Attachment 5 TO 04 FA8650-22-F-6408 SOO Final.pdf

Basic FA8650-22-D-6400 Task Order 04 FA8650-22-F-6408

STATEMENT OF OBJECTIVES

FA8650-22-F-6408

Human and Machine Co-Learning

21 October 2021

FA8650-22-D-6400

Task Order 0004

1.0 OBJECTIVE. The objective of this effort is to enable training for humans, machines, and teams of humans and machines by creating capabilities for collaborative real-time learning, planning and decision-making. The goals of the effort are to improve the USAF and USSF’s capability to prepare multi-capable Airmen, to personalize, adapt and assess individual and team training; and to advance robust machine learning and interactive task learning to improve Airman, intelligent agent, and team proficiency and performance by developing and validating agile, collaborative human-machine teaching and learning of entirely new content on demand.

2.0 SCOPE. The scope of this effort includes the development, test, and validation of training approaches, methods, tools, instrumentation, and enterprise infrastructure for learning and operational readiness. It includes efforts to measure and model Airman expertise and performance to enable training for teams of humans and machines and to develop and validate human-machine teaching and learning to enable multi-capable Airman. The research will discover, develop, and transition operator-centric interface technology, robust machine learning, intelligent tutors, decision aiding tools, and situationally-adaptive augmentation methods to seamlessly integrate Airmen, Space Guardians and intelligent machines into maximally collaborative warfighting teams. Envisioned technologies will provide the capability to increase the Airman's combat capabilities, enabling humans, robots, and agents to transfer knowledge, learn collaboratively, and acquire new tasks through natural interactions.

3.0 REQUIREMENTS

3.1 Collaborative Human-AI Mission Planning & Debrief. The contractor shall develop and demonstrate technologies that enable a team of manned and unmanned space and aircraft, together with other team members, to simultaneously understand the mission representation to conduct tactical missions on ground or space targets in a contested environment. The contractor shall develop and deliver technologies and processes changes for integrating unmanned space and aircraft and intelligent agents into all stages of mission planning and debriefing. This includes methods and approaches to deliver agents capable of 1) mission-relevant content parsing, processing, and constraint representation; 2) continuously running agents and AI adapting to evolving human intent; and 3) interactive streaming data analytics and incorporation of novel information from multiple sources, to include inferences about new information provided through machine communications media and through conversation and interaction between human mission planners; 4) communicating with humans and other agents relevant information, constraints and evolving planning conditions to support reasoning, anticipatory thinking, and decision making; and 5) synthesizing pre-mission plans and mission execution data for comprehensive joint mission debriefing with human planners, including manned and unmanned aircraft teams.

3.2 AI-enabled Knowledge Capture and Transfer. The contractor shall enable human and machine collaborative reasoning and co-learningby advancing technologies that enable machines to accurately infer skills, knowledge, expertise and goals from humans and leverage that capture to inform learning and teaching between humans

Attachment 1 and intelligent agents. This includes developing or leveraging real-time sensing of the physical environment to inform inferences about cognitive processes, goals, and priorities, delivering 1) interactive machine intelligence capable of learning with minimal training data and through natural interactions with humans; 2) methods and approaches for integration of sensor technologies including natural language processing with cognitive modeling approaches; 3) computer vision techniques capable of action classification and behavior recognition relevant to human and machine co-learning and mission planning; 4) validated methods leveraging goals, planning, and Bayesian inference to support collaborative human-AI reasoning, planning and decision making;

and 5) approaches for integration of inferences across interactions in continuously running agents. The contractor should advance techniques for integrating domain knowledge acquired through Cognitive Task Analysis into co-learning teams and technologies. The effort will require the contractor to (1) develop and execute experimental designs to evaluate effects of system development on system usability, human machine teaming, and human performance; (2) develop and evaluate human and machine interfaces for knowledge transfer, human machine teaming, and co-learning; and (3) explore mobile devices and robot capabilities for applying virtual teammate technology to human training tasks.

