Give us a little social credit: to design or to discover personal ratings in the era of Big Data

Give Us a Little Social Credit: To Design or to Discover Personal Ratings in the Era of Big Data

The article considers the key features of the social credit (rating) system implementation and functioning, which is the main tool for digitalization of Chinese society, and in the future is considered by the Chinese authorities as a basic mechanism of electronic government. The historical retrospective of the phenomenon of social rating emergence and development, which was later transformed into social credit, is presented. Attention is paid to the differences in the implementation and functioning of the social credit system, depending on regional characteristics. The participants in the social credit system and the main mechanisms for collecting information for the social credit level formation, including through the mandatory use of specially designed ID-cards, and recently the almost widespread use of the verification for a person by face, have been determined. Despite the position of the Chinese authorities, according to which the use of the social credit system is successful, a list of shortcomings that are now inherent in this system, both of an author’s and of an expert nature, is given. The practice of implementation the state digital eco-environment «Diia» (State and I), which is a key tool for building a digital state, as well as the functional content of the «Diia» eco-environment (service) and its main components, is analyzed. The basic shortcomings that are now inherent in the service are determined, in particular, the key tool in the fight against coronavirus – «Diia. Vdoma», as well as the controversial character of the proposed innovation for the business environment «Diia. City». The features of the declared novel of the relationship between the citizen and state ‒ the concept of «paperless», are studied. The issue of regulation of the «Diia» eco-environment functioning is raised in the context of the legislative introduction of the concept of «paperless» announced on September 1, 2021. The conclusion is substantiated that the basic mechanisms are already being introduced in Ukraine, which form the basis for the Chinese social credit system functioning, in particular, through the tools of citizensʼ verification. On the basis of the analysis carried out, proposals are made to improve the functionality of the «Diia» eco-environment.

Credit market knowledge and education in our country although initially with the legal environment and competitive mechanisms which Compatible with the market economy, however, in line with the market economy has not yet formed a credit institution, credit system. Especially the concept of credit business, civil society and the whole is still far from meeting the requirements of the market economy. An important part of college honesty education is the college education of credit market knowledge, Conduct college education of credit market knowledge, is the fundamental way as soon as possible with the social credit system construction standards.

The Transparent Self Under Big Data Profiling: Privacy and Chinese Legislation on the Social Credit System

The social credit system, created in the PRC in 2014 and which has been in widespread use since approximately 2016, is being evaluated.The assessment by the population is being considered. An estimate expressed in market indicators is given. Assessment by a learned community trying to comprehend the social credit system in terms of the paradigm of authoritarian government analyzed.The results of the consideration of market indicators show that the introduction of the social credit system did not have an impact on business climate indicators such as BCI or PMI.Meanwhile, for the sake of business climate indicators, the social credit system was introduced, as was stated when it was created: this system was designed to prevent unscrupulous behavior of frms. Thus, the declared goal of introducing a social credit system was not achieved.It seems logical to wonder if there was a different goal from the declared goal of introducing social credit, the goal of strengthening the tendency of authoritarian government.At the same time, point studies of the assessment of the social credit system by the population showed a high level of approval of social credit by citizens.Western liberal thought with its cult of individualism sees the following consequences of the introduction of a social credit system: violation of human rights, non-observance of the principle of social justice, violation of the principle of privacy, violation of the principle of equality of rights, development of totalitarian and authoritarian tendencies.It is assumed that some conclusions based on this approach may be called into question due to a mismatch of values: it is proved that assessment categories based on the values of extreme individualism are poorly applied to Chinese society, whose ideology is based on collectivist values.In this regard, a fundamentally different approach is applied to assessing the social credit system: signs of authoritarianism are postulated as the presence of unequal opportunities for symbolic construction of reality; the social credit system is tested for such capabilities within the theory of mass communication.The social credit system used to control the content of Internet sites will have an extremely negative impact on political communication, making it more asymmetric, on the democratic structure of the political system and human quality.

