Conference:  Transform X 2022

Authors: Dr. Jane Pinelis, Mark Valentine

2022-10-19

Dr. Jane Pinelis, the Chief of AI Assurance at the Chief Digital and Artificial Intelligence Office (CDAO), sits down with Scale's Head of Federal, Mark Valentine, to discuss the U.S. government’s efforts to develop explainable and ethical AI capabilities for national security. Dr. Pinelis recounts her journey to her current role, including the time she worked on Project Maven, which at the time was the Department of Defense’s most significant investment in AI, where she implemented a test and evaluation framework to evaluate vendor-submitted models. This work led to an AI assurance branch at the CDAO. Dr. Pinelas will discuss how the CDAO implemented AI principles of responsibility, equitability, traceability, reliability, and governability across the DoD and how it is working with international partners.Dr. Pinelis discusses the DoD’s plans for the next 12 months, including creating more best practices and tools to help implement advanced AI for different types of use cases including developers, senior leaders, and on the battlefield. Another focus is on the need to grow and nurture the existing AI workforce and build a strong base of responsible AI partners.Dr. Pinelis also discusses the launch of the Tradewind procurement ecosystem, allowing the DoD to accelerate the adoption of AI and machine learning by making it easier to work with academia, industry, and other groups.

Conference:  Transform X 2022

Authors: Dan Patt, Mark Valentine

2022-10-19

The future of economic growth is about information processing and a knowledge economy, with AI being a major player. The commercial sector has already realized the value of AI, but the public sector lags behind in operationalizing it.

• The economy has shifted towards a knowledge economy where information processing is key
• Consumer scale markets drive investment and innovation, leading to a virtuous cycle
• AI is a major player in the knowledge economy and has already been adopted by the commercial sector
• The public sector lags behind in operationalizing AI in their core processes