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A better world through a systems approach

Artificial Intelligence Systems

AIExplorer

Next Session: May 4th
(Star Wars Day: May the 4th be with you)

10:00 AM US Eastern Time

FREE – REGISTER NOW

TWO FEATURED TALKS

AI Explorer events feature two brief (TED-style) talks on key Artificial Intelligence topics. First up is a tour of the subject of explainable AI—a very hot topic in AI these days. After that, in honor of Star Wars Day, we’ll take a look at how AI appears in Star Wars, and Star Trek also, and see how AI is depicted in the science fiction future.

Ali_Raz

A System Engineer’s Guide to Explainable AI

Abstract: System Engineers (SEs) are faced with incorporating Artificial Intelligence and Machine Learning (AI/ML) based solutions into modern systems for meeting complex technological and societal needs. It is imperative for SEs to characterize the behavior of AI/ML based components that often appears as black boxes even to the component designers. This talk will introduce key concepts of Explainable AI (XAI) that creates a window into the black-box nature of AL/ML based component. We will debunk some common myths about explainability and discuss how SEs can utilize XAI for test and evaluation of systems with AI/ML-components.

Presenter: Dr. Ali Raz (CSEP) is an Assistant Professor of Systems Engineering and an Assistant Director of Intelligent Systems and Integration at George Mason University C4I and Cyber Center. Dr. Raz research interests are in integrating autonomous systems and brings together a system of systems perspective with artificial intelligence and information fusion. Dr. Raz is the current co-chair for INCOSE’s Artificial Intelligence Working Group and a co-chair of the Complex Systems Working Group. He holds a BSc and MSc in Electrical Engineering from Iowa State University and a doctorate in Aeronautics and Astronautics from Purdue University.

Barclay_Brown

Everything I Know about Artificial Intelligence I Learned from the Movies

Abstract: Much of what most people “know” about artificial intelligence traces its source to science fiction mythology. Science fiction representations of robots, created minds, and intelligent machines spans a wide range of perspectives. Speculative books may describe possible futures of AI, but movies and TV series can show what a world would be like if these scenarios became reality. Star Wars and Star Trek, show nearly polar opposites in how AI turns out in a highly advanced human (and non-human) civilization.

Presenter: Dr. Barclay R. Brown, ESEP,  is Associate Director for Research in AI at Collins Aerospace, a division of Raytheon Technologies. Before joining Collins, he was an Engineering Fellow in Raytheon Missiles and Defense, focusing on MBSE, and prior to that he was the Global Solution Executive for the Aerospace and Defense Industry at IBM. Dr. Brown holds a bachelor’s degree in Electrical Engineering, master’s degrees in Psychology and Business and a PhD in Industrial and Systems Engineering. He has taught systems engineering and systems thinking at several universities, and is a certified Expert Systems Engineering Professional (ESEP), certified Systems Engineering Quality Manager, and CIO of INCOSE for 2021-2023. He chairs the INCOSE AI Systems working group.

Mission & Objectives

The general goals of the AI Systems WG are to identify needs of the international AI community (industry, academia, government) which are well-suited for contributions by INCOSE, and to provide expertise across SE functions and lifecycle management that can be used by industry to promote the development of AI Systems. The specific goals are to: 1) identify and communicate emerging AI technologies that can be applied to the engineering of systems (AI for SE), including AI that appertains to industries of the Future, and 2) develop and communicate advances in SE methods needed to effectively engineer systems with embedded AI (SE for AI). To meet these goals, the following research objectives have been identified: 

  • Explore Human-AI collaboration

  • Evaluate Safety and Security of AI systems

  • Measure and evaluate AI technologies through standards and benchmarks

  • Understand and promote workforce development and STEM initiatives

  • Contribute to public-private partnerships and affiliations to accelerate advances  

  • Establish best practices for using AI techniques in Systems and Systems Engineering

Leadership

Barclay R. Brown, Ph.D., ESEP, Assoc. Director AI Research Collins Aerospace
Chair

Ali Raz, George Mason University
Co-Chair

Tom McDermott - Stevens Institute of Technology
Co-Chair

Interested?! Please contact the chairs for how to get involved!

Working Group Products

SE & AI Primer

Planned Working Sessions at the Next Events


Planned Presentations at the Next Events