Strong data governance is crucial for effective AI governance. Transparency in data usage is key for building trust and credibility within organizations. However, incomplete or unclear metadata can hinder this transparency. To address this issue, IBM collaborated with the Data and Trust Alliance and other companies to develop cross-industry data provenance standards. By testing these standards, IBM observed improvements in data authorization review time and data quality. As a result, IBM is aligning its internal data standards with the Data Provenance Standards to efficiently handle data authorization requests while upholding responsible data practices. Trustworthy AI requires clarity, transparency, and ethics throughout the AI lifecycle. IBM’s Granite Foundation Models prioritize transparency through adherence to data governance and risk criteria. The new data provenance standards aim to enhance transparency about data origin and promote the development of responsible AI in various industries. IBM encourages the adoption of these standards and offers support to customers in implementing robust data governance frameworks.
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https://www.ibm.com/blog/how-ibm-and-the-data-trust-alliance-are-fostering-greater-transparency-across-the-data-ecosystem/
