In yesterday's article, I shared the potential risks that AI applications can pose to personal privacy.

The reason for these risks is due to the operational model of current AI applications---when end users call upon AI, they directly upload their data to AI big models located in the cloud, which then infer user behavior characteristics based on the data.

The longer this accumulation of data lasts, the better AI big models can master users' comprehensive behavioral habits through algorithms.

This risk represents a privacy leak for individuals and a leak of trade secrets for companies.

In a video interview last year, Huang Renxun mentioned this risk regarding AI and strictly required his company's employees to know what data must remain local and what data can be uploaded to the cloud when using AI tools.

However, at that time, I only considered this risk as information, and I only remembered his warning when I personally experienced this risk.

This issue has just started to surface, but it will soon escalate.

Therefore, I believe that in the future, as AI becomes more widespread, we will need a terminal (whether a phone, glasses, or another form we cannot yet imagine) that runs a streamlined big model locally, processes most sensitive data locally, infers simple requirements, and only uploads some heavy tasks and data to the cloud after "filtering" for the complex big model in the cloud to handle. This will avoid the cloud's big model from directly capturing the user's personal behavioral characteristics.

Moreover, in the encryption ecosystem, the handling of privacy has long been on the agenda.

In the early days, Vitalik mentioned that public chains like Ethereum face challenges for large-scale use in the business field due to the transparency and openness of data and information---because in many cases, parties in business transactions are reluctant to publicly disclose transactional information to protect trade secrets.

Recently, some commercial users pointed out that they are currently very cautious about the large-scale use of stablecoins. Because stablecoin accounts on public chains are open, it means anyone can see how much stablecoin a particular account holds. Once an account's identity information is leaked, it becomes transparent information about which companies/businesses hold how much funds (stablecoins).

Therefore, whether in AI or the encryption ecosystem, privacy issues are problems that must be solved next.

However, if we carefully compare the applications of privacy in AI and the encryption ecosystem, at least it seems that encryption applications are ahead---the encryption ecosystem already has privacy coins (like Monero, ZCASH, etc.) and mixers.

However, these privacy applications are actively avoiding regulation, so they have been somewhat stigmatized.

The privacy applications that can truly be accepted by the public and regulators now seem to be more mature and feasible are likely based on zero-knowledge proof solutions, such as a method that has been experimented with:

Having a licensed regulatory institution act as an intermediary, both parties in the transaction go through this intermediary, but the identity and transaction information are hidden, with only the final generated zero-knowledge proof placed on the public chain for certification.

This ensures transaction information privacy while allowing the parties to avoid criminal suspicion.

I hope that in the protection of privacy and compliance in transactions, the exploration and application within the encryption ecosystem can leverage its advantages to first carve out a new path for AI applications.

免责声明：本文章仅代表作者个人观点，不代表本平台的立场和观点。本文章仅供信息分享，不构成对任何人的任何投资建议。用户与作者之间的任何争议，与本平台无关。如网页中刊载的文章或图片涉及侵权，请提供相关的权利证明和身份证明发送邮件到support@aicoin.com，本平台相关工作人员将会进行核查。