Blockchain and AI: synergy or conflict?
Artificial Intelligence especially when powered by Large Language Models (ChatGPT) analyzes data for decision-making and forming assumptions. When we think of AI, we often associate it with math and statistics.
On the other hand, there’s Blockchain, a decentralized and transparent database, that is typically associated with security and cryptographic elements.
The relationship between Blockchain and AI is somewhat contradictory:
- Centralization vs decentralization — AI is often associated with centralized models, both in terms of data storage and decision-making within technology development. On the other hand, Blockchain has been designed with decentralization in mind, with it’s open-source code and active community, usually taking part in the governance.
- Corporations vs Rebels/Early adopters — When it comes to the groups creating projects, the largest artificial intelligence models are often developed by well-known global corporations, while the early blockchain projects were created by rebels — geeks (Cypherpunks) seeking alternatives to existing financial systems.
- Lack of transparency vs Transparency & Open source — LLMs are trained on massive amounts of data provided by users, who are often not only unaware of providing these data but also don’t know how the data was utilized. Obviously, it’s done intentionally and there is even a positive motivation behind it: if models and the data they are fed are made public, there is a chance that someone could plan an attack on the network. On the other hand, blockchain, with its open source code, gives users transparency and control over their data, challenging the community to attempt an attack on the network, thereby enhancing its resistance in the future.
However, digging deeper it looks like these technologies complement each other. What kind of magic happens when these two join forces?
Let’s start with an AI angle: How can Blockchain help Artificial Intelligence?
- Transparency and Data Credibility — The current challenge in machine learning models is the lack of transparency in their decision-making processes. Using blockchain as a transparent data registry reveals the data on which models rely for training and decision-making.
- Authentication — The use of blockchain can help confirm the authenticity of images, video files, text documents, or other types of media, which is especially important in the era of deepfakes.
- Cryptocurrencies as AI Currency — The payment system that AI would use must be accessible, digital, and automated…sounds familiar, right? Crypto can also be used to create incentive models, as a reward for users who participate in training models. Companies can pay users to share their data.
Also, some technologies, such as Zero-Knowledge Solutions, are being used by both technologies. As the blockchain community actively works on ZKs (as mentioned it in the Scalability piece), the technology evolves, influencing AI.
Now let’s look at the topic from a different angle - How can AI help Blockchain?
- Smart Contract Analysis — By leveraging AI, users can analyze complex smart contracts and identify real-time risks. AI can guide us, highlight potential vulnerabilities, provide suggestions, and even facilitate the creation of new smart contracts.
- Process Optimization — Data analysis and machine learning algorithms can improve the efficiency of the entire blockchain system i.e. concensus mechanisms.
- Predictions and Arbitrage — AI can easily analyze historical price data, news, social media, and other sources to assess market sentiment and make predictions or forecast price movements. It can also help develop more efficient bots for arbitrage strategies.
- On-chain Data Analysis — AI can effectively analyze data stored on-chain, enabling the identification of patterns and providing information about network participants. It can increase network security by higlighting illicit transactions or suspicious behavior patterns.
- Automation (Chatbots) — AI-powered chatbots can support automation on cryptocurrency platforms. They can handle user queries, guide users, or provide information about market trends. Future AI-boosted DeFis can react to users’ commands, facilitating on-chain interaction such as ‘Hey chat, execute a transaction on Uniswap based on a market price,’ ‘buy me the cheapest NFT from the latest collections on Blur,’ or ‘Is this address 0x… legit? Is it safe to interact with it?’
The list is not exhaustive, and we could come up with many more examples, but I hope it provides you with enough understanding of the topic. If you are looking for a more technical piece, go to Vitalik’s latest blog post.
