In the Information Age, Data Becomes a New Factor of Productivity
In economics, factors of production, also known as production inputs, are essential resources for the production of goods and services. In his epochal work “Principles of Economics”, famous British economist Marshall put forward the theory of four factors of production — land, labor, capital and entrepreneurial talent. National income (NI) is the reward of four factors, and that is, national income (NI) = labor wage (w) + land rent (r) + capital interest (i) + operating profit (π). This “four-in-one formula” sums up the core of western economic production theory and distribution theory, which has been widely accepted for more than a century.
However, factors of production are a historical category that evolves with the development of economy and society. The birth and development of the Internet has changed the mode of production, life and consumption, and it promoted many important and profound changes, and played an increasingly important role in economic development, social life and national governance. The full exploitation and effective utilization of all kinds of data has raised production efficiency to an unprecedented level. Data has become an indispensable factor in economic activities and a new generation of production factors after land, energy, population and food.
Table – Production Factors at Different Stages
Privacy Brings Data Dilemma and MPC Realizes Data Collaborative Computing
Nowadays, people have already extended their social activities to the network space. Every day, people contribute data continuously to the network space. A large amount of data is collected, calculated, analyzed, excavated and this goes beyond the original data level of information value.
However, because of the plain text nature of the data, the owner loses ownership of the data once the data is granted to others for use. Therefore, to ensure the privacy protection of data, a huge amount of data managed by enterprises cannot be exchanged and co-calculated with the data held by other enterprises, which is why a large number of data cannot generate value.
The emergence of privacy computing ends this dilemma. Yao Qizhi, a member of the Chinese National Academy of Sciences, proposed secure multi-party computing (MPC) in 1982. In a nutshell, participants have to enter information to calculate an agreed function. In addition to the accuracy of the calculations, they must also protect the privacy of each participant’s input data. Specifically, there are now n participants, each of whom, xi, is aware of the xi they entered, who together calculate a pre-agreed function f (x1 ,…, xn) = y. In this way, all participants will get the final y value, but they will not be able to know the specific data entered by the other participants. Thus, with local data not aggregated and privacy not divulged, each party can still achieve a common desired result by performing the operations of the given logic.
Privacy computing opens up huge business prospects for the digital world (Crypto Space)
Bitcoin’s pioneering combination of virtual currencies and peer-to-peer payment systems open the door to decentralization. With the introduction of intelligent contract function, Ethernet has greatly improved the scalability of blockchain, and all kinds of applications can be deployed on blockchain. Because of these characteristics, early public blockchain networks such as Bitcoin and Ethernet have been developed, attracting a large number of blockchain and encryption enthusiasts in the world, and many traditional institutions have been entering the area of blockchain, exploring various possibilities of decentralization.
The combination of privacy computing and blockchain is expected to put data ownership back in the hands of data producers, meaning that vast amounts of data can be counted without affecting privacy and ownership, so that the owners can profit and data can burst out with greater value. Therefore, the blockchain project based on privacy calculation is naturally suitable for the commercial practice in the fields of financial, medical, scientific research, government affairs, and logistics and so on.
“Operator” PlatON network for blockchain data
PlatON, the representative project of the combination of privacy computing and blockchain currently, is based on the basic attribute of blockchain and is supported by privacy computing network, and provides the next generation Internet infrastructure protocol with the core characteristics of “computing interoperation”. PlatON’s vision is to become the public infrastructure for privacy computing of the next generation, publishing privacy computing algorithms through contracts, and implementing MPC protocols with data providers and computing nodes for privacy protection requirements, so as to realize cooperative computing of data. PlatON, designed to price data flows, is all about computing and data, which is the most fundamental part of future human production. PlatON can achieve large-scale application landing and commercial scenario implementation:
For example:
I. Build a wider credit collection network. The public chain that provides private computing can provide user with customizable computing logic template and multi-party access mode, and in the case that the access party’s data does not need to be collected and shared, only the credit inquiry results are output to the demander, and the original data can be encrypted and stored in the blockchain system to meet all kinds of audit needs.
II. Supply chain financial infrastructure. The public chain of private computing is based on blockchain technology and cryptography algorithm, which can provide a platform solution for supply chain finance to digitally identify, process and transfer assets. Construct a new financial financing model of supply chain in which the information of the upstream and downstream enterprises can be shared symmetrically, the credit value of the core enterprises can be transmitted, the business tickets can be split and the risk can be controlled, and provide convenient data traceability for the supervision and enhance the service efficiency of the industry as a whole.
To build the public infrastructure for the digital age, PlatON continuously optimizes technology, iterates the underlying infrastructure, and breaks through the “impossible triangle” in terms of performance. “Impossible triangle” means that it is difficult to achieve both a good “decentralization” and a good “security” of the system in a blockchain and a high “transaction processing performance” at the same time. The most well-known blockchain projects in the industry are Bitcoin, Ethernet, and EOS. At present, using native Token transfer performance test method and EOS under the same testing conditions, PlatON has achieved a comprehensive performance leader in the quasi-real environment, and will continue to focus on the data field and accelerate the construction of data market.
Abigail White is brilliant editor; she is written some books of poetry, article, and essay. She went to Oxford University. She also knew throughout the world as the writer of article. She has more than 2 years experience in digital news publication. Now she works news writer on Thinker Now.
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