Kathleen Fisher: DARPA and AI for National Security

Kathleen Fisher: DARPA and AI for National Security

Author: Daniel Bashir December 21, 2023 Duration: 46:16

In episode 103 of The Gradient Podcast, Daniel Bashir speaks to Dr. Kathleen Fisher.

As the director of DARPA’s Information Innovation Office (I2O), Dr. Kathleen Fisher oversees a portfolio that includes most of the agency’s AI-related research and development efforts, including the recent AI Forward initiative. AI Forward explores new directions for AI research that will result in trustworthy systems for national security missions. This summer, roughly 200 participants from the commercial sector, academia, and the U.S. government attended workshops that generated ideas to inform DARPA’s next phase of AI exploratory projects. Dr. Fisher previously served as a program manager in I2O from 2011 to 2014. As a program manager, she conceptualized, created, and executed programs in high-assurance computing and machine learning, including Probabilistic Programming for Advancing Machine Learning (PPAML), making building ML applications easier. She was also a co-author of a recent paper about the threats posed by large language models.

Since 2018, DARPA has dedicated over $2 billion in R&D funding to AI research. The agency DARPA has been generating groundbreaking research and development for 65 years – leading to game-changing military capabilities and icons of modern society, such as initiating the research field that rendered self-driving cars and developing the technology that led to Apple’s Siri.

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Outline:

* (00:00) Intro

* (01:30) Kathleen’s background

* (05:05) Intersections between programming languages and AI

* (07:15) Neuro-symbolic AI, trade-offs between flexibility and guarantees

* (09:45) History of DARPA and the Information Innovation Office (I2O)

* (13:55) DARPA’s perspective on research

* (17:10) Galvanizing a research community

* (20:06) DARPA’s recent investments in AI and AI Forward

* (26:35) Dual-use nature of generative AI, identifying and mitigating security risks, Kathleen’s perspective on short-term and long-term risk (note: the “Gradient podcast” Kathleen mentions is from Last Week in AI)

* (30:10) Concerns about deployment and interaction

* (32:20) Outcomes from AI Forward workshops and themes

* (36:10) Incentives in building and using AI technologies, friction

* (38:40) Interactions between DARPA and other government agencies

* (40:09) Future research directions

* (44:04) Ways to stay up to date on DARPA’s work

* (45:40) Outro

Links:

* DARPA I2O website

* Probabilistic Programming for Advancing Machine Learning (PPAML) (Archived)

* Assured Neuro Symbolic Learning and Reasoning (ANSR)

* AI Cyber Challenge

* AI Forward

* Identifying and Mitigating the Security Risks of Generative AI Paper

* FoundSci Solicitation

* FACT Solicitation

* Semantic Forensics (SemaFor)

* GARD Open Source Resources

* I2O Newsletter signup



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Hosted by Daniel Bashir, The Gradient: Perspectives on AI moves beyond surface-level headlines to explore the intricate machinery and human ideas shaping artificial intelligence. Each episode is built on a foundation of deep research, leading to conversations that are both technically substantive and broadly accessible. You'll hear from researchers, engineers, and philosophers who are actively building and critiquing our technological future, discussing not just how AI systems work, but the larger implications of their integration into society. This isn't about speculative hype; it's a grounded examination of real progress, persistent challenges, and ethical considerations from those on the front lines. The discussions peel back layers on topics like model architecture, policy, and the fundamental science behind the algorithms becoming part of our daily lives. For anyone curious about the substance behind the buzz-whether you have a technical background or are simply keen to understand a defining technology of our age-this podcast offers a crucial and thoughtful resource. Tune in for a consistently detailed and nuanced take that treats artificial intelligence with the complexity it deserves.
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