Erica Briscoe

Erica Briscoe joined ARLIS following her position as the Senior Vice President for Strategy and Delivery at Calypso AI, a software start-up company focused on trusted AI. Prior to her role at Calypso, she spent 12 years at the Georgia Tech Research Institute, where she last served as the Interim Chief Technology Officer, managing a 14 million-dollar internal research and development (IRAD) portfolio, several staff, and serving on the executive council of GTRI. Additionally at Georgia Tech, she was Chief Scientist of the autonomy, transportation, and threat systems lab, managing a portfolio of IRAD programs in areas including robotics and autonomous systems, high-tech agriculture, and aerospace engineering. She also held a joint appointment in the Sam Nunn School on International Affairs.

Dr. Briscoe has managed technical research portfolios, with teams and conducting research in a number of data-driven domains, including computational social science, technology emergence and prediction, multi-modal reasoning, anticipatory intelligence, insider threat detection, terrorism/radicalization, and trusted AI. Her work has been funded by DARPA, CDC, ASD R&E, DHS, DTRA, DoJ, Carnegie, and NSF.

As of September 2022, Dr. Briscoe is on an Intergovernmental Personnel Act (IPA) assignment to the Defense Advanced Research Projects Agency.

EDUCATION:

PhD in Cognitive Psychology, Rutgers University

MS in Cognitive Psychology, Rutgers University

MS in Information Systems, Drexel University

MS in Industrial Engineering, Georgia Tech

MISSION AREA:

Applied AI for Performance

Cognitive Security

Language & Culture

Papers

Briscoe, E. & Fairbanks, J. (2020). Artificial Scientific Intelligence and Its Impact on National Security and Foreign Policy. Orbis, 64(4).

Briscoe, E. (2017). “Big Data: Exposing the Risks from Within,” Big Data: 21st Century Arms Race. Atlantic Council

Briscoe, E., Appling, S., and Schlosser, J. (2016). “Passive Crowd Sourcing for Technology Prediction,” IEEE Transactions on Computational Social Systems, 3(1), 23-31.

Appling, D., Briscoe, E. and Hutto, C. (2015). “Discriminative Models for Predicting Deception Strategies,” Proceedings of WWW Conference Workshop. Rumors and Deception in Social Media: Detection, Tracking, and Visualization. May 15-20, Florence, Italy.

Briscoe, E., Appling, D., Mappus IV, R., and Hayes, H. (2013). “Determining credibility from social network structure,” In Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (pp. 1418-1424). ACM.

Mappus, C. and Briscoe, E. (2013). “Layered behavioral trace modeling for threat detection,” Proceedings of the 2013 IEEE Intelligence and Security Informatics Conference. Seattle, Washington.

Briscoe, E. and Feldman, J. (2011). “Conceptual complexity and the bias/variance tradeoff,” Cognition, 118, 2–16.

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