1. Engineering Autonomy Mr. Robert Gold Director, Engineering Enterprise
Office of the Deputy Assistant Secretary of Defense for Systems Engineering
Society of Automotive Engineers (SAE)
Aerospace Standards Summit
McLean, VA | October 2, 2018

2. Outline Defense Research and Engineering (R&E) Strategy
Key Research and Development Areas
Background
Engineering Challenges
Summary

3. Defense Research & Engineering Strategy
Mitigate current and anticipated threat capabilities
Enable new or extended capabilities affordably in existing military systems
Create technology surprise through science and engineering
Focus on Technical Excellence Deliver Technologically Superior Capabilities Grow and Sustain our S&T and Engineering Capability

4. Key Research & Development Investment Areas
Autonomy & Robotics
Electronic Warfare / Cyber
Microelectronics
Hypersonics
Directed Energy
Manufacturing
Artificial Intelligence / Man-Machine Interface
Future of Computing
Novel Engineered Materials
Precision Sensing: Time, Space, Gravity, Electromagnetism
Emerging Biosciences
Understanding Human and Social Behavior

5. Background DoD emphasis on the increased use of autonomous systems
DASD(SE), in collaboration with Services, assessed current autonomy efforts and associated engineering challenges
The purpose was to ascertain the ramifications of autonomous systems on DoD engineering practice

6. Engineering Challenges
Increase Level of Experimentation
Understand autonomy trade-space for architecture/conceptual designs
Engage Warfighter in experimentation to set expectations
Engage Service Laboratories and Industry Partners to conduct mission-specific experiments
Leverage computational biosciences, cognitive and social sciences, and robotics opportunities
Standardize Taxonomy
Develop autonomy-consistent terms, definitions, and phraseology (e.g., authorized/control entities, flexible/supervised autonomy, human on/outside the loop)
Refine Requirements Development
Apply tools to translate natural language, imagery, and video to representations and relations usable for reasoning
Advance methods to encode interactions between operators and the system for requirements traceability
The source of these voice-over recommendations is AFRL 711 HPW:
-The bullet “Increase Level of Experimentation” – add the concept of building repositories of large labeled datasets to support future AI development.
Computational biosciences is the pioneering field of study that leverages computational power of computer that advance human health and molecular understanding of life. It is the science of using biological data to develop algorithms or models to understand biological systems and relationships.

7. Engineering Challenges
Understand/Manage Human-Machine Interaction
Allocation of functions between human and machine
Explore techniques for ensuring operators trust autonomous systems
Advance sensor development and assessment methodologies
Leverage wearable electronic sensor development and adapt to the cognitive/physical state of the warfighter
Facilitate Trust and Social Interactions
Develop software assurance tools to enhance ‘trust’
Define techniques for monitoring and bounding autonomous system behaviors
Understand social dynamics of autonomous systems to effectively communicate and collaborate with humans
The source of these voice-over recommendations is AFRL 711HPW:
It is recommended that under the “Understand/Manage Human-Machine Interaction” bullet:
-Voice-over on “Allocation of functions between human and machine”:
Humans will likely train machines and feedback mechanisms must be designed without interfering with the human’s normal operation of the machine.
-Voice-over on “Advance sensor development and assessment methodologies”:, it is recommended to note:
“Assessment methodologies” include (1) machine learning and (2) advancing cognitive modeling. Examples of cognitive modeling include realistic avatars, adaptive training, and performance monitoring and prediction.
(2) It is recommended that under the “Facilitate Trust and Social Interactions” bullet:
-The software design will have to take into account the leveraging of human perceptual and cognitive processes. The human will need to see the display of information in and explainable and usable manner to effectively establish trust.

8. Engineering Challenges
Enhance Analysis, Evaluation, and Certification
Explore use of formal methods to analyze autonomous systems
Enable rapid evolution of autonomous capabilities thru:
Rapid deployment of software upgrades
Perform system certifications concurrently with design
Use of modular open systems architecture
Synchronize Technology Development with Life Cycle Planning
Rapid autonomous system development and technology transition will mandate effective coordination between engineering and product support activities.

9. Engineering Challenges
Understand Consequences of Self-Learning Systems
Evaluate consequences of autonomous system behavior being dictated by hardware, software, and system data.
Artificial intelligence will allow new levels of autonomy
Understand Impact to the Workforce
Develop the Body of Knowledge for autonomous systems to support competency development
Mission-specific work force education, training, and experience in human-autonomy teaming
Establish Science, Technology, Engineering, and Mathematics relationships with academic institutions
The source of this voice-over material is the AFRL 711 HPW:
It is recommended that under the “Understand Consequences of Self-Learning Systems” bullet:
-Self-learning systems will bring with them the ability to magnify the human-machine productivity. It will also bring with it the need to be cognitive of trust (including system safety) in its design, but also the requirement for system security to protect the system from cyber tampering.
(2) Voice-over for “Understand Impact to the Work Force”:
…it is important to state that DoD recognizes that the workforce must be educated and trained to support autonomous systems, artificial intelligence technologies, and the human-machine collaboration process.

10. Summary
Fielding autonomy-enabled warfighting capability will require close collaboration with:
Research, Engineering, and Test & Evaluation
Acquisition and Operational Communities
Our Industry Partners
Collaboration needs to occur through planned demonstrations and prototyping, especially at Engineering Commands where these systems are currently designed.
Autonomy technologies will impact the collective workforce, inclusive of the challenges unique to the engineering community.

11. Systems Engineering: Critical to Defense Acquisition
Defense Innovation Marketplace
DASD, Systems Engineering

12. For Additional Information
Mr. Robert Gold
ODASD, Systems Engineering