The internet has seen a massive amount of progress over the years, but it still suffers from a number of problems, such as privacy issues. With personal data leaks, endless oversharing on platforms, and now AI systems making decisions with little to no transparency, users have become more vulnerable than ever. With traditional privacy tools failing, programmable privacy emerged as an alternative.
The problem with traditional privacy tools, such as ad blockers, encrypted chats, and even zero-knowledge privacy enabled by ZK proofs, is that they are not enough anymore. They still help, but they do not give internet users full control over their data, and how, when, and why it is being used.
Programmable privacy does, making it the next step after ZK proofs and basic privacy tools. It allows users to set conditions, automate their protections, and decide what to reveal and when.
What Is Programmable Privacy?
At the basic level, programmable privacy means granting users the ability to control their own information, such as when they want to share it, with whom, how much, and under what precise conditions the data sharing is going to happen. Users can set up these rules, which are then applied by an algorithm, making them more adaptable than traditional solutions.
This is a system based on specific rules, where users get to program the way their data is being shared, similarly to what can be done with automated, recurring payments or smart contracts. The idea comes from two different sources: zero-knowledge proofs, blockchain privacy, and AI.
ZK proofs were introduced originally when they brought the ability to prove that something is true without exposing the actual data. Meanwhile, as AI platforms evolved, the need for greater, more complex levels of privacy emerged here as well. Ultimately, programmable privacy was built using these foundations, as it needed a system with a set of rules that firmly protect the data, but are also flexible enough to be applied to a variety of situations.
It now combines cryptographic tools with the ruleset defined by the user, as well as machine learning. The result is a new privacy layer that is both enforceable as well as dynamic.
The Core
Programmable privacy was built using three different ingredients: Zero-Knowledge Proofs (ZKPs), AI-based context awareness, and User Controls.
As mentioned earlier, ZKPs were designed to enable verifying information without revealing the sensitive data. This is a cryptographic technique that represents the very basis of programmable privacy, as it ensures that sensitive data does not leave the user’s device unless the user allows it.
Next, AI for context-aware privacy is what makes programmable privacy more advanced than the old solutions. The way it works is that it doesn’t apply the same rules everywhere, but rather, it uses AI to assess different situations and modify privacy settings to match those situations. AI can detect when it is necessary to share data, but also whether or not it is safe to do so. This is possible thanks to its ability to make decisions based on its situational awareness.
Finally, User Controls allow real people to set the rules, or create exceptions for unique situations where even programmable privacy’s flexible ruleset doesn’t properly apply.
Why do Zero-Knowledge Proofs Strengthen Privacy?
Zero-knowledge proofs represent the heart of programmable privacy because they allow people to prove that something is true without exposing the underlying information. In practice, this means that the user can confirm their identity, balances, or permissions without having to share sensitive details with the entity they are interacting with.
By limiting what data is revealed, zero-knowledge proofs can significantly reduce the risks of data leaks, surveillance, and similar threats, and at the same time, keep blockchains verifiable.
Benefits for everyday users
While programmable privacy has plenty of applications in the world of enterprises, it can be much more than that, and everyday users can benefit from it, as well. It can be used in everyday life to provide individual users with a way to use their data freely and safely at the same time. For example, it can offer:
1. Safe identity checks
One of the biggest improvements in everyday life would be a safer way to handle sensitive documents and data, such as safe identity checks. This would allow users to prove their identity without exposing themselves to risks. For example, when buying goods reserved for adults only online, such as alcohol, users could confirm that they are an adult without revealing their date of birth.
2. Control over sensitive information
As discussed previously, programmable privacy offers users the ability to set up specific rules and decide who gets to see them, when, why, and so on. An example would be a social app offering friend suggestions by listing people in the user’s area without revealing their exact location.
3. Protection from data leaks
Programmable privacy can also protect users from data leaks, since less data is being shared. With less data travelling through the systems, the possibility of bad actors intercepting it is lower, as well.
