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About Victor Sint Nicolaas, Protocol Engineer - Provable

Victor Sint Nicolaas is Protocol Engineer at Provable. He loves to further the science of cryptography and mechanism design, and aims to bring them into the real world. Previously, he worked on securing taxation and identity software.

How to use zero-knowledge to coordinate economic entities

When looking at the privacy benefits of zero-knowledge proofs, even the smallest use case will involve different entities that don't fully trust each other. These entities might be different people, different organizations, or even different departments within an organization. Whenever such entities need to share information, zero-knowledge proofs can be of help. 

A natural starting point for thinking through privacy and social cooperation is to look at companies and how they interact with each other, which is well represented by Porter's Forces.

zk economic entities image 2

Relationship 1: Buyers and suppliers

One type of relationship where zero-knowledge proofs can increase trust is between buyers and suppliers. This is the most central relationship in the business world: if there is no buyer, there is no economy. From a supermarket and its supplying farmers, to an IT company and its supplying freelance designers - buyers and suppliers are all around us.

Buyers want to audit suppliers for durability, compliance, and other product properties. Think about it: have you ever bought a product or service, and would you like to gain a little bit more insight into the supplier's guarantees? Suppliers, on the other hand, want to audit the buyer for durability, solvability, etc.

So how can zero-knowledge improve the buyer-supplier relationship?

Increase transparency into algorithmic recommendations

A big topic here is algorithmic transparency of social media and dating services. Suppliers can prove to users exactly the algorithms which are being run. However, the real value capture here is dependent on the stakes of the algorithm.

If the algorithm is just serving users ads and relevant recommendations, the stakes are much lower than if an AI judge were serving a user a prison sentence based on data. In the latter example, verifying that a model is unbiased is more relevant to both parties than in the ads recommendation example.

Moreover, they can also prevent leaking too much information to the supplier. For example, if the supplier is a security auditor, instead of sending all your raw data, you could send some kind of proof of analysis on the data in order to verify that you as the buyer can prove compliance without revealing unnecessary information.

More trust in situations with information asymmetries

Zero-knowledge proofs can also prevent buyers from defrauding the supplier. An example of this is the privacy-preserving, vulnerability disclosure program FROMAGER. Actors can prove that they know a vulnerability exists in written code without revealing what the vulnerability actually is.

Proof of reserves and debts are incredibly useful to get assurances about the solvability of any business partner, whether they are a supplier or buyer. This dovetails into continuous financial auditing as a product that helps to coordinate information asymmetries.

There is also the idea of zero-knowledge middleboxes, which allows the operator of a router to ensure that users do not visit blacklisted websites. A school could use this to control the content that students can access, or a company can even use this to control different departments. In recent years, there has been a move towards zero-trust security: even within a single organization, the above examples can be used to build trust between departments.

Relationship 2: Complements and partners

The economy consists of more than just atomic buyers and suppliers. In many cases, companies forge alliances and need to prove good intent. Companies could prove their profitability to each other, or they could prove that indeed all of their products adhere to the agreed-upon standards. When shared resources are bought collectively, guarantees about the product can be made.

Some go a step further, and state that collaboration opens up fundamental new pathways to economic growth. Lunar Venture's collaborative computing thesis states that entirely new products can be created by making use of shared data. Additional tools like homomorphic encryption and multi-party computation can be used to do private calculations on sensitive data without making everything public. Zero-knowledge proofs are an additional tool that can provide useful guarantees about the information that different parties are supplying.

Relationship 3: Competitors, substitutes and… governments!

So far, we discussed all the different entities which a company may voluntarily want to interact with. Is there anything that zero-knowledge proofs can do to improve the other economic relationships, those between distrusting competitors and substitutes? The answer is yes, and the key to such relationships is the government and regulatory framework under which everyone operates.

Most of the law operates under spot checks: the government periodically checks whether companies pay the appropriate taxes, that companies don't have too much market power, and that the environment is taken into account. In many cases, it takes a mob of people and media to point governments to a problem, when it is already too late. Even in this scenario, we can use zero-knowledge proofs to strengthen whistleblowers' claims. Stakeholders prove that fraudulent behavior exists, without revealing who they are exactly.

However, there are also many scenarios where zero-knowledge proofs can help to ensure compliance by design. Companies can submit proof of correct taxation, proof of contractual arrangements, and more. It is hard to understate how much more flexible and powerful compliance can become. To avoid Venture Predation, one can even envision firms having to reveal more information to competitors who are similar. Or even generalizing this: conditionally reveal information based on the other party's information. This gives you much more control over the economy to fight externalities.

The role of trustworthy payments infrastructure

In order for all of the above economic relationships to thrive, it is key that companies can operate using a reliable and secure payments infrastructure. Ideally:

  • There is a static or slowly increasing supply of currency, with little risk of runaway inflation

  • User's day-to-day transactions are fully private to outside observer

  • Controlling entities have little but non-zero insight into activities deemed illegal

  • Users have an insight into who owns current and future currency

At first sight, features two and three might seem at odds with each other. However, zero-knowledge proofs can help to make this a reality. And regarding point four: In the long run, it would be of tremendous value for the world if users could somehow receive some kind of aggregate statistics about where the currency is being used. All of these can help inform people which currencies to use, to provide as many benefits to themselves and those they care about.

Conclusion

Zero-knowledge proofs can enhance privacy and trust in a wide range of economic relationships, including buyer-supplier dynamics and collaborations. They can also offer innovative solutions for regulatory compliance and accountability. By enabling secure and private digital transactions, individuals and businesses can take control of their financial interactions while preserving the utmost confidentiality.

Provable’s zero-knowledge ecosystem can bridge the gap between transparency and privacy in algorithmic systems, protect against fraud, and strengthen whistleblowing claims underlines its significance in today's data-driven and interconnected world. Our programming language Leo allows you to create zero-knowledge proofs about any programmatically defined logic. This can be related to your own cryptocurrency, or related to specific data structures about which you want to make guarantees.

Create a React Leo app

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About Victor Sint Nicolaas, Protocol Engineer - Provable

Victor Sint Nicolaas is Protocol Engineer at Provable. He loves to further the science of cryptography and mechanism design, and aims to bring them into the real world. Previously, he worked on securing taxation and identity software.

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