This paper focuses on the probable transformative effects of the application of the Chinese Social Credit System and similar projects in the realm of public administration on constitutional rights and freedoms, balances in citizen-state relations, and the model of statehood. The starting point of the research is the assumption that the Social Credit System, despite its specifically national Chinese peculiarities, can be seen as a reflection of a broader tendency towards the use of reputational information, techniques of ranking (grading) and risk management in the process of exercising the state power. To test this hypothesis, the author analyzes the actual experience of the Social Credit System’s introduction in the People’s Republic of China, compares this project with e-government projects, and proposes the umbrella-term of “social-credit mechanisms” to describe procedures and means of social control, based on the permanent collection and analysis of reputation data relating to persons. It is argued in this paper that the introduction of social-credit mechanisms to the practice of public administration ultimately leads to the emergence of a gap between formally enshrined rights and the actual ability to exercise them, between the legal capacity of a person and the ability to realise this capacity in certain legal relations. Examining the prospects of introduction of reputation-based social-credit mechanisms to the public administration, the author notices the probability of discrimination against persons who took a false step. As is demonstrated in the paper, the use of reputation data and social ratings by state authorities may result in the gradual differentiation in quality and scope of public services depending on social ratings (grades) of their addressees. This state of affairs may signify the birth of a new caste society and the end of the principle of equality before the law. According to the conclusions made in the paper, projects akin the Chinese Social Credit System reflect the global tendency towards the formation of a new type of constitutionalism. In the framework of this new constitutionalism the main emphasis will be shifted from citizens’ democratic participation in the execution of state power and the citizenry’s political subjectivity to ensure public safety and social stability. The issue of social-credit mechanisms’ introduction to the process of public administration is de facto an issue between the values of freedom and the values of security — the issue of choosing between political subjectivity and guaranteed biological existence.

This article examines the normative legal framework and principles of functionality of the Social Credit System that is currently being implemented in the People's Republic of China. For the first time in legal science, the Social Credit System is viewed not as an organizational and regulatory technique that in one or another way is related to law, but rather as an independent legal institution relevant to the branch of administrative law. The application of formal-legal and comparative-legal methods allows describing the hierarchy of sources of the Chinese law pertaining to social credit mechanisms and procedures, as well as giving characteristics to major provisions of the corresponding normative acts. The peculiarities of legal regulation of the mechanisms and procedures that comprise the Social Credit System in PRC include the following aspects: sublegislative nature of such regulation, prevalence of joint lawmaking, focal role of normative legal acts of the Chinese government, declarative character and ambiguity of multiple legal provisions with regards to the Social Credit System. The author underline the specificity of interpretation of the normative legal acts of the People's Republic of China, usage by the lawmaking branches of moral categories in formulation of provisions for regulation of elaboration and implementation of the social credit mechanisms. The provisions of governmental and departmental normative legal acts pertaining to the Social Credit System are correlated with the provisions of the current Constitution of the People's Republic of China.

The banking system is the most important mechanism for organizing cash flows in the country, ensuring the flow of capital between its suppliers and consumers through credit mechanisms. Social credit system, the main beneficiaries of which are socially vulnerable segments of the population, involves the state as a mandatory participant in the system, which creates programs to support vulnerable segments of the population, provides budgetary funds to subsidize interest rates and compensate part of the loans, and acts as a guarantor of the sustainability of the system. The purpose of the study is to develop theoretical and methodological principles and develop scientific and practical recommendations for modernizing the social credit system in the Russian Federation. Methodology: The study is based on an integrated approach, the implementation of which involves the use of the dialectical method, as well as methods of logical and comparative analysis, deduction and induction using observation and expert questioning, thereby ensuring a high level of data reliability when processing empirical material as the basis for conclusions and proposals. Results: a conceptual conflict is established in the theoretical and methodological basis of the social credit system, and a notion and theoretical justification for this definition are proposed, allowing one to crystallize the economic essence of social credits. It is substantiated that the current social credit system in Russia focuses on the mortgage component, in which the level of paternalism is higher than the social effect from the use of budget funds. State programs to support social credit system are systematized, clarifying their conditions and impact on competition and paternalism in this area. Recommendations for modernizing the social credit system are substantiated, based on the introduction of social rating elements into the current system, developed and successfully tested in China. The author's program “Preferential Loan” is proposed, combining elements of the social credit system in force in Russia and the social rating system of the People's Republic of China. An original mechanism for modernizing social credit system in the Russian Federation has been developed, which includes the subjects of the system, the substantive aspect of the relationship between them, digital technologies and information infrastructure.

