Michael Schmid (amazee.io): Where’s My Data Traveling When Using AI 

This talk was presented at the AI The Docs online conference on April 4, 2024. We are thrilled to share the recording and the summary with you.

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Michael Schmid

Co-founder and CEO at amazee.io

Michael's presentation

In this presentation, Michael explores data privacy and its implications in the context of AI and large language models (LLMs). He highlights key concerns and strategies for managing data sovereignty and protection.

Key Takeaways

Understanding Data Privacy with AI

• Risks and Concerns: Michael addresses the concerns around data handling in AI systems, emphasizing the need for robust data protection strategies.

Data Sovereignty

• Definition: Data sovereignty involves storing and handling data in encrypted formats and specific approved locations to comply with varying data protection laws.
• Personal Data Management: It’s crucial to ensure that sensitive information is handled securely and only by necessary parties.

Challenges in Compliance

• Regulatory Landscape: Different regions have varying data protection regulations (e.g., GDPR, CCPA, PIPEDA, LGPD). Compliance can be complex due to these diverse requirements.
• AI and Unstructured Data: Unlike traditional data forms, chatbots and LLMs often handle unstructured and sensitive data, complicating compliance efforts.

Data Privacy Policies and Practices

• Privacy Policies: Companies like OpenAI claim GDPR compliance but may have policies allowing data sharing with vendors and governments, which complicates understanding of data usage and protection.
• Global Data Processing: OpenAI’s privacy policy suggests data could be processed or disclosed across various jurisdictions, highlighting the importance of understanding these practices.

Future Considerations

• Managing Data: Emphasizes the need for ongoing vigilance in data management practices to ensure compliance and protection.
• Transparency: Advocates for transparency regarding data handling and changes in policies, such as in cases of company acquisitions.

Strategies for Addressing Data Privacy

• Open Source Solutions: Michael suggests that open source tools and practices can provide solutions to some data privacy challenges.
• Proactive Management: Companies should proactively manage and secure data, ensure compliance with regulations, and remain transparent about data practices.

Conclusion
Michael underscores the importance of understanding data privacy concerns, implementing robust data management practices, and leveraging open source solutions to address these challenges effectively.