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When people talk about zero-knowledge cryptography in 2024, they’re often referring to a privacy-focused use case that relies on a combination of blockchain technology, cryptocurrencies, digital wallets, and users with some degree of web3 knowledge.
Zero-knowledge proofs have existed since the 1980s, long before the advent of web3. So why limit their potential to blockchain applications? Traditional companies can—and should—adopt ZK technology without fully embracing web3 infrastructure.
At a basic level, ZKPs unlock the ability to prove something is true without revealing the underlying data behind that statement. Ideally, a prover creates the proof, a verifier verifies it, and these two parties are completely isolated from each other in order to ensure fairness. That’s really it. There’s no reason this concept has to be trapped behind the learning curve of web3.
Most organizations that could benefit from ZK technology aren’t using blockchains or are not even aware of web3. The industry is still young, with many just now familiarizing themselves with Bitcoin (BTC) and Ethereum (ETH), not to mention Layer 2s and 3s.
Despite all that, ZKPs can already be applied to a variety of real-world use cases, and they don’t need to integrate fully web3 rails to do so.
Do you trust your slot machine payout?
With zero-knowledge proofs, you don’t have to trust a gaming operator. You can just enjoy playing and have peace of mind knowing that the game is designed fairly. Every digital gambling machine in the world should be designed with ZKPs; it just makes sense for the operators and the players. The best part is that players can enjoy the benefits without the words “web3” or “crypto” even entering their minds.
Recently, DraftKings and White Hat Gaming were fined $22,500 by the state of Connecticut for their online slot machine game, which failed to pay any winners over one week in August 2023—even though there were more than 20,600 spins that week. The game advertised that nearly 95 cents would be paid out for every $1 wagered, so the algorithm should have returned $19,570 to the players who wagered $20,600 in spins. Instead, players lost $20,600—all of which went to DraftKings.
This is where zero-knowledge proofs can make a big difference. A ZKP could prove that a game paid out a certain amount of money over a given period and at a specific hit rate without revealing individual spins or player identities.
This is great, but there is still the problem of verifying the proof. Someone needs to ensure that DraftKings, or any gaming operator, constructed the proofs correctly based on all the required data. It could be DraftKings themselves, but we shouldn’t trust them to handle their own verification. A regulator or auditor could do it, but this would likely cost DraftKings a lot of money, which would then be passed on to the customer.
In this situation, the best option is a public and decentralized network built specifically to verify proofs in a quick and cost-effective manner. Instead of the user being asked to trust a centralized entity, they can trust a decentralized protocol that ensures nefarious actors (i.e., those who may try to verify an incorrect proof) are punished if they misbehave.
AI output and trustworthiness
AI’s potential for deception is well-established. However, there are ways we can harness AI’s creativity while still trusting its output. As artificial intelligence pervades every aspect of our lives, it becomes increasingly important that we know the models training the AIs we rely on are legitimate because if they aren’t, we could literally be changing history and not even realize it. With ZKML, or zero-knowledge machine learning, we avoid those potential pitfalls, and the benefits can still be harnessed by web2 projects that have zero interest in going onchain.
Recently, the University of Southern California partnered with the Shoah Foundation to create something called IWitness, where users are able to speak or type directly to holograms of Holocaust survivors.
This is an undeniably powerful use of machine learning. There’s something so strangely moving about interacting with a hologram of a Holocaust survivor and feeling like you’re having a real conversation. But with a subject this sensitive, it’s even more crucial that the algorithm underlying the hologram is generating factual information.
Enter zero-knowledge proofs. If we were to reimagine this project, we might consider adding a “proof of algorithm output” where the user is able to see evidence that the responses they are seeing are based on a Natural Language Processing algorithm that was correctly trained on troves of historical transcripts and interviews with Holocaust survivors, ensuring that the information presented is accurate.
ZKPs make it possible to get proof of this input data and AI training without revealing the underlying information. Fact-checking the Holocaust information would also require perusing vast amounts of data, potentially requiring the end user to download or access large data sets and then spend hours reading or watching interviews. ZKPs allow the user to forgo this tedious and resource-intensive process.
In this case, we might trust USC to verify proofs for this particular project, but there are certainly more use cases with AI where the end user may not want to trust a centralized entity to both create and verify proof. When incentives to construct “fake” proofs and have them verified align, decentralized proof verification makes the most sense.
ZK is a trustless, decentralized system for all
We don’t need to trust companies or robots to tell us the truth because we have ZK. Many industries can level up with zero-knowledge blockchain solutions, even if they know nothing about the web3 space.
By tapping into ZK proof verification, companies and institutions can essentially keep doing everything they have been infrastructure-wise. They just need to create a simple system for proof creation and then use a decentralized system like zkVerify to handle the proof verification. Even though a blockchain is used, the users don’t need to worry about that.
The future of ZK will be massive, and organizations won’t have to change much to reap the benefits. They can just plug and play.
