User Identification Issues: Key Challenges of Decentralization in Social Web

In the development process of decentralized Social Web, user identification has always been a highly concerning issue. The core of this problem lies in how to effectively identify real users and bot accounts while protecting user privacy.

In recent years, the impact of robots on public discussions has become increasingly significant, influencing elections and shaping public perceptions of major events. For decentralized platforms that emphasize anonymity and privacy protection, how to convincingly prove the authenticity of platform users in today's era of advanced artificial intelligence is a pressing challenge that needs to be addressed.

Simply adopting traditional KYC solutions obviously cannot meet the needs of a Decentralization platform, as this would raise serious privacy issues. Users have no reason to believe that any platform can securely store their sensitive data.

Therefore, the key to user identification lies in seeking a balance between confirming the user's authenticity and protecting personal privacy. Currently, there are two main solutions: methods based on biometrics and methods based on social guarantees.

A well-known project has adopted retinal scanning technology to create biometric proofs to distinguish between humans and robots. The project claims to use technologies such as zero-knowledge proofs to protect user privacy. However, this solution still faces many controversies, including the effectiveness of privacy protection, data security, and overall fairness.

Another approach is to use the Social Web method. The core idea is that if multiple verified real users vouch for a new user, then that new user is likely to be real as well. The key to this method lies in designing a reasonable incentive mechanism to maximize the effectiveness of "verification of human".

A certain project requires users to submit personal information and a deposit, with registered users acting as guarantors. If anyone questions it, the case will be submitted to a Decentralization court for adjudication. Similar projects include solutions based on video call verification, as well as gamified solutions based on continuous verification code generation and resolution.

These social verification-based solutions seem less intrusive compared to biometric solutions, and some of them can even maintain a degree of anonymity. However, they also face their own challenges, such as how to effectively prevent cheating.

With the advancement of AI technology, designing novel and effective human identification mechanisms has become increasingly important. This is not only related to applications such as universal basic income for certain project concepts but also key to the healthy development of the future Social Web.

However, from data privacy to the intrusiveness of processes, and then to the effectiveness of verification, this process involves many trade-offs. Some believe that a hybrid approach may be needed: relying on biometric methods in the short term, while transitioning to more Social Web-based methods in the long term.

In the future, this field needs more process transparency, open-source code, and public data. Only in this way can we truly create a social web infrastructure that aligns with the concepts of Decentralization and privacy protection.