Should we be paid for our data?5 min read . Updated: 14 Aug 2020, 12:18 PM IST
Tech giants grow larger by the day on the data we provide, but we have a right to ask for a better bargain—a greater share of value and a minimization of harm
We’ve all come to expect services on the internet to be available for free. For everything, from getting directions to the clinic to messaging friends, we use free apps. The two companies providing a vast majority of these services, Google and Facebook, rank No.4 and No.6, respectively, in the list of world’s top firms by market capitalization. It is well known that Google and Facebook make money from digital advertising.
Advertisers pay for the user’s attention and engagement, or clicks. This business model utilizes user data to make predictions about their behaviour with a goal to serve relevant content and advertising at the right time. For example, if you search for an ophthalmologist, you’re likely to see an ad for an eyewear shop in your neighbourhood for the next few days, even if you don’t make an appointment to see the doctor.
This is a benign representation of the “age of surveillance capitalism", a term made prominent by Harvard University’s Shoshana Zuboff, who describes how large internet companies have built tremendous power and revenue through collection of data about users. The holy grail of this business model is to “think the thought before you do", or in other words, predict your behaviour. The best way to achieve this is to collect and analyse all the data about your demographic, online search, purchase history, friends, address, video-viewing patterns and much more, which accurately defines your digital presence and identity. Such deep understanding, combined with non-personal data such as weather and traffic patterns, has helped create viable online businesses. Tech giants in the field of online advertising, ride sharing, gig economy and ecommerce, all thrive on data.
Does this mean our data is the “raw material" and should we get paid for it? After all, on average, Facebook made a revenue of $30 per user worldwide in 2019. The answer lies in understanding the unique nature of data and its value, and in enabling tools of greater societal value creation.
Data is unique in its conception. It has been compared to oil, gold, coal, poison and carbon dioxide. These comparisons seek to establish that data is a resource, which can be utilized for value creation (oil, gold) or that it can lead to individual and public harm (carbon dioxide, poison).
There are four characteristics of data and its value that uniquely complicate the task of attributing costs and benefits to it. First, from an economic lens, data does not diminish as it gets used, unlike resources such as oil or coal. Many copies of the same data can be made and used any number of times by several organizations.
Second, data involves externalities—benefits or costs imposed on third parties that are not related to the transaction. Some externalities are beneficial. A person’s daily commute data when anonymized and aggregated with the wider population data, will help boost traffic prediction in Google Maps. In an example of harm, data about individual members of a community can be aggregated to discriminate against an entire community.
Third, value of data can be exponentially enhanced by combining it with other data sets. At the same time, the liabilities are also likely to increase manifold. Therefore, the understanding of value will need to account for all aspects of individual benefits and harms, societal welfare and profits for businesses.
Lastly, there is an exchange of value. Value creation is driven by at least five stakeholders: technology company, government, community, gig-economy worker and individuals. The company collects and processes data and realizes value through monetization. Individuals and communities receive economic value of services from tech corporations such as maps, news, email, networking. Governments receive some tax revenue, and gig workers make wages. However, it is increasingly clear that the current design of the data economy leads to concentration of profits with the technology giants and does not support realization of fair value for people and society.
There is some good news, though. There is a growing class of tech services that promise to provide control, empowerment and minimization of harm to users. Personal data stores such as Solid, Digi.me, Hub of All Things and Meeco promise users the ability to store and manage permissions to their data. These efforts are in early stages of development, and discovery of business models. Greater control in the hands of users could lead us towards optimal outcomes.
The responsibility of creating a fair data economy, however, cannot be shouldered only by individuals. They are usually not in a position to negotiate their rights and economic gains. In India, first-time internet users are increasingly transacting online and are especially vulnerable to harm.
There are three ideas under exploration for political and policy efforts that can nudge the data economy towards equitable outcomes for all stakeholders. First, a progressive tax levied on monetization of data can serve to extract some value for the purpose of redistribution. Noble prize-winning economist Paul Romer has proposed that the revenue generated from monetization of data should be subject to a progressive tax, which can serve to disincentivize collection and monetization of user data. While the original proposal intends to minimize surveillance, this tool can be further explored for its efficacy in aiding redistribution of economic gains. The progressive nature will ensure that early-stage innovators are not disadvantaged.
Second, the idea for giving every citizen a “data dividend" can be explored. This idea, proposed by California governor Gavin Newsom, and again more recently by Andrew Yang’s Data Dividend Project, is similar to universal basic income, albeit focused on data-related economic activity.
Lastly, catalysing greater societal value creation, such as finding a cure for cancer using data, can create immense value for societies. The European Union’s data strategy report and India’s non-personal data committee report has emphasized unlocking value of data for society by enabling greater access to community data sets. Responsible stewardship of data through mechanisms such as cooperatives, trusts, exchanges, personal data stores and account aggregators will ensure right safeguards and enable greater data sharing by people. Individuals and communities may be open to sharing health data for research, without expecting monetary compensation when offered a safe mechanism that prevents misuse.
On balance, there are complex trade-offs associated with the data economy. We can all agree that individuals have a right to ask for a better bargain—greater share of value and minimization of harms. The road to an equitable data economy will undoubtedly begin with questioning the structural dominance of large tech enterprises.
*Sushant Kumar is principal at Omidyar Network India.
(Omidyar is an investor in Digi.me)