aiengineering

AI system trustworthiness is dependent on end users’ confidence in the system’s ability to augment their needs. This confidence is gained through evidence of the system’s capabilities. Trustworthy systems are designed with an understanding of the context of use and careful attention to end-user needs. In this webcast, SEI researchers discuss how to evaluate trustworthiness of AI systems given their dynamic nature and the challenges of managing ongoing responsibility for maintaining trustworthiness.

What attendees will learn:

• Basic understanding of what makes AI systems trustworthy
• How to evaluate system outputs and confidence
• How to evaluate trustworthiness to end users (and affected people/communities)

As Artificial Intelligence permeates mission-critical capabilities, it is paramount to design modular solutions to ensure rapid evolution and interoperability. During this webcast, we’ll discuss some of the primary quality attributes guiding such design, and how a Next Generation Architecture can facilitate an integrated future state.

What attendees will learn:

• current challenges facing AI engineering
• approaches to promoting interoperability across AI solutions
• considerations for facilitating modularity and reuse in design

In this webcast,  Carol Smith, Carrie Gardner, and Michael Mattarock discuss maturing artificial intelligence (AI) practices based on our current body of knowledge. Much as it did for software engineering in the 1980s, the SEI has begun formalizing the field of AI engineering, beginning with identifying three fundamental pillars to guide AI engineering: human-centered, scalable, and robust and secure. Watch to learn more about these pillars and how they can be used to help national defense and security agencies adopt and develop AI.

In its 2021 report, the National Security Commission on AI (NSCAI) wrote, "The impact of artificial intelligence (AI) on the world will extend far beyond narrow national security applications." How do we move beyond those narrow AI applications to gain strategic advantage? Join Dr. Matt Gaston, Director of the SEI AI Division, Dr. Steve Chien, NSCAI Commissioner and Technical Group Supervisor of the Artificial Intelligence Group and Senior Research Scientist in the Mission Planning and Execution Section at the Jet Propulsion Laboratory, California Institute of Technology, and Dr. Jane Pinelis, Chief of Test and Evaluation of AI/ML at the DoD Joint AI Center (JAIC) for a discussion on scaling AI. Carnegie Mellon University is proud to partner with NSCAI in this discussion, part of an ongoing series of virtual panel discussions to realize the future of AI.

What attendees will learn:
• NSCAI recommendations for scaling AI
• How AI Engineering can scale the impact of mission capabilities
• Where to find leading AI Engineering practices
• Challenges and opportunities for the future of AI