Exploring the Future of Web3 Social: Personal Identification and Cryptography Technology to Solve User Identity Issues

This article is the second in a series on decentralized social networking, exploring how current technologies and trends address a range of challenges faced by decentralized social networks.

In 2017, a group of researchers from the Media Lab at the Massachusetts Institute of Technology raised three major challenges faced by decentralized social networks in an article: attracting users from scratch, handling users' personal information, and the issue of user-targeted advertising. They argued that due to the scale advantages of tech giants, these issues are nearly impossible to solve.

However, to this day, these "impossible" challenges seem to have become surmountable. We are at the dawn of a paradigm shift in the concept of social media networks. This series of articles will explore how new ideas in decentralized social ( DeSo ) address these challenges, including:

1. Use open social layers to solve the cold start problem
2. Use personal identification and Cryptography technology to address user identification issues
3. Use a token economic model and incentive mechanisms to solve income issues.

This article will focus on the solution to the second problem.

Challenges of User Identification in Social Media

Modern social media is facing a serious bot problem. Bots have a significant impact on public discussions, from being accused of interfering in elections to influencing public perceptions of the pandemic. For decentralized social platforms that emphasize anonymity and privacy, convincing users that accounts on the platform are real and not bots is a huge challenge in the age of artificial intelligence.

A simple approach is to adopt traditional KYC protocols, but this immediately raises privacy concerns. Why should users trust any platform to store their sensitive personal data?

Therefore, the "user identification" issue is essentially about seeking a balance between confirming that the user "is indeed a person" and protecting personal data privacy. This article will explore two different solutions: biometric methods ( using zero-knowledge proofs ) and social assurance methods.

Biometric Identification Solutions

In the field of "identity verification", a certain project is one of the most well-known and controversial projects. The project's solution to the "personal verification" issue is very straightforward: it creates a biometric proof using retinal scans, proving that the user is a human and not a robot, and obtains a certification token. Regarding data privacy, the project claims to use zero-knowledge proofs to ensure the secure storage of biometric data.

The project believes that as the role of artificial intelligence in society grows, it is necessary to distinguish between humans and robots in a way that protects privacy and is decentralized. Through retinal scanning, users can obtain an ID similar to a "digital passport," which may qualify holders for a cryptocurrency-based global basic income and participation in new global democratic governance mechanisms.

However, despite these privacy protection statements, there are still many controversies regarding real privacy, security, and fairness guarantees. Reports have indicated that authentication credentials have been stolen and IDs are being sold on the black market. There are also overall fairness issues, with articles accusing the project of deception and exploitation of users during the testing phase. In fact, Kenya, once one of the largest data collection sites for the project, has banned related scanning activities due to security, privacy, and financial issues.

In addition to these specific controversies, there are broader concerns about the use of dedicated hardware for biometric authentication. Even if the software is flawless, there is no guarantee that the hardware is free of backdoors that allow for the secret collection of users' actual biometric data. For skeptics, all the project's privacy assurances seem like nothing more than a parody.

Social Guarantee Methods

Another way to solve the issue of identification is through social guarantees. The basic principle is that if multiple verified humans vouch for someone, then that person is very likely also human. The key is to design incentive mechanisms to maximize the "verification of humanity."

Some projects have adopted similar methods, using social graphs to verify a person's identification. This includes video call verification, mutual verification, continuous creation of verification codes and solving games, as well as trust circle-based verification, etc.

The biggest appeal of these platforms based on social verification is that they seem to be less invasive than biometric solutions. Some of these methods even retain a certain degree of anonymity, without requiring a large amount of personal data sharing or third-party identification centers.

The Future of Human Identification

With the continuous advancement of artificial intelligence, designing innovative human identification mechanisms has become increasingly important, not only for incentive measures such as universal basic income but also for better purifying and regulating future social networks.

However, from data privacy to the intrusiveness of processes, to the effectiveness of determining human identification, this process involves many trade-offs and is a dilemma in the cryptocurrency field. There seems to be no one ideal form of human identification; a possible hybrid approach is a biometrics-based starting method, but transitioning to more social graph-based methods in the long term.

Looking to the future, this field needs more process, code, and data transparency. In short, there can be no paradox where users need to "trust that this is a trustless solution." Only in this way can we truly create a social network foundation that aligns with the original vision of decentralization and privacy in Cryptography.