AI Engineering Assets
• Collection
Publisher
Software Engineering Institute
Abstract
AI Engineering is an emergent discipline focused on developing tools, systems, and processes to enable the application of artificial intelligence in real-world contexts. This collection includes papers, videos, presentations, and other publications related to the SEI's AI Engineering work.
Collection Items
Deep System Instrumentation for In Situ Human-AI Interaction Measurement Within Complex Information Systems
• Conference Paper
By Joshua C. Poore (University of Maryland at College Park), Alex Veerasammy (University of Maryland at College Park), Amir Ghaemi (University of Maryland at College Park), Grant Tamrakar (University of Maryland at College Park), Kelsey Rassmann (University of Maryland at College Park), Craig Lawrence (University of Maryland at College Park)
This paper was presented at the 2022 AAAI Spring Symposium on AI Engineering.
Read
Building Coherent Use into the DevOps Lifecycle for High-Stakes AI
• Conference Paper
By Kelsey Rassmann (University of Maryland at College Park), Jana Schwartz (University of Maryland), Julie Marble (University of Maryland), William Regli (University of Maryland at College Park)
This paper was presented at the 2022 AAAI Spring Symposium on AI Engineering.
Read
Measuring Beyond Accuracy
• Conference Paper
By Violet Turri, Rachel Dzombak, Eric Heim, Nathan M. VanHoudnos, Jay Palat, Anusha Sinha
This paper was presented at the 2022 AAAI Spring Symposium on AI Engineering.
Read
Lessons Learned in Human-Artificial Intelligence Teaming in Business Processes
• Conference Paper
By Michael J. Mendenhall (Air Force Research Laboratory), Gilbert L. Peterson (Air Force Research Laboratory), Alexander Graves (Air Force Research Laboratory), Jonathan W. Butler (Air Force Research Laboratory)
This paper was presented at the 2022 AAAI Spring Symposium on AI Engineering.
Read
Exploring Opportunities in Usable Hazard Analysis Processes for AI Engineering
• Conference Paper
By Nikolas Martelaro (Carnegie Mellon University), Carol J. Smith, Tamara Zilovic (Carnegie Mellon University)
This paper was presented at the 2022 AAAI Spring Symposium on AI Engineering.
Read
Experience with Using Synthetic Training Images for Wearable Cognitive Assistance
• Conference Paper
By Roger Iyengar (Carnegie Mellon University), Emily Zhang (Carnegie Mellon University), Mahadev Satyanarayanan (Carnegie Mellon University)
This paper was presented at the 2022 AAAI Spring Symposium on AI Engineering.
Read
Adaptive Autonomy as a Means for Implementing Shared Ethics in Human-AI Teams
• Conference Paper
By Allyson I. Hauptman (Clemson University), Beau G. Schelble (Clemson University), Nathan J. McNeese (Clemson University)
This paper was presented at the 2022 AAAI Spring Symposium on AI Engineering.
Read
Kernel Density Decision Trees
• Conference Paper
By Jack H. Good (Carnegie Mellon University, Robotics Institute, Kyle Miller (Carnegie Mellon University, Robotics Institute), Artur Dubrawski (Carnegie Mellon University, Robotics Institute)
This paper was presented at the 2022 AAAI Spring Symposium on AI Engineering.
Read
Juneberry - Tutorial
• Presentation
By Andrew O. Mellinger, Nathan M. VanHoudnos, Nick Winski
Presented at Naval Applications of Machine Learning 2022, this tutorial reviews Juneberry, a reproducible research framework to build, maintain, and evaluate ML with declarative configs.
Learn More
AI at the SEI
• Video
By Michael Mattarock, Matthew J. Butkovic
In this episode, Matt Butkovic, talked with Michael Mattarock, about the SEI’s efforts to apply AI techniques to address national security mission needs while leading a national initiative to build …
Watch