区块链技术可能即将找到它的杀手级用例：人工智能问责制

随着能够创建与现实几乎无法区分的文本、图片甚至视频的生成式人工智能模型的迅速崛起，全球的政策制定者都处于不利地位。

Generative AI models are capable of creating texts, pictures, and even videos that are virtually indistinguishable from reality. This technology has the potential to revolutionize many industries, but it also poses new challenges for policymakers.

生成式人工智能模型能够创建与现实几乎无法区分的文本、图片甚至视频。这项技术有可能彻底改变许多行业，但也给政策制定者带来了新的挑战。

One of the biggest challenges is ensuring that generative AI models are used responsibly. For example, if a deepfake of a politician admitting to a heinous crime goes viral and costs them the election, how do we discover who did it? Or if an AI model developed by a trading house crashes a national economy and causes financial instability, how do we hold the developers accountable?

最大的挑战之一是确保负责任地使用生成式人工智能模型。例如，如果一位政客承认犯有令人发指的罪行的深度伪造行为在网上疯传并导致他们失去选举，我们如何发现是谁干的？或者，如果贸易公司开发的人工智能模型导致国民经济崩溃并导致金融不稳定，我们如何让开发商承担责任？

To address these challenges, some policymakers are considering using blockchain technology to create an immutable evidence trail for generative AI models. This would allow regulators to track who created a particular model, what data was used to train it, and how it was used.

为了应对这些挑战，一些政策制定者正在考虑使用区块链技术为生成人工智能模型创建不可变的证据线索。这将使监管机构能够跟踪谁创建了特定模型、使用哪些数据来训练该模型以及如何使用该模型。

An immutable evidence trail would make it much easier to enforce regulations on generative AI models. It would also naturally disincentivize bad behavior in the first place. After all, people are less inclined to steal when they know a CCTV is watching them.

不可变的证据线索将使对生成人工智能模型的监管变得更加容易。它自然也会从一开始就抑制不良行为。毕竟，当人们知道闭路电视正在监视他们时，他们就不太愿意偷窃。

However, this doesn’t have to lead to a world without privacy; quite the opposite. By using privacy-preserving techniques, such as zk-SNARKs, we can keep sensitive data confidential while still allowing regulators to verify its authenticity.

然而，这并不一定会导致一个没有隐私的世界；恰恰相反。通过使用 zk-SNARK 等隐私保护技术，我们可以对敏感数据保密，同时仍允许监管机构验证其真实性。

At the recent London Blockchain Conference, FICO’s Scott Zoldi explained how the data analytics company uses a private blockchain to create accountability in AI. It stores the evidence trail on a private blockchain, which regulators can access as needed.

在最近举行的伦敦区块链会议上，FICO 的 Scott Zoldi 解释了这家数据分析公司如何使用私有区块链来创建人工智能问责制。它将证据追踪存储在私有区块链上，监管机构可以根据需要访问该区块链。

However, private blockchains have their limitations—one being that they are essentially databases controlled by the same entities regulators may be trying to investigate.

然而，私有区块链也有其局限性，其中之一是它们本质上是由监管机构可能试图调查的同一实体控制的数据库。

The solution is scalable public blockchains like BSV. These allow for sensitive data to be stored in private overlay networks while being linked back to cryptographic hashes of the data on a public chain. In this way, regulators can verify that data in the private networks has not been altered since its creation. Thus, we have an immutable evidence trail with sensitive data kept away from prying eyes but linked directly back to a public record that cannot be tampered with.

解决方案是像 BSV 这样的可扩展公共区块链。这些允许敏感数据存储在私有覆盖网络中，同时链接回公共链上数据的加密哈希值。通过这种方式，监管机构可以验证专用网络中的数据自创建以来没有被更改。因此，我们拥有一条不可变的证据线索，敏感数据远离窥探，但直接链接到无法篡改的公共记录。

Applied to the development of AI models, this would allow for data about the scientists and engineers, as well as any intellectual property and other confidential information about the models themselves, to be kept private while linking them back to a time-stamped record on a public, immutable blockchain that verifies what the sequestered data says.

应用于人工智能模型的开发时，这将允许有关科学家和工程师的数据以及有关模型本身的任何知识产权和其他机密信息保持私密，同时将它们链接回带有时间戳的记录。公共的、不可变的区块链，用于验证隔离数据的内容。

Is this pie-in-the-sky hypothetical, or does it have any basis in reality? As a matter of fact, Sentinel Node and Trace App, both blockchain apps developed in conjunction with IBM (NYSE:IBM), are already live and utilizing precisely what is described above.

这是天上掉馅饼的假设，还是有现实依据？事实上，Sentinel Node 和 Trace App 这两个与 IBM（纽约证券交易所股票代码：IBM）联合开发的区块链应用程序已经投入使用，并且正是利用了上述内容。

It’s only with the unanticipated explosion of generative AI models that the importance of such a technology is finally being realized. Of course, for it to work, the blockchain will need to be unboundedly scalable, and policymakers worldwide will have to recognize its potential as a solution and have the political will to mandate its use.

只有随着生成式人工智能模型的意外爆发，这种技术的重要性才最终被认识到。当然，要使其发挥作用，区块链需要具有无限的可扩展性，世界各地的政策制定者必须认识到它作为解决方案的潜力，并有政治意愿来强制使用它。