Quantifind Project with the Department of Defense and Defense Innovation Unit Serves as Case Study in New “Responsible AI Guidelines in Practice” Report

Quantifind, a provider of a software-as-a-service (SaaS) platform that provides entity risk intelligence and tools used to discover financial crimes and the networks behind them, has had a joint project included as an exemplary case study in an authoritative report detailing guidelines for operationalizing Responsible AI. The project—conducted by the Department of Defense (DoD), the Defense Innovation Unit (DIU), and Quantifind—supports DoD analysts in countering foreign malign influence with entity risk analytics derived from publicly available and commercially available information.

The “Responsible AI Guidelines in Practice” report was written by DIU to provide a process of inquiry to be applied as part of the AI system development process towards integrating the DoD’s Ethical Principles for AI into the DIU’s commercial prototyping and acquisition programs. The report captures best practices from government and non-government partners to provide actionable guidelines for implementing responsible AI practices at each phase of software development.

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“DIU’s RAI Guidelines provide a step-by-step framework for AI companies, DoD stakeholders, and program managers that can help to ensure that AI programs align with the DoD’s Ethical Principles for AI and that fairness, accountability, and transparency are considered at each step in the development cycle of an AI system,” said Dr. Jared Dunnmon, technical director of the AI/ML portfolio at DIU.

“Users want to know that they can trust and verify that their tools protect American interests without compromising our collective values,” said Quantifind Co-Founder John Stockton. “These guidelines show promise for actually accelerating technology adoption, as it helps identify and get ahead of potentially show-stopping issues. We’ve found that leaning into this effort has also served us well outside of government, by strengthening internal controls and producing transparency and patterns of trust that can also be leveraged with all users, both public and private.”

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