Observed Signal · Jul 9, 2024 · Policy Update · Source: CMSWire · Impact: 3/5 · Sentiment: Positive
Data & Trust Alliance Releases Version 1.0 Data Provenance Standards
The Data & Trust Alliance (D&TA) released version 1.0.0 of its Data Provenance Standards, following testing and validation with more than 50 organizations including IBM, Walmart, and Pfizer. Originally proposed in November 2023, the finalized standards comprise 22 metadata fields grouped into three categories: Source, Provenance, and Use. The metadata is designed to travel with datasets as they are shared and transformed, bringing transparency to the origins and usage of data powering AI applications. An IBM survey cited in the article found 61% of CEOs consider lack of clarity on data lineage and provenance a top barrier to generative AI adoption. Built by a working group of chief data officers and data strategy leaders across more than 15 industries, the standards aim to help practitioners make informed decisions about data suitability. For CX and marketing leaders, the standards increase transparency into how customer data is collected and used, highlighting risks such as lookalike or generative synthetic data skewing targeting strategies or collapsing AI models.
Industry-led data provenance standards bring transparency to AI training data and customer data acquisition, directly affecting how marketers and AdTech practitioners evaluate data quality, lineage, and risk. Validated by major enterprises including IBM and Walmart, the standards could see broad adoption across the data supply chain, reducing legal and reputational risks associated with opaque or synthetic datasets.
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Key Takeaways & Evidence Grounding
- Data & Trust Alliance released version 1.0.0 of its Data Provenance Standards on July 9, 2024.
- The standards contain 22 metadata fields grouped into three standards: Source, Provenance, and Use.
- The standards were tested and validated with more than 50 organizations, including IBM, Walmart, and Pfizer.
- An IBM survey found that 61% of CEOs cite lack of clarity on data lineage and provenance as a top barrier to generative AI adoption.
- IBM tested the standards in its clearance process for datasets used to train foundational AI models, reporting increased efficiency and data quality.
Connected Companies & Entities
12 Entities mapped“IBM tested the standards as part of their clearance process for datasets used to train foundational AI models; Rob Thomas is SVP, software a...”
“The standards were tested and validated with more than 50 organizations including IBM, Walmart, Pfizer and others....”
“The standards were tested and validated with more than 50 organizations including IBM, Walmart, Pfizer and others....”
“Christine Pierce, chief data officer, audience measurement at Nielsen, said the standards promote trust and transparency by surfacing critic...”
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“Listed as an Alliance company involved in building the D&TA Standards....”
“Listed as an Alliance company involved in building the D&TA Standards....”
“Listed as an Alliance company involved in building the D&TA Standards....”
“Listed as an Alliance company involved in building the D&TA Standards....”
“Listed as an Alliance company involved in building the D&TA Standards....”
Ontology Mapping & Concepts
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