new washing machine is not covered by patent protection. In fact, Einstein could not patent his celebrated E=mc²¹¹ either, because for patent law the speed of light is as our purchase, just a description of reality.

We can argue, though, that a data set is intellectual property; just as mixtures of ingredients such as medicines are.

If the effect of a mixture is more than the effect of its components, it can be subject to intellectual property law¹². The value of an assembled data set associated with a unique person and their personal data (such as history of purchases, delivery addresses or their browser history) is higher than a simple sum of isolated descriptions and facts.

Protect data as Intellectual Property

Of all types of property Intellectual Property is the only one, that is open for bottom-top claim. One cannot simply decide to make a piece of land, commodity or business to be theirs. Creators of “mixture of ingredients” though are free to decide to declare their creation as own property.

If data would be intellectual property, it could be covered as a patent, utility model, copyright, trademark or design and therefore be prevented from unauthorized usage.

Conclusion

The value of personal data is not distributed equitably and the so called “Data protection” law does not protect data. It protects privacy and its current design leads to the exclusion of producers from data-driven value chains. Furthermore, data is raw material, a by-product and an environment of the digital world and could contribute to the common good. The deposited personal data is a contribution, investment and right.

To upgrade the current distribution of personal data to a fair level, we have to give tools to produsers to preserve personal data. In addition we could give the right to decide what to do with personal data to the produsers, work out a fair exchange rate for data, and design an ownership model, which considers data as a commodity, that is produced, owned and controlled by users of data-driven products and services.

Research & writing:

Markus Kreutzer, Sveta Goldstein

References

  1. EU directive 95/46/EC: Article 2a: “personal data‘ shall mean any information relating to an identified or identifiable natural person (“data subject”)” Article 4a: „data subject“ is one „who can be identified, directly or indirectly, by means reasonably likely to be used by the controller or by any other natural or legal person“ (http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:31995L0046, retrieved July 17, 2017)
  2. Apple Inc., official website: Answers to your questions about Apple and security (https://www.apple.com/customerletter/answers/, retrieved July 17, 2017)
  3. Axel Bruns, Wikipedia, Second Life, and Beyond: From Production to Produsage
  4. Wikipedia, Ownership (https://en.wikipedia.org/wiki/Ownership, retrieved July 17, 2017)
  5. John Locke, The Second Treatise on Civil Government
  6. Karl Marx, Selected Writings, ed. D. McLellan, New York: Oxford University Press, 1977
  7. Wikipedia, Mining (https://en.wikipedia.org/wiki/Mining, retrieved July 17, 2017)
  8. Wikipedia, Mining Law (https://en.wikipedia.org/wiki/Mining_law#Ownership, retrieved July 17, 2017)
  9. The American Petroleum Institute (API), Putting Earnings into Perspective, p.4
  10. Henry Hansmann, The Evolution of Shareholder Voting Rights: Separation of Ownership and Consumption p.5, p.61
  11. What Cannot be Patented (https://library.und.edu/government-documents/cannot-patent.php, retrieved July 17, 2017)
  12. Ibid.