Working Group Purpose & Mission


The INCOSE AI Systems WG was established as a result of the Future of Systems Engineering (FuSE) initiative in 2019. The purpose of the AI Systems WG is to identify and communicate emerging AI technologies that appertain to industries of the Future. The AI Systems WG seeks to establish INCOSE as a recognized resource of expertise for research, development, and application of AI systems.


AI Explorer events feature two brief (TED-style) talks on key Artificial Intelligence
topics and allow time for questions and discussion by all participants.

Watch this space for announcement of the next AI Explorer program

Next AI Explorer Event

April 6, 10:30 am New York,

Topic: Large Language Model Applications 

Talks and Speakers: 


1. How Large Language Models Work: Next Word Prediction using Word Vectors, RNN, LSTM (Dr. Barclay Brown, Assoc. Dir AI Research, Collins Aerospace) 


LLMs like GPT-4 and chatGPT are popular in the press and getting lots of attention for their surprising abilities. But how do they work? Are they small minds that think like we do? Are they nearly sentient? In this segment we'll look closely at the fundamental concepts used to create LLMs, and break it down to fundamentals without using code or advanced math.



2. Diagram generation with Large Language Models (Ricardo Reis) 


3. LLMs: Need for Prudence (Dr. Ramakrishnan Raman, Fellow, Honeywell Aerospace) 

Abstract: As with any of the contemporary AI models, Large Language Models too have limitations. It is necessary for users to be cognizant of those limitations. For instance, uses may need to be aware of the  limitations due to the inherent bias and inaccuracies in the data used for training – since these aspects would have a significant bearing on the model responses. This brief session would highlight some of the typical limitations of large language models, and stress the need for discretion while being aware of associated implications.

Bio: Dr. Ramakrishnan Raman is currently Fellow at Honeywell Aerospace, and Co-Chairs the INCOSE AI Systems Working Group. His areas of interest includes complex systems, system-of-systems and AI-ML.

4. Applications of LLMs (Tom McDermott) 

Transformation Enablers

TechOps Domain






Barclay Brown


Ali K. Raz

Ramakrishnan Raman

Tom McDermott


This WG will address use of AI within Systems and using AI as part of the Systems development. The WG will encourage research to be conducted by members or via collaboration with other organizations.


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
Customers/Stakeholders in the AI Systems WG include INCOSE members, chapters, WGs, Corporate Advisory Board, Academic Council and affiliates.


  • AI Explorer Series (recordings posted in iNet)
  • AI Systems Primer (in progress)
  • IW2023 Lightning talk series in MBSE program

Recordings from this Event Coming Soon

IW23: International Workshop Focus

SE AI/Machine Learning Workshop

IW2023, Sunday, January 29

MBSE TED-Like Lightning Round is focused on Artificial Intelligence (AI) and Machine Learning (ML).



(Barclay Brown, MC)

10:30-11:00, Opening: Three Wakeup Calls for AI and SE and AI Systems WG Update, Barclay Brown

11:00 – 11:30, Keynote 1: AI in Defense and Aerospace, Tod Newman, former AI Lead, Raytheon Technologies

11:30 – 11:50, Roadmap for AI and SE, Tom McDermott

11:50 – 12:00, Discussion: Priorities for AI and SE in 2023

12:00-13:00, Lunch


(Ali Raz, MC)

13:00-13:20, Time slot 1: Digital Assistance for Systems requirements Discovery and Analysis Using Machine Learning Natural Language Processing Algorithms (Nipa Phojanamongkolkij)

 (Alessandro Migliaccio)

13:40-14:10, Time slot 3 – Use NLP to Create Behavior Models from Natural Language Text, Steve Dam, SPEC Innovations

14:00-14:20, Time slot 4  - Agent-Based Modeling from a Systems Engineering Approach  (Rebekah Yang)

14:20-14:40, Time slot 5 - AI/ML Risk Management Approach for Federal Agencies (PACE Concept) (John Crissman)

14:40-15:00, Time slot 6 – (CHALE GONGORA Hugo Guillermo)

15:00-15:30, Break

15:30-15:50, Time slot 7: MBSE to support AI Digital Assistant solutions (Ricardo Reis)

15:50-16:10, Time slot 8 - Staying Fresh and Relevant: Book Review of Mathematical Intelligence, by Junaid Mubeen, and The Myth of Framework by Karl Popper (Josh Sparber)

16:10-16:30, Time slot 9 – Test and Evaluation of AI Systems with Explainable AI and Counterfactuals (Ali Raz)

16:30-17:00, Time slot 10 – Quick Overview of AI Primer, with Discussion and Feedback (Ali Raz, Ramakrishnan Raman) 17:00-17:30, Speaker Interaction/Q&A session and wrap-up


Planned Activities

  • AI Explorer programs - ongoingthing 2
  • Monthly all-WG meetings
  • Weekly leadership check-in meetings
  • Weekly AI Primer editorial meetings

Planned Work Products

  • AI Systems Primer - Q2 2023
  • Self-Guided AI Education - Q2 2023
  • AI Explorer programs - ongoing


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