Karen O’Brien is a senior principal data scientist and AI/ML practice lead at Modern Technology Solutions, Inc. In this capacity, she leverages her 20-year Army civilian career as a scientist, evaluator, ORSA, and analytics leader to aid DoD agencies in implementing AI/ML and advanced analytics solutions. Her analytics career ranged ‘from ballistics to logistics’ and most of her career was in Army Test and Evaluation Command or supporting Army T&E from the Army Research Laboratory. She was physics and chemistry nerd in her early career, but now uses her M.S. in Predictive Analytics from Northwestern University to help her DoD clients tackle the toughest analytics challenges in support of the nation’s Warfighters.
The topic of synthetic data in test and evaluation is steeped in controversy - and rightfully so. Generative AI techniques can be erratic, producing non-credible results that should give evaluators pause. At the same time, there are mission domains that are difficult to test, and these rely on modeling and simulation to generate insights for evaluation. High fidelity modeling and simulation can be slow, computationally intensive, and burdened by large volumes of data - challenges which become prohibitive as test complexity grows.
To mitigate these challenges, we posit a defensible, physically valid generative AI approach to creating fast-running synthetic data for M&S studies of hard-to-test scenarios. Characterized as a “Narrow Digital Twin,” we create an exemplar Generative AI model of high-fidelity Hypersonic Glide Vehicle trajectories. The model produces a set of trajectories that meets user-specified criteria (particularly as directed by a Design of Experiments) and that can be validated against the equations of motion that govern these trajectories. This presentation will identify the characteristics of the model that make it suitable for generating synthetic data and propose easy-to-measure acceptability criteria. We hope to advance a conversation about appropriate and rigorous uses of synthetic data within T&E.
Session Materials: dataworks.testscience.org/wp-...
21 май 2024
