KPMG Awarded U.S. Patent For Blockchain Application That Increases Trust In AI Data Management Practices
KPMG’s new patent – U.S. Patent No. 10,528,890 – demonstrates how blockchain can be used to store, track and trace data used throughout the AI lifecycle, including training, deployment and monitoring of AI models and their algorithms. It also establishes an AI chain of custody that verifies how and where data and models have been generated and used.
“Using blockchain allows both KPMG and our clients to confidently stand behind the responsible use of data entrusted to us,” said Marisa Boston, KPMG director and patent co-inventor with KPMG Director Rupa Shah. “With this approach, we are able to help companies manage data, identify and mitigate issues such as bias or unnecessary access that could compromise data integrity, and drive increased confidence in insights driven by AI.”
Organizations across the public and private sectors recognize the potential for data-driven business models to accelerate competitive advantage. However, current compliance regulations require data to be carefully monitored for rightful use. Additionally, in order for machine learning models to become more accurate and effective when reflecting human intelligence and reasoning, they need to be fueled with improved data quality and data security.
KPMG’s method improves shortcomings in current data management approaches, and can help organizations operationalize a trust paradigm within the AI lifecycle by using blockchain to manage data provenance and lineage, and support integrity in models and algorithms. It allows them to responsibly identify the most relevant available data; record how multiple parties interact with the data; manage data permissions and approvals for use in AI algorithms; identify when potential bias has been introduced through the training data; monitor training data history and quality; and track how and where the models have been deployed and utilized.
Key components of the data management process are automated using smart contracts to enhance the existing human procedures required to maintain data records and controls across large organizations. Outputs and insights gleaned by AI are explainable and auditable, allowing for increased confidence in results among stakeholders.
The trust and transparency enabled by end-to-end data provenance allows AI to serve as a reliable technology that business leaders can leverage as part of their broader digital transformation efforts. Beyond helping clients with data management, KPMG plans to use this new technology in its own data strategy and digital transformation efforts.
“Technology is both the impetus for and solution to many of today’s most complex business problems. However, it’s critical that new innovations be developed and deployed responsibly,” said Mike Nolan, KPMG Vice Chair, Innovation & Enterprise Solutions. “This blockchain method demonstrates how KPMG is focused both on uncovering the full potential of converging emerging technologies such as AI and blockchain, and on their responsible implementation.”
The patent is one component of KPMG’s intellectual property portfolio, which includes strategic investments in emerging technologies and partnerships with leading technology companies, to develop and deploy technology-based solutions that address complex business challenges.
About KPMG LLP
KPMG is one of the world’s leading professional services firms, providing innovative business solutions and audit, tax, and advisory services to many of the world’s largest and most prestigious organizations.
KPMG is widely recognized for being a great place to work and build a career. Our people share a sense of purpose in the work we do, and a strong commitment to community service, inclusion and diversity, and eradicating childhood illiteracy.
KPMG LLP is the independent U.S. member firm of KPMG International Cooperative (“KPMG International”). KPMG International’s independent member firms have 207,000 professionals working in 153 countries and territories. Learn more at www.kpmg.com/us.
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