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Should we charge for offering our personal data on the web?

An IMDEA Networks institute researcher proposes that users receive financial compensation in exchange for the personal data they offer on the web.

Woman using her laptop.

Woman using her laptop. / Photo: Unsplash

LatinAmerican Post | Marcelo Jaime

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Leer en español: ¿Deberíamos cobrar por ofrecer nuestros datos personales en la web?

Every time we perform an action on the internet (a search, a purchase, a visualization) we generate very valuable information for companies. These personal data are the basic input to carry out advertising campaigns, orient sales towards a specific product or feed artificial intelligence systems. It is not surprising, therefore, that they are marketed at very high prices. Now, should they pay us to give them our on the web?

In an article published in the IEEE Internet Computing magazine, Professor Nikolaos Laoutaris states that users should receive explicit monetary compensation in exchange for their data. Nowadays, on the contrary, the remuneration is implicit: companies take the data in exchange for free online services.

For Laoutaris, a researcher at the IMDEA Networks Institute, this change would be an important step towards an industrial revolution based on data. This revolution is framed in what he calls a people-centered data economy.

How much are personal data worth on the web?

Calculating the cost of personal data is not a simple task, as several factors must be taken into account. This results in a lot of difference between the various estimates published in this regard.

For example, according to an article published in The New York Times, the benefit generated by data collection in the United States was US$ 76 billion in 2018. A figure that would be equivalent to US$ 122 per user. However, according to ABC, bank and social media data are sold on the deep web at 870 euros (about 940 dollars) per user.

In that sense, Nikolaos Laoutaris argues that a family of four could earn about US$ 20,000 annually for the transfer of their data. By the way, it clarifies that it is a rather conservative calculation and that it should increase in the future.

Also read: Latin America 2020: labor market and AI

Benefits of an annual income in exchange for personal data

According to Professor Laoutaris, an annual income in exchange for personal data would be beneficial not only for users but also for society in general and for companies engaged in the collection and sale of data. In this sense, other authors have already expressed the idea of a minimum universal income based on the profits generated by the digital economy in which we live. An economy, by the way, that needs more and more data to support its growth.

As for people, such income would be an economic compensation that would dampen the impact of automation on the loss of jobs. For companies, it would represent the possibility of accessing better quality data, since at present, due to the ease and gratuity with which they are obtained, an excessive amount of information tends to be collected, much of which is irrelevant In economic terms.

In addition, if users received explicit financial compensation, they would be more predisposed to provide valuable information. Not for nothing, says Laoutaris, this proposal has been well received by industry leaders such as Mark Zuckerberg, Elon Musk and Bill Gates.

Is the proposal for an annual income in exchange for personal data feasible?

Despite the challenges of designing the technology necessary for its application, Professor Laoutaris states that his proposal is feasible. In his opinion, the indispensable tools to carry it out already exist today, it is only a matter of combining them properly. Of course, for this purpose, the participation of various disciplines (economics, computer science, mathematics, among others) will be necessary.

Finally, Laoutaris argues that “all that this change requires is for a small set of visionary online services to discover the benefits of this approach (reduce disputes between privacy and utility, encourage users to share more data) and use it as a differentiating element and a competitive advantage over its competitors. If it is successful, other companies will adopt it and eventually it will become a common practice. ”

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