4. Automated privacy settings
By using artificial intelligence, users’ privacy can be modified in real time to match any given situation. For example, AI can detect that the user is connected to public WiFi, and hide their work contacts, but have them enabled when they are in the office.
5. Easy compliance
Programmable privacy can even transform compliance and eliminate the need to handle cookie banners and privacy policies. Systems could enforce GDPR and HIPAA-level protections in the background and simplify user experience.
Data Transparency Made Simple
Thanks to its ability to allow users to choose exactly what data is being shared, programmable privacy can enable selective transparency. Current systems cannot offer this, as they only let you reveal everything or hide everything, while programmable privacy lets you reveal what is necessary while keeping other sensitive information hidden.
For example, in the healthcare industry, patients can use platforms powered by ZK proofs to prove that they are vaccinated without exposing their entire medical history. This can also come in handy during travel, and it would have been useful during the COVID-19 pandemic.
Another example would be in the financial industry, such as when the user wishes to apply for a loan. Instead of sharing entire bank statements, they could offer selected pieces of information that prove that their income is high enough to qualify for the loan they want.
Users could even use this to verify that they are real humans when trying to access platforms that have some sort of anti-bot system, without having to reveal their identity, location, or other sensitive details.
What are the best programmable privacy services right now?
With programmable privacy becoming a major new trend in the world of data security, many services and platforms are built around it. Here are some of the most notable examples:
- Aleo - This is a blockchain built with privacy as its main focus. It uses Decentralized Private Computation to offer shielded identities, private transactions, and programmable applications.
- Mina Protocol - Mina Protocol, also known as the lightest blockchain, stands out thanks to its zkApps, which were created in TypeScript. They allow developers to choose what data to make public when conducting off-chain computation verified on-chain.
- Secret Network - This is the first blockchain that supports privacy-oriented smart contracts, and it does so using Trusted Execution Environments, which enable features like shielded NFTs, private messages, and AMMs that can resist censorship
- Oasis Network - Oasis Network consists of privacy-enabled chains created using modular paratimes. Oasis offers custom environments, including both public and private (confidential) ones, which are used for processing data.
- Zcash - Zcash is well-known in the crypto industry as a privacy coin that was one of the first, if not the first, to use zk-SNARKs. It enables anonymous transactions by obfuscating both the sender and the receiver, and even the amount that is exchanged between the two.
- Findora - Findora is a privacy-based blockchain with programmable zkDapps and customizable subnets. These subnets allow fine-grained data visibility control across different apps.
What is the role of AI agents in automating privacy policies?
Another factor impacting programmable privacy is AI Agents. Thanks to AI Agents, users do not have to keep changing their privacy settings on different apps manually. Instead, they can teach AI their preferences, and have it apply them to all the different apps in real time. For example, an AI agent could decide which parts of the user’s health records to share with a doctor, but hide them from other parties, such as insurance companies. It can also change permissions for different entities to adjust them based on any given situation.
AI is also finding greater use in policy translation, making it understandable to a regular person by simplifying the language and removing the legal jargon. This has been one of the largest problems that users have had with privacy policies in any sector, where the language used is purposefully complex and difficult, which sometimes allows companies to get users to agree to things that are not in their interest, such as allowing them to use and share user data in any way they see fit.
AI agents can read the documents, extract key details from them, simplify the language, and explain to the user what exactly they are asked to agree to. More than that, they can apply the instructions that users have entered through User Control, and compare the two to decide whether the policies’ requests are in compliance with privacy settings that the user has selected.
Conclusion
Advanced technologies such as blockchain and AI have enabled programmable privacy, which represents the next step in data privacy evolution. Programmable privacy can now change how users, as well as companies, interact with sensitive data. As such, it can empower the user, whether it is an individual or an enterprise, and offer selective transparency, smart consent management, and automated compliance.
For the everyday user, this means a greater peace of mind, as they will know that their sensitive information is protected. As for organizations, they can meet regulatory requirements easily, without sacrificing functionality and resources.
As the adoption of programmable privacy grows, even the internet itself can evolve into a safer space by reducing issues like data breaches and exposure of sensitive information.
