GDOC Data Ecology on the Block Chain: Devolve Facebook in Five Years?

Recent global events pertaining to data privacy have led to significant controversies in communities around the world. Leading the pack is Facebook's "Data Gate" scandal, which involved the unauthorized data leak of 87 million users by its partner Cambridge Analytica. This directly prompted the United States Congress to launch a special hearing against Facebook. At the April 10th congressional hearing, a total of 44 U.S. senators interrogated Facebook's founder, Mark Zuckerberg, on data privacy, security protection, and data ownership.

On March 22nd, the Hangzhou branch of Chinese Central Bank issued administrative penalties to Alipay, citing 7 violations, leading to a fine of 180K RMB. These violations include curtailing of customer rights, inappropriate product promotion, and inadequate protection of personal information.
Although these two events are thousands of miles apart, they both involve Data, or Big Data in the Internet age, for that matter.

With the continuous evolution and advancement of the Internet economy, data accumulated by human society has literally exploded. In 2015, 8.6 ZB (1 ZB=1 trillion GB) of data was generated globally, with a 40% annual growth rate. Globally generated data is expected to reach 40 ZB by 2020. The explosive data growth introduced new business models and company structures, e.g., Facebook, Twitter, Tencent, Amazon. From a fundamental data perspective, the vast majority of these huge Internet corporations actually rely entirely on data processing and application development to generate new business models. For example, Facebook and Twitter are essentially large data-advertisers (providing users with free social tools to produce data), while Tencent is a mixed breed; peddling games in addition to advertising.
Strictly speaking, this is a tacit deal: companies provide free platforms and services to users in exchange for the virtually unlimited and unrestricted use of their UGC (user generated content), upon which companies have developed and evolved into a variety of business models, thereby generating huge profits. As the popular meme goes, "Skimming wool off the pigs".

Unfortunately, recent events have led to huge potential conflicts in this particular "Skimming wool off the pigs" business model.

In February 2016, the Wall Street journal reported that Tencent accused mobile phone maker Huawei of over-stepping Tencent's app/data sovereignty and simultaneously violating WeChat users' privacy by capturing user's chat records in their Honor Magic phone. Tencent also requested the Ministry of industry and information to investigate their claim.
Moreover, Huawei subsequently issued a statement to the Wall Street journal denying that it infringed user privacy and asserts that it had actually been authorized by users to access their data. Further, Huawei claims that its Honor Magic phone has been certified by the Ministry of industry and commerce, with no violations of privacy whatsoever. Huawei advocates that all user data should rightfully belong to users instead of WeChat or Huawei. In fact, this particular incident highlighted the importance of claiming data ownership.

Another recent incident also brought up this issue. Facebook's COO Shirley Sandberg in an interview with NBC, suggested that users should pay for the privilege to have their data completely removed from social media services.
Be it Tencent or Facebook, both companies' core business model is built on the development and application of large-scale personal data. Without user data, Tencent or Facebook will no longer cease to be commercially viable. The reason why Huawei advocates personal data ownership is because it makes money off hardware, not data, unlike Facebook and Tencent.

Regardless of the prevailing viewpoints on data ownership, we can fall back onto the fundamental attributes of personal data in our ensuing discussions. Firstly, personal data deals with the recording or description of a particular individual, and its source is the human individual himself. Thus, from a legal standpoint, data ownership should be viewed in the same light as rights to personal portraits and reputation. Secondly, because of its huge commercial potential, data should possess properties akin to assets, which can not only be used for transactions, but should also come with potential profit yield.

Based on the prevailing legal practices of countries around the world, all of the aforementioned rights should belong to the individual itself. The EU has the GDPR (General Data Protection Regulation) legal framework, which will come into force on May 25, 2018. GDPR's core provisions clearly require data holders to provide privacy protection, data security management, and data authorization, etc. Although there currently exists no clear regulations on personal data protection in China, the legal and economic consensus is that data has value, and is a class of property with all reserved rights, thereby demanding proper authorization and approval from the rightful owner when used in practice.
The development of big data in China is lagging the West, due to two primary reasons as follows.

First, the problem of data ownership and transaction costs. According to Nobel Laurate Ronald H. Coase's property rights theory, a stable and sustainable data property transaction system cannot be established if the data property rights remain unclear. Similarly, the ambiguity of data property rights will inevitably lead to high transaction costs or even failed transactions.

Second, problems dealing with the right-of-use and right-to-earn. Without clearly defined data property rights, there can be neither agreed-upon right-of-use nor right-to-earn consensus. This leads to problems in the current data market, where data profit cannot be fairly distributed among data owners and data operators. On the contrary, it has fostered a thriving grey market and secret trading, leading to massive privacy leaks.

We believe that the above problems can be addressed by using block chain technology with a focus on data property rights, which we call the GDOC (Global Data Ownership Chain).

Firstly, the block chain is a decentralized, distributed ledger with two key features: immutability and perpetuity. This fits well with the ownership assertion of data assets, which is not stand-alone. Data assets manifest themselves as numbers and code online, which can be easily replicated and misappropriated. The immutability and perpetuity properties of block chain makes it perfect online medium for irrevocably registering data ownership.
Secondly, the tri-partite delineation of power into data-ownership, right-to-use, and right-to-earn ensures total transparency at each stage of the data life-cycle, from birth to transaction, to destruction. This allows the data asset to generate profits that can be fairly and efficiently distributed in the ecosystem, thereby greatly reducing transaction costs among the key data players.