China's Online Consumerism: Managing Business, Moral Panic and Regulation

PurposeThe purpose of this paper is twofold: first, to explore how China uses a social credit system as part of its “data-driven authoritarianism” policy; and second, to investigate how datafication, which is a method to legitimize data collection, and dataveillance, which is continuous surveillance through the use of data, offer the Chinese state a legitimate method of monitoring, surveilling and controlling citizens, businesses and society. Taken together, China’s social credit system is analyzed as an integrated tool for datafication, dataveillance and data-driven authoritarianism.Design/methodology/approachThis study combines the personal narratives of 22 Chinese citizens with policy analyses, online discussions and media reports. The stories were collected using a scenario-based story completion method to understand the participants’ perceptions of the recently introduced social credit system in China.FindingsChina’s new social credit system, which turns both online and offline behaviors into a credit score through smartphone apps, creates a “new normal” way of life for Chinese citizens. This data-driven authoritarianism uses data and technology to enhance citizen surveillance. Interactions between individuals, technologies and information emerge from understanding the system as one that provides social goods, using technologies, and raising concerns of privacy, security and collectivity. An integrated critical perspective that incorporates the concepts of datafication and dataveillance enhances a general understanding of how data-driven authoritarianism develops through the social credit system.Originality/valueThis study builds upon an ongoing debate and an emerging body of literature on datafication, dataveillance and digital sociology while filling empirical gaps in the study of the global South. The Chinese social credit system has growing recognition and importance as both a governing tool and a part of everyday datafication and dataveillance processes. Thus, these phenomena necessitate discussion of its consequences for, and applications by, the Chinese state and businesses, as well as affected individuals’ efforts to adapt to the system.

China's national policy formulation undergone economic transformation and shaped the making of policies in promotion of private business and stock market regulation. China's distinctive process of central-local interaction in policy generation is one of its core strengths in reforming its economy.

