Here is the linked info https://www.linkedin.com/feed/update/urn%3Ali%3Aactivity%3A7366131817831194626/?midToken=AQHShn0lw49Icw&midSig=167iBkc5HRErU1&trk=eml-email_notification_single_mentioned_you_in_this_01-hero_notification_cta-0-1ep~cta&trkEmail=eml-email_notification_single_mentioned_you_in_this_01-hero_notification_cta-0-1ep~cta-null-e0odk~mesum33u~i8-null-null&eid=e0odk-mesum33u-i8
Event/Publication Name:
Open Source Initiative - Deep Dive: Data Governance
Event/Publication Date: October 1 - 3, 2025
Role: Presenting at VIRTUAL CONFERENCE (PRERECORDED PRESENTATION):
Topic: How Data Provenance Powers Trustworthy AI
"Today's AI models depend on an invisible supply chain: the data they're trained and fine-tuned on. But who's responsible for documenting, disclosing, and governing that lineage? Without standardized automated ways to capture and communicate data provenance, responsible AI and regulatory compliance remain wishful thinking and the risk of harm when using this data rises . This talk charts the journey from corporate innovation to open standard, specifically how the Data & Trust Alliance developed the first cross-industry data provenance specification, and how it's now being shepherded through the OASIS Open standards process to ensure open governance, interoperability, and adoption across sectors. We'll walk through:
● Why provenance is essential for trustworthy AI
● How governance, signaling, and stewardship intersect in real-world enterprise settings
● The role of open standards in translating principles into practice
● Lessons learned from cross-industry collaboration
● What's next: implementation guides, tools and enterprise adoption
This is a talk for practitioners, policy thinkers, and engineers who want more than frameworks, and are looking for tools, standards, and field-tested insights that can scale with the complexity of AI systems."
Lisa Bobbitt (lbobbitt)
Principal Engineer, Privacy
Cisco