Augmented (human) Intelligence, AI

IIn the National Defense Strategy of 2018, Secretary of Defense James Mattis encouraged adoption of new
practices to achieve greater performance and affordability to meet current and future challenges. The recently
signed Digital Engineering Strategy outlines several goals to help achieve the necessary improvements. In
particular, Goal 3 is to “incorporate technological innovation to improve the engineering practice”. It proposes advancements in human-machine interactions, realizing an end-to-end digital enterprise, advances in artificial intelligence and cognitive technologies.
This strategy follows The International Council on Systems Engineering (INCOSE) efforts to accelerate the
transformation of Systems Engineering to a model based discipline. In particular, INCOSE’s Augmented
Intelligence in Systems Engineering (AuI SE) Challenge Team is directed to further the understanding of how
computational approaches, such as artificial intelligence, machine learning, and data science, can collaborate with
human systems engineers to measurably improve the system engineering effort. The activity is leveraging SE and
AI best practices to develop a framework and technical approach to enhance human capabilities in systems
engineering.
The poster outlines findings from the INCOSE AuI SE activity and characterize a “team play”
approach – where engineers and algorithms can coordinate to develop transparent, traceable, and
understandable system designs that are better than either human or algorithmic approaches could develop alone.
Augmented Intelligence requires deliberate consideration to the characteristics of AI systems as integral parts of
the engineering system. The team has identified several characteristics critical to support “team play”
development: 1) understanding the conceptual model for learning and application of learned information in a
mixed environment, 2) roles and responsibilities for models and humans in a unified human-model interaction
team, and 3) factors influencing trust in model-centric decision making.
This poster visually describes how well-structured data in the form of system models enables the use of artificial
intelligence, algorithmic capabilities, expert systems, and human-computer interactions as essential elements in
improving the performance of systems engineering and its essential role in improving our National Security.
Expected outcomes include improving decision making, speeding capability development and overall
improvement in the ability to innovate. The INCOSE AuI SE team includes contributors from commercial, FFRDC,
and academic participants.

The prime purpose of a consciousness switch is to keep track of infological direction while interconnecting a basically analogue non-blocking token flow of something we can call "meaning". This translates into an asynchronous mode of information accretion as well as dilution of information sometimes separated by some transitional decision state that may evolve into a basically quantized intentions which is a result of a finished "thought" as described by the article called "The nature of thinking".