Photo by Josh Riemer on Unsplash
 Introduction
 With the rapid advancements in neurotechnological machinery and improved analytical insights from machine learning in neuroscience, the availability of big brain data has increased tremendously. Neurological health research is done using digitized brain data.[1] There must be adequate data governance to secure the privacy of subjects participating in brain research and treatments. If not properly regulated, the research methods could lead to significant breaches of the subject’s autonomy and privacy. This paper will address the necessity for neuroprotection laws, which effectively govern the use of big brain data to ensure respect for patient privacy and autonomy.
 Background
 Artificial intelligence and machine learning can be integrated with neuroscience big brain data to drive research studies. This integrative technology allows patterns of electrical activity in neurons to be studied in detail.[2]Specifically, it uses a robotic system which can reason, plan, and exhibit biologically intelligent behavior. Machine learning is a method of computer programming where the code can adapt its behavior based on big brain data.[3] The big brain data is the collection of large amounts of information for the purpose of deciphering patterns through computer analysis using machine learning.[4] The information that these technologies provide is extensive enough to allow a researcher to read a patient’s mind. AI and machine learning technologies work by finding the underlying structure of brain data, which is then described by patterns known as latent factors, eventually resulting in an understanding of the brain’s temporal dynamics.[5]
 Through these technologies, researchers are able to decipher how the human brain computes its performances and thoughts. However, due to the extensive and complex nature of the data processed through AI and machine learning, researchers may gain access to personal information a patient may not wish to reveal. From a bioethical lens, tensions arise in the realm of patient autonomy. Patients are not able to control the transmission of data from their brains that is analyzed by researchers. Governing brain data through laws may enhance the extent of patient privacy in the case where brain data is being used through AI technologies.[6] A responsible approach to governing brain data would require a sophisticated legal structure.
 Analysis
 Impact on Patient Autonomy and Privacy 
 In research pertaining to big brain data, the consent forms do not fully cover the vast amounts of information that is collected. According to research, personal data has become the most sought out commodity to provide content to corporations and the web-based service industry. Unfortunately, data leaks that release private information frequently occur.[7] The storage of an individual’s data on technologies accessible on the internet during research studies makes it vulnerable to leaks, jeopardizing an individual’s privacy. These data leaks may cause the patient to be identified easily, as the degree of information provided by AI technologies are personalized and may be decoded through brain fingerprinting methods.[8]
 There has been an extensive growth in the development and use of AI. It is efficient in providing information to radiologists who diagnose various diseases including brain cancer and psychiatric disease, and AI assists in the delivery of telemedicine.[9] However, the ethical pitfall of reduced patient autonomy must be addressed by analyzing current AI technologies and creating more options for patient preference in how the data may be used. For instance, facial recognition technology[10] commonly used in health care produces more information than listed in common consent forms, threatening to undermine informed consent. Facial recognition software collects extensive data and may disclose more information than a person would prefer to provide despite being a useful tool for diagnosing medical and genetic conditions.[11] In addition, people may not be aware that their images are being used to generate more clinical data for other purposes. It is difficult to guarantee the data is anonymized. Consent requirements must include informing people about the complexity of the potential uses of the data; software developers should maximize patient privacy.[12] Furthermore, there is a “human element” in the use of AI technologies as medical providers control the use and the extent to which data is captured or accessed through the AI technologies.[13] People must understand the scope of the technology and have clear communication with the physician or health care provider about how the medical information will be used. 
 Existing Laws for Brain Data Governance 
 A strict system of defined legal responsibilities of medical providers will ensure a higher degree of patient privacy and autonomy when AI technologies and data from machine learning are used. Governing specific algorithmic data is crucial in safeguarding a patient’s privacy and developing a gold standard treatment protocol following the procurement of the information.[14] Certain AI technologies provide more data than others, and legal boundaries should be established to ensure strong performance, quality control, and scope for patient privacy and autonomy. For instance, currently AI technologies are being used in the realm of intensive neurological care. However, there is a significant level of patient uncertainty about how much control patients have over the data’s uses.[15] Calibrated legal and ethical standards will allow important brain data to be securely governed and monitored.
 Once brain signals are recorded and processed from one individual, the data may be merged with other data in Brain Computer Interface Technology (BCI).[16] To ensure a right and ability to retrieve personal data or pull it from the collection, specific regulations for varying types of data are needed.[17] The importance of consent and patient privacy must be considered through giving patients a transparent view of how brain data is governed.[18] The legal system must address discriminatory issues and risks to patients whose data is used in studies. Laws like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Protection Act (CCPA) can serve as effective models to protect aggregated data. These laws govern consumer information and ensure the compliance when personal data is collected.[19] California voters recently approved expansion of the CCPA to health data. The Washington Privacy Act, which would have provided rights to access, change, and withdraw personal data, failed to pass. Other states should improve privacy as well,[20] although a federal bill would be preferable. Scientists at the Heidelberg Academy of Sciences argue for data security to be governed in a manner that balances patient privacy and autonomy with the commercial interests of researchers.[21] The balance could be achieved through privacy protections like those in the Washington Privacy Act. Although the Health Insurance Portability and Accountability Act (HIPAA) provides an overall framework to deter the likelihood of dangers to patient protection and privacy, more thorough laws are warranted to combat pervasive data transfer and analysis that technology has brought to the health care industry.[22] Breaches of patient privacy under current HIPAA regulations include releasing patient information to a reporter without their consent and sending HIV data to a patient’s employer without consent.[23] HIPAA does not cover information being shared with outside contractors who do not have an agreement with technology companies to keep patient data confidential. HIPAA regulations also do not always address blatant breaches on patient data confidentiality.[24] Patients must be provided with methods to monitor the data being analyzed to be able to view the extent of private information being generated via AI technologies. In health research, the medical purposes of better diagnosis, earlier detection of diseases, or prevention are ethical justifications for the use of the data if it was collected with permission, the person understood and approved the uses of the data, and the data was deidentified.
 A standard governance framework is required in providing the fairest system of care to patients who allow their brain data to be examined. Informed consent in the neuroscience field could reaffirm the privacy and autonomy of patients by ensuring that they understand the type of information collected. Laws also could protect data after a patient’s death. Malpractice in the scope of brain data could give people a cause of action critical in safeguarding patient’s rights. Data breach lawsuits will become common but generally do not cover deidentified data that becomes part of big data collection. A more synchronized approach to the collection and consent process will encourage an understanding of how big data is used to diagnose and treat patients. Some altruistic people may even be more likely to consent if they know the largescale data collection is helpful to treat and diagnose people. Others should have the ability to opt out of sharing neurological data, especially when there is not certainty surrounding deidentification.[25]
 Conclusion
 Artificial intelligence and machine learning technologies have the potential to aid in the diagnosis and treatment of people globally by extracting and aggregating brain data specific to individuals. However, the secure use of the data is necessary to build trust between care providers and patients, as well as in balancing the bioethical principles of beneficence and patient autonomy. We must ensure the highest quality of care to patients, while protecting their privacy, informed consent, and clinical trust. More sophis