In retrospect, there are simply too many fundamental fatal flaws in traditional Internet businesses ecosystems like Facebook:

The first problem is data ownership. Both Facebook and Tencent make it very clear that all personal data are properties of the company. As mentioned, Facebook's COO has publicly said that end users must pay to stop their personal data from being monetized. Furthermore, the Facebook "Data Gate" was not just a simple data leak, but in fact involves profiteering by Cambridge Analytica, who allegedly sold the leaked personal data to a [Suspicious link removed]pany, ironically.
In retrospect, Facebook not only does not guarantee data privacy and security, but misappropriate and profit from user data, and pays nothing for data usage. Such harsh data exchange conditions are clearly unacceptable to anybody in the world. Therefore, with the introduction of data protection rules such as the EU GDPR, as well as the increasing public awareness of personal data ownership rights, the latter may very well become the value proposition for rocking the foundation of traditional Internet companies.

The second problem involves the transaction cost of data ecosystems. According to Coase's property rights theory, a market cannot reach Pareto Optimality if any participating entity has a large external or negative efficiency, defined as transaction costs, potential risks undertaken by participants in the transaction process, including communication, bargaining, delinquency, trust capital, contract enforcement costs, infringement of legal rights, potential risk capital, etc. At present, large Internet companies worldwide have controlled the vast majority of individual data. Moreover, since the legal data ownership rights remain unclear at best, there is no vested interest for companies big and small to advance data ownership rights for the proper development and usage of personal data. On the contrary, it has led to unethical data transactions and even illegal black market data transactions. The latest case being the transfer of leaked data by Cambridge Analytica to a [Suspicious link removed]pany. More outrageously, the company's CEO had originally planned to use this "illegal" data business model as a basis for public ICO, before the scandal broke.

The Facebook scandal erupted in US and Europe, with relatively comprehensive judicial mechanism for data protection and privacy. With data protection largely absent, China is in an even more dire situation with illegal data transactions reaching disastrous proportions. Up till now, black market trading still occupies the bulk of China's data transactions. According to statistics, the number of domestic personal information leakage hovers around 5.53 billion records, averaging 4 leaked data records per person. Each leaked data record will undergo multiple hands in the black market until its value is sucked dry. Among the leaked data, 80% originated from corporate insiders, with hackers accounting for only 20%. In April 17th of 2018, CCTV exposed a case of data trafficking in the Feicheng city of Shandong Province, involving 3 million personal records and 80M RMB. The case investigator was quoted saying "the insiders who illegally provided student and phone records were online operators from the education ministry and China mobile, respectively", in fact, "these are rudimentary and cheap, while high-end leaks like real-time user mobile location, after pass through multiple middle men, can fetch as much as one to two thousand RMB per instance."

In view of the aforementioned problems in data exchange and Internet application markets, the GDOC core team has officially launched the GDOC project, using block chain to address these problems.

GDOC stands for Global Data Ownership Chain, with its core technology and business model as follows:

Firstly, the use of third generation block chain protocols like EOS, and DPOS (Delegated Proof of Stake) consensus mechanism, will allow GDOC to support large-scale data application transactions, with a maximum theoretical TPS (transactions per second) of 1 million. The GDOC project team has already communicated with EOS CEO Brendan Blumer, who has expressed strong interest for GDOC and the EOS team to form a technology partnership.

Secondly, GDOC's innovative Tri-partite division of power will completely address the problem of data property rights in the GDOC ecosystem chain. The original property rights of the data, similar to personal rights, can be granted to the data owner algorithmically, who can in turn authorize the use of data to qualified DApp (distributed App) developers in the GDOC ecosystem chain. The latter uses big data technologies to process properly authorized data, and create data application services such as advertising, social networking, push messages, shopping guides, etc. These services may eventually be offered to businesses off-chain, thereby maximizing its utility.

Thirdly, the GDOC ecosystem chain immutably records all data transactions, including the uploading of data to the system, the processing of data, data-application development, and various key business workflows. The immutable ledger provides a trusted basis for all market participants in the GDOC ecosystem chain, including data owners, data processors, and Dapp developers, to obtain their fair share of the revenue. Fairness is ensured by GDOC's unique CPA (Contribution Pricing Algorithm) real time pricing algorithm. CPA aims to alter the income disparity in the data exchange industry, currently dominated by big businesses. Data owners are incentivized to use GDOC, thereby creating conditions for the legitimate and compliant exchange of data.

Fourthly, as a DAO (Decentralized Autonomous Organization), the GDOC ecosystem neither relies on external resources, nor needs expensive trusted third-parties for market arbitration. This allows the ecosystem (from data to application services) to grow organically and autonomously. As a result, the transaction cost between the various entities can be greatly reduced. Specifically, the cost of data application services can be reduced with economies of scale. For example, a USD$2 ad impression on Facebook might cost just USD$0.20 or even lower at GDOC!

Fifthly, in addition to the CPA pricing algorithm, which protects the rights and benefits of all market participants, GDOC can provide the highest level of data security via the use of quantum key distribution technology.

The GDOC core team has a vision to provide the world with a safe, reliable, and distributed application ecosystem for large data transactions. This will genuinely make an impact on the current big data exchange market or ecosystem, which unreasonably and illegally tramples on individual data owner's rights. We hope to establish a relatively fair, transparent, and compliant DAO ecosystem that promotes autonomy, equality, and advancement for all.

We would love to hear your views.