What Military Leaders Need to Know about Artificial Intelligence

What Military Leaders Need to Know about Artificial Intelligence

Speakers: Carley, K. (Center for Computational Analysis of Social and Organizational Systems [CASOS] at Carnegie Mellon University); McCulloh, I. (Johns Hopkins University Applied Physics Laboratory)

Date: 2 August 2018

Speaker Session Preview

SMA hosted a speaker session presented by Dr. Ian McCulloh (Johns Hopkins Applied Physics Laboratory) and Dr. Kathleen Carley (Carnegie Mellon University) as a part of its SMA General Speaker Series. Dr. McCulloh and Dr. Carley discussed a multitude of key items that military leaders should be aware of in order to achieve national defense strategy objectives in artificial intelligence (AI) and machine learning (ML). Dr. McCulloh spoke about the monumental advancements that have been made over the past few decades in AI and ML and elaborated on a few challenges the DoD faces as this rapid technological advancement continues. He also discussed common measures of effectiveness in machine learning, quality and performance metrics involved in monitoring annotation efforts (annotators at Johns Hopkins University have been tasked with identifying items of importance for special operations), and the national defense implications of these topics. Dr. Carley then outlined the key problems associated with machine learning regarding feature set extraction, training set construction, generalized models and contextualized application, the assumption of stationarity, biases in data collection, and explanations to the public. She emphasized the importance of creating appropriate models and being cautious when selecting problems that we want ML to assist us with.

Speaker Session Audio File

Download Dr. Carley’s and Dr. McCulloh’s biographies and slides