The improvement of the social credit environment and corporate ESG performance - evidence from the "construction of china's social credit system"

Purpose The purpose of this study uses data of companies listed on the Shanghai and Shenzhen A-shares between 2012 and 2021 and uses the staggered difference-in-differences (DID) causal inference method to evaluate the impact and mechanisms of China’s social credit system construction (CSCSC) on labor employment decisions. Design/methodology/approach This scenario conforms to two key elements of staggered DID. First, micro-enterprises were not uniformly affected by policy shocks over time (2017 with 12 cities, 2019 with 16 cities and 2021 with 34 cities). Second, since the onset of policy impacts, there has been no instance of micro-enterprises exiting the pilot policies, meaning there was no occurrence of policy withdrawal or reversal. Findings The findings of this study are as follows: first, the pilot policy for CSCSC has resulted in an approximate increase of 3.10% in enterprise labor employment. Second, the CSCSC has facilitated the expansion of labor employment by augmenting the scale of debt financing, diminishing the cost of debt financing and curtailing the supply of commercial credit. Furthermore, heterogeneity analysis demonstrated that the pilot policy for CSCSC has a more pronounced effect on enhancing enterprise labor employment when the labor market supply is abundant and the degree of regional marketization and the relationship between government and market are both relatively low, particularly for small-scale, non-state-owned enterprises with weak profitability. Research limitations/implications Chinese listed companies constitute only a subset of the firms affected by the credit policy. An analysis of how the social-credit-system reform influences employment structure within this sector cannot, by definition, demonstrate that the same effects apply to unlisted firms. Future research could usefully examine whether, and the extent to which, China’s social-credit-system reform and related policy measures influence the evolution of employment structures. Practical implications Given that the construction of the social credit system has been shown to significantly increase the scale of enterprise labor employment, policymakers are advised to consider the continued expansion of this system to foster the growth and development of additional enterprises. Considering that China’s central regions derive greater benefits from the social credit system, it is imperative that the state intensifies its support for these areas, including measures such as fiscal and tax incentives, to promote balanced regional development. Social implications The policymaker should take into account the positive impacts of the social credit system construction on different regions and types of enterprises, and accordingly adjust and refine related policies and measures to fully leverage the role of the social credit system in promoting economic development and corporate growth. Employment is recognized as the paramount aspect of people’s welfare and acknowledged as the most fundamental foundation of economic growth. Originality/value The marginal contribution of this study is mainly reflected in the following three aspects. First, it supplements the literature on the impact of social credit on macro-employment behavior. Second, this study innovatively explores the impact of the social credit system construction on labor employment decisions from a human capital perspective. Finally, the limitations of existing research have been addressed by this study, contributing to an enhanced understanding of the effects of social credit system construction on labor employment decisions in pilot area enterprises.

The development of a digital social credit system in China has sparked debates around urban governance and citizenship performance. Although China’s social credit system is portrayed as a single technical system, the article offers a new perspective on digital social credit focused on geographical variegation. We analyze how variegation is manifested through use of multiple data streams and a diverse range of aims operationalized in various social credit systems at the municipal level. Social credit can be seen as part of algorithmic urban governance and an instrument of urban citizenship performance through scoring, ranking, incentives, and punishments. Analysis of social credit systems’ development in Chinese cities contributes to debates around the role of the urban Global East and evolution of digital and algorithmic governance in and beyond China.