Unlike most factors of production, we can reuse data limitlessly. Functional data markets would enable the utilisation of collected data for the benefit of society.
The term data markets refers to an economic structure, or a market place, in which economic operators, such as businesses, provide data to be reused and re-utilised by third parties. Together with his team at the Department of Communications and Networking, Professor of Practice Pekka Nikander studies how such data markets could be implemented especially for data produced and collected by Internet of Things (IoT) devices.
‘From an economics point of view, the main value of data lies in its ability to create new innovations’ says Nikander.
‘Unlike for most goods and services, the value of data increases with its use and consolidation. When combining reliable data, the value of the combination is greater than the sum of the parts. The more the data is reused, the more it adds value to the society as a whole.’
For example, open location data could benefit transportation planning and help avoid overcrowding in healthcare.
However, the data markets are not working in the current economic system. For example, the companies collecting data about individuals are able to extract more value from that data than the individuals ever could which creates little incentive to properly compensate the individuals.
At the same time, most companies do not want to sell the data they have collected for fear of other companies using the data against them or because of the difficulties of agreeing on the monetary value of the data. As a result, data does not move in a way that would be most beneficial for society, and many potential innovations never see the light of day.
According to Nikander, there are structural reasons to blame for this market failure: the current system of a capitalist economy has emerged for exchanging of competing and mutually exclusive products, which data is not. In economics, such exclusive, typically material products are denoted as rival products as opposed to so-called non-rival productswhich are often mass services, such as museum visits. As products, data are not only non-rival but anti-rival.
Examples of currently working but limited data markets would be digital business platforms, such as Uber or AirBnB. These platforms have a specific operator or owner that controls their underlying computer and communication systems, meaning they also own the accumulated data. This means that the platform companies have exclusive control over the data they collect.
Since the same IT systems are also used to convey the business transactions facilitated by the platform (such as a ride with Uber or lodging through AirBnB), the platforms form a monopolistic economic structure in which their owners can charge disproportionately high transaction fees, or in economic terms, extract rents. Economics deems an ability to extract rents a clear sign of a market failure.
Data stays safe inside a blockchain
Blockchains could provide a solution to the challenges faced by data markets. Distributed ledgers, or the so-called blockchains, provide a transparent and massively distributed database where business transactions can be reliably stored and later retrieved from.
An open distributed ledger is implemented within a network of hundreds or thousands of independent actors (or so-called miners), each owning or controlling their own computer resources, independently from the others. In principle, anyone can become a miner without needing any permission or agreement from the other miners. In such a ledger, the data stored in the blocks are openly viewable and anyone can independently verify the authenticity and integrity of the stored transactions.
In technical terms, storing business transactions or other data in a ledger block first creates a digital fingerprint, or a ‘hash’, of the data. The fingerprints correspond exactly to the data that the block is being created from. Whenever a new block is created, it contains fingerprints that cover all the data in the block and the fingerprint of the previous block. This creates a block chain. The original data can’t be restored from the fingerprints, but they can be used to quickly verify that the original data has not been tampered with.
As each block is composed of the fingerprints of the data stored in it and the fingerprint of the previous block, changing any data inside one block also changes the fingerprints of all the subsequent blocks. For this reason, it’s impossible to change the data stored in a blockchain afterwards without someone noticing. Because the blockchain itself is distributed across multiple computers, falsifying the data would require falsifying all copies of the chain.
Blockchains could release information for the use of society
According to Nikander's research group, blockchain systems could be used to create new types of digital business platforms that would work without any specific owner. This means that an equivalent of Uber could exist but without Uber. Such a platform would allow all the fees to go directly to the drivers (minus the small amount needed to run the ledger). In addition to the usual monetary payments, new structurally different compensation mechanisms could also be put into place.
Furthermore, no-one would be able to take exclusive advantage of the customers’ data as the information would be available to all. In the best possible case, the data would also be transparently controlled by all the parties reflected by the them.
So far, results of the research group show that there are no technical barriers to implementing such business platforms. However, the current market system poses challenges which the group aims to identify, and perhaps even remove in the long run.
‘To tackle the challenges facing us over the next few decades, we will need to be able to utilise the potential of data more effectively. Practical experiments with new economic systems that are substantially different from the current ones could, at least in theory, create alternative models which would hopefully lead to a more sustainable society’ Nikander concludes.
Watch an educational video created by Nikander and his research group here. The video provides more detail on the structural differences between data and other factors of production.
The group’s position paper, published at ITS Europe 2019 in June, can be found here.
This communication was first published 20 August 2019 by Aalto University.