China’s plan to establish a social credit system (SCS) has aroused the concern of building a surveillance state. Yet this view oversimplifies and misunderstands the essence of the SCS. The highest priorities of the SCS are promoting economic credibility and reinforcing court orders. Meanwhile, the SCS aims to steer citizens’ social behaviors and interactions by utilizing a redlist system that introduces numerous moderate rewards. The SCS is also more lax in execution than in planning. It reflects a unique Chinese understanding of law, which treats law as a moral guide. This article also acknowledges the concerns for the SCS. Without actively preventing positive and negative invasions in the construction of the project, the SCS authorities will risk creating further mistrust in society.
NFTs  are not just cat pictures that people trade on blockchains. Today digital art , collectibles , and in-game assets  are the most visible use cases for these nifty non-fungibles. But the market holds an inconspicuous secret: there is a staggering diversity of online digital content that can be placed on a blockchain in the form of NFTs.
As we use these services, they learn more and more about us. They see who we are, but we are unable to see into their operations or understand how they use our data. As a result, we have to trust online services, but we have no real guarantees that they will not abuse our trust. Companies share information about us in any number of unexpected and regrettable ways, and the information and advice they provide can be inconspicuously warped by the companies’ own ideologies or by their relationships with those who wish to influence us, whether people with money or governments with agendas.
To protect individual privacy rights, we’ve developed the idea of “information fiduciaries.” In the law, a fiduciary is a person or business with an obligation to act in a trustworthy manner in the interest of another. Examples are professionals and managers who handle our money or our estates. An information fiduciary is a person or business that deals not in money but in information. Doctors, lawyers, and accountants are examples; they have to keep our secrets and they can’t use the information they collect about us against our interests. Because doctors, lawyers, and accountants know so much about us, and because we have to depend on them, the law requires them to act in good faith—on pain of loss of their license to practice, and a lawsuit by their clients. The law even protects them to various degrees from being compelled to release the private information they have learned.
Given all the positivity surrounding SSI, and its laudable promise to give people control, it may be surprising to find an essay called “The dystopia of self-sovereign identity (SSI)”. Its author Philip Sheldrake warns the SSI community that their projects may achieve the opposite of what is intended, partly by viewing the problem too much from a technical perspective: “SSI cannot provide an ‘identity layer’ of the Internet any more than the Internet might be said to be missing a ‘truth layer’.”
The music industry group filed a copyright complaint with code repository Github, demanding that the project be taken down for breaching the anti-circumvention provisions of the DMCA. While this was never likely to be well received by the hoards of people who support the software, the response was unprecedented.
These reforms generally come in two varieties. Propertarian reforms diagnose the source of datafication’s injustice in the absence of formal property (or alternatively, labor) rights regulating the process of production. In 2016, inventor of the world wide web Sir Tim Berners-Lee founded Solid, a web decentralization platform, out of his concern over how data extraction fuels the growing power imbalance of the web which, he notes, “has evolved into an engine of inequity and division; swayed by powerful forces who use it for their own agendas.” In response, Solid “aims to radically change the way Web applications work today, resulting in true data ownership as well as improved privacy.” Solid is one popular project within the blockchain community’s #ownyourdata movement; another is Radical Markets, a suite of proposals from Glen Weyl (an economist and researcher at Microsoft) that includes developing a labor market for data. Like Solid, Weyl’s project is in part a response to inequality: it aims to disrupt the digital economy’s “technofeudalism,” where the unremunerated fruits of data laborers’ toil help drive the inequality of the technology economy writ large.5 Progressive politicians from Andrew Yang to Alexandria Ocasio-Cortez have similarly advanced proposals to reform the information economy, proposing variations on the theme of user-ownership over their personal data.
The second type of reforms, which I call dignitarian, take a further step beyond asserting rights to data-as-property, and resist data’s commodification altogether, drawing on a framework of civil and human rights to advocate for increased protections. Proposed reforms along these lines grant individuals meaningful capacity to say no to forms of data collection they disagree with, to determine the fate of data collected about them, and to grant them rights against data about them being used in ways that violate their interests.
This week, Congress released a report on big tech monopolies that makes clear what so many Americans instinctively know: A handful of powerful corporations rule over our lives and our economy. The report details the actions the four big tech platforms — Amazon, Google, Facebook and Apple — have taken in gaining and preserving their monopoly power across numerous markets. (Amazon CEO Jeff Bezos owns The Washington Post.) The report’s prescription for undoing their power is just as clear: We must break them up. Alongside this essential recommendation, the report also calls for strengthening the antitrust laws and adopting new rules to ensure the dominant platforms do not exploit their power. If we fail to confront the tech monopolies head on, the report argues, we relinquish our control over the way we shop, sell and speak to one another.
The thesis of the Berg et al. effort is that the key problem (at the margin, at least) is trust. The optimizing organizational response involves institutional cryptoeconomics. As they note, the chief problem in cryptoeconomics is designing mechanisms for generating reliable consensus; this is rather technical, and involves code that embodies solutions to strategic problems. Institutional cryptoeconomics asks what institutional forms will best embed cryptoeconomic solutions organically and with little friction into their daily operations.Again, the authors recognize the significance of their claim. If they are right, the new solutions to the problems of trust are just as important, and as disruptive, as the creation of the joint stock corporation. That means that the transformation, if it occurs, will happen on a massive scale and at breathtaking speed. The institutional advantages of the joint stock corporation, in terms of raising large amounts of capital and monitoring and enforcing contracts, were such that the commercial world went from “no corporations” to “above a certain size, only corporations” within a century. By analogy, at this point, uses of blockchain protocols to solve large-scale commercial problems are nearly unknown, but, in a few years, no other form of organization will be viable.
Social trust is linked to a host of positive societal outcomes, including improved economic performance, lower crime rates and more inclusive institutions. Yet, the origins of trust remain elusive, partly because social trust is difficult to document in time. Building on recent advances in social cognition, we design an algorithm to automatically generate trustworthiness evaluations for the facial action units (smile, eye brows, etc.) of European portraits in large historical databases. Our results show that trustworthiness in portraits increased over the period 1500–2000 paralleling the decline of interpersonal violence and the rise of democratic values observed in Western Europe. Further analyses suggest that this rise of trustworthiness displays is associated with increased living standards. Quantifying how social trust evolved throughout history can help us understand the long-run dynamics of our societies. Here, the authors show an increase in displays of trustworthiness, using a face processing algorithm on early to modern European portraits.