**Summary: **
The Community Call focused on the implications of AI, particularly around privacy concerns in the age of AI.
Participants:
-
Sudo & Jaya from NYM)
-
Dr. Nick Almond from FactoryDAO Labs
Key Points:
-
Generative AI & Privacy: Generative AI, particularly LLMs, are trained on vast datasets, raising significant privacy concerns. These models could potentially use personal data, leading to privacy invasions.
-
Surveillance and AI: The development of AI is deeply intertwined with surveillance practices, especially in the corporate sector, where data collection is often invasive.
-
The Role of DAOs: DAOs can play a pivotal role in ensuring that AI technologies are developed and governed in a way that respects privacy and decentralization. The conversation touched on the need for decentralized control over AI systems to prevent the monopolization of truth and knowledge by centralized entities.
-
Digital Identity vs. Credentials: The discussion highlighted the dangers of digital IDs and the importance of using privacy-preserving credentials to access services without exposing personal data.
Q&A:
Q1: Is there a unique threat of generative AI when it comes to individual privacy?
- A: Yes, generative AI presents a unique threat as it requires vast amounts of data, often personal, to function effectively. The move towards personalized AI models could lead to increased corporate surveillance, making privacy technologies more important than ever.
Q2: What can be done to prevent misinformation from AI-generated content?
- A: Developing better social consensus mechanisms and improving the curation of data used to train AI models are essential. Smaller, well-curated data sets could help mitigate the spread of misinformation.
Q3: Do you believe any third party with whom data is shared meets strict privacy and security standards?
- A: Generally, no. Data breaches are common, and relying on third parties for data security is risky. Instead, privacy needs to be built into the infrastructure by design.
Q4: In terms of data protection, which country has appropriate laws that can serve as an example for other territories?
- A: The GDPR in the EU is considered the gold standard, though its enforcement and the need for technological innovation alongside regulation are crucial.
Conclusion:
A consensus on the critical need for decentralized technologies to counterbalance the privacy risks posed by AI. The importance of building and adopting privacy-preserving technologies and governance models, such as those offered by NYM and FactoryDAO, to ensure that the future of AI development remains in the hands of communities rather than centralized corporations.