Research Summary
The report explores the intersection of cryptocurrency and artificial intelligence (AI), two significant software technology trends. It discusses the potential and challenges of merging these technologies, focusing on areas such as AI as a player, an interface, the rules, and the objective of a game in the crypto space. The report also delves into the computational and security implications of integrating AI into blockchain and smart contracts.
Key Takeaways
AI and Crypto: A Promising Intersection
- AI as a Player: The report identifies AI as a player in blockchain-based games as the most viable application. AI arbitrage bots, which are more efficient than humans, have been a longstanding example of AI in the crypto space. The AI as a player category is likely to expand beyond arbitrage bots to include a broader range of blockchain applications involving auctions and trading.
- AI as an Interface: AI can enhance user understanding of dapp participation and transaction consequences, acting as a real-time tutor and protector against mistakes in the cryptocurrency space. However, pure AI interfaces in wallets are considered risky due to the potential for errors and adversarial machine learning.
- AI as the Rules: The concept of AI as part of the rules of the game, such as AI judges or decision-makers in smart contracts or DAOs, is seen as risky due to adversarial machine learning challenges. Cryptographic solutions like zero-knowledge proofs are considered for protecting AI models, but face challenges such as computational overhead and vulnerability to black-box adversarial attacks.
- AI as the Objective: The report discusses the potential for blockchain-based AI systems with current centralized AI judges, which already influence social media content visibility and political opinions. It suggests that blockchain experimentation with AI might not exacerbate the current situation and could offer improvements.
- Challenges in Merging AI and Crypto: The report acknowledges the challenges in merging open-source cryptography with AI, where the openness can increase susceptibility to adversarial machine learning attacks. It suggests that the integration of AI into blockchain and smart contracts must be approached with caution, considering both computational and security implications.
Actionable Insights
- Explore the Potential of AI as a Player: Given the viability of AI as a player in blockchain-based games, there is potential to explore this area further. This could include developing more advanced AI bots for a broader range of blockchain applications involving auctions and trading.
- Improve AI as an Interface: While AI can enhance user understanding of dapp participation and transaction consequences, there are risks associated with pure AI interfaces. Efforts should be made to improve the security and reliability of AI interfaces to mitigate these risks.
- Consider Cryptographic Solutions for AI Protection: With the risks associated with AI as part of the rules of the game, it may be beneficial to consider cryptographic solutions like zero-knowledge proofs for protecting AI models. However, the challenges associated with these solutions, such as computational overhead and vulnerability to black-box adversarial attacks, should be taken into account.
- Experiment with Blockchain-Based AI Systems: The report suggests that blockchain experimentation with AI might not exacerbate the current situation and could offer improvements. Therefore, it could be beneficial to experiment with blockchain-based AI systems, while being mindful of the potential risks and challenges.
- Approach AI and Crypto Integration with Caution: Given the challenges in merging open-source cryptography with AI, it is crucial to approach the integration of AI into blockchain and smart contracts with caution. This includes considering both computational and security implications.
