Season 6, Episode 20: Unveiling the Future of Data Integrity: Exploring the Data Provenance Standards (with Kassi Burns and Olga V. Mack)
Dec 30, 2023
auto_awesome
Attorney Kassi Burns, with 10 years of experience in AI and Machine Learning, discusses the Data Provenance Standards initiative by the Data & Trust Alliance. Learn how these standards promise transparency in data's journey from source to application and their potential to revolutionize sectors like healthcare and finance. Uncover challenges and benefits of standardizing metadata for data sets and explore future trends in data governance.
Data provenance standards promise greater transparency in data's journey from source to application, addressing AI adoption challenges.
Data provenance standards have the potential to revolutionize sectors from healthcare to finance, ensuring data integrity and fostering trust in AI systems.
Deep dives
Importance of Data Provenance and Standards
In this episode, the hosts emphasize the significance of data provenance and the need for standards in the AI and data industry. They discuss how data sets used to train AI models should have clear metadata that establishes the origin, legal rights, privacy, and data lineage. This ensures transparency and helps address compliance and regulatory requirements. They highlight that data provenance is crucial for risk assessment, trust-building, and the ethical use of data. The hosts also mention the emerging trend of data supply chain, which parallels the importance of sustainability in consumer goods. They predict that in the next five years, there will be an expectation for AI models to use data sets with established provenance, and non-compliant models may be considered subpar or untrustworthy.
Challenges and Opportunities for Small Businesses
The podcast explores the potential impact of data provenance standards on small businesses. While standards can enhance transparency and trust, there may be challenges for small companies in terms of the cost of developing AI models using data sets with provenance. The hosts discuss the possibility of a premium on data sets with provenance established, which could pose financial challenges for small businesses. They also speculate on the implications of legal issues related to using data, and the potential barrier to entry for startups due to increased compliance requirements. However, they remain cautiously optimistic, pointing to potential government grants and the democratization of tools that could level the playing field for small and medium-sized businesses.
Preparing for Data Governance Trends
The hosts provide practical advice for professionals to prepare for upcoming data governance trends and the adoption of data provenance standards. They suggest getting familiar with the concept of data provenance and understanding the importance of metadata in data sets. They recommend exploring resources by organizations like the Data Trusts Group and NIST for valuable information on data standards and use cases. Additionally, they highlight the need to stay updated on AI regulations and compliance requirements related to data. They encourage individuals to engage with vendors, who can provide valuable education and insights into data management and governance. Finally, they emphasize the importance of continuously educating oneself and being proactive in understanding data fluency.
The Future of Data Governance and Standards
The hosts speculate on the future of data governance and standards, particularly in the context of AI. They predict that within five years, there will be an expectation for AI models to use data sets with provenance attached to ensure trust and compliance. They discuss the potential impact on AI models without provenance, which may be considered subpar or untrustworthy. They also highlight the importance of data transparency, traceability, and control in the context of AI and individual rights. They suggest that in the future, data standardization and understanding one's data supply chain will be essential for innovation, opportunities, and the autonomous extension of self. They also anticipate the rise of small to medium-sized businesses leveraging sophisticated data tools and creating a renaissance in the industry.
Welcome to "Notes to My Legal Self," a podcast where we dive deep into the intersection of law and technology. In this episode, we're exploring the intricate world of Data Provenance Standards with two seasoned experts in the field, Olga Mack and Kassi Burns. Get ready for a geeky yet enlightening conversation about data, AI, legal technology, and much more!
Key Takeaways:
Insight into Data Provenance Standards by the Data & Trust Alliance.
How these standards, akin to food safety labels, enhance transparency and trust in data usage.
The impact of data integrity standards on various sectors, including healthcare and finance.
Exploring the intersection of AI, legal tech, and data governance.
Guest Information:
Kassi Burns is a forward-thinking attorney with a decade of experience in AI and Machine Learning.
Olga Mack is a legal tech enthusiast and expert in disruptive tech and the future of law.
Special Features:
Engaging in rapid-fire Q&A sessions with the guests.
Discussion on practical solutions over legal philosophy.
Insights into the future of legal education and the impact of AI on small businesses.
Teaser Questions:
How can Data Provenance Standards revolutionize trust in AI systems?
What are the implications of these standards on your career in the legal tech industry?
Can small businesses leverage these standards for growth and opportunity?
"Stay ahead of the curve in the evolving world of legal technology. Follow us for more insightful episodes and join the conversation by sharing your thoughts on how data provenance is shaping the future of AI and legal tech."
Remember Everything You Learn from Podcasts
Save insights instantly, chat with episodes, and build lasting knowledge - all powered by AI.
