This text discusses the importance of trust in AI and how cryptography can help address trust-related concerns. The author highlights four main challenges in trusting AI, including its use for harmful purposes, the authenticity of AI-generated content, the privacy of data and queries, and the manipulation of results by AI companies. While the first challenge requires regulation, the other three can be addressed through technology, specifically cryptography. The author explains how cryptographic signatures can help verify the authenticity of online content and emphasizes the significance of digital identities and verified social media accounts. Additionally, the use of homomorphic encryption enables users to keep their data private while using AI services. Lastly, zero-knowledge proofs are introduced as a solution to ensure that AI results are not manipulated, providing a way for users to verify the authenticity of the response. The text concludes by advocating for the use of cryptography to enhance trust in AI.
| Signal | Change | 10y horizon | Driving force |
|---|---|---|---|
| Making AI safer with cryptography | Trust in AI | AI content and data privacy | Ensuring trust and preventing manipulation |
| Trusting the content we see is real | Authenticity of online content | Content signed with cryptographic keys | Ensuring credibility and reducing risks |
| Trusting that our data remains private | Data privacy | Fully Homomorphic Encryption | Protecting user data |
| Trusting that AI companies don’t manipulate results | Transparency in AI services | Zero-Knowledge Proofs | Verifying integrity and preventing manipulation |