3.3 Mutual Understanding for Effective Human-Autonomy Teaming. The contractor shall identify, analyze and develop theories, methods and technologies to study and address capabilities to establish, promote and maintain mutual understanding between humans and autonomous or artificial-intelligence-enabled technologies (referred to as “intelligent machines”). This effort will (1) define the criteria, benchmarks, and critical validation processes to test for an intelligent machine’s ability to understand its human teammates and human abilities to make appropriate inferences about machine teammates; (2) develop rigorous definitions and working models, implemented in a demonstration human-machine system, of the fundamental mechanisms for machine understanding of human teammates; (3) support the developmental test, evaluation, validation, and verification of human-machine teams complementing domain-specific research at the human-machine interface; (4) support the evaluation of robustness in human-machine teaming to ensure readiness under adversarial conditions.

3.4 Technical Briefings and Demonstrations. The Contractor shall participate in 711 HPW/RHW briefings and demonstrations to Air Force operational personnel, as required.

3.5 Program Management. The contractor shall perform all management and administrative functions for the Task Order.

3.6 Operations Security (OPSEC). The highest level of security classification for the technical research areas under this contract is Top Secret.

The contractor shall provide OPSEC protection for all sensitive/critical information and indicators involved in execution of this contract/Task Order, as defined by AFI 10-701 (Operations Security). 711 HPW Critical Information and Indicators are protected under the 711 HPW Operations Security Program and the 711 HPW Critical Information and Indicators List (CIIL). Contractor employees granted access to critical information and indicators will be provided initial OPSEC training by the 711 HPW OPSEC Coordinator upon in-processing and prior to being granted access to CIIL items related to the contract/Task Order. The contractor will also participate in 711 HPW’s annual OPSEC training and education programs, which includes periodic updates and refresher training on CIIL items applicable to the contract/Task Order. The 711 HPW OPSEC coordinator will evaluate the OPSEC posture of AF contract activities and operations.

All contractor personnel require a minimum of a Tier 1 background check (T1)/SF85 for any position that requires access to the internet, use of automated information systems to cover standalone computers or unescorted entry into restricted or controlled areas prior to reporting for duty in support of any requirement. The investigation is not for a security clearance; it is for a position of trust. This is a mandatory requirement set forth in DoDM 5200.02_AFMAN 16-1405, Air Force Personnel Security Program. All documentation required for security certification shall be the responsibility of the contractor.

3.7 Information Security and Force Protection. The contractor will provide Information Security and Force Protection training pursuant to the Basic Contract terms.

3.8 Protection of Human Subjects. The technical research areas under this contract are anticipated to include human subject research. The contractor shall provide for the protection of human subjects pursuant to the Basic Contract terms.

4.0 OTHER REQUIREMENT

4.1 GFP/GFI – N/A

4.2 Base Support – Includes working space, phones, network access, material, equipment, services, office computers, access to conference rooms, server rooms, lab spaces and testbeds or other support in the performance of this effort at Bldg 852

WPAFB, OH

-Unclassified Lab/testbeds (Rm 331) -Classified Labs/testbeds (Rm 111, 114, 115, 116, 151, 153, 155, 155A, 204, 206, 214, 215, 216, 216A, 217, 339) -Contractor work area (Rm 327, 334, 340)

4.3 CAP – N/A

4.4 Ground Flight Test – N/A

4.5 Software – Any data and software developed

4.6 Hardware – Any hardware prototypes developed or special test equipment acquired in support of research objectives.

4.7 ACA - CAE USA (L3 Harris) and Carnegie Mellon University (CMU)

5.0 REPORTING / DOCUMENTATION

A001: DI-MISC-80711A/T - Scientific and Technical Reports – Final Report

A002: DI-FNCL-80331A/T - Funds and Man-Hour Expenditure Report A003: DI-MGMT-81468/T - Contract Funds Status Report (CFSR) A004: DI-MGMT-80227/T - Contractor Progress, Status, and Management Report A005: DI-MISC-80711A/T - Scientific and Technical-Interim Report A010: DI-IPSC-81488/T - Computer Software Product Source Code A020: DI-ADMN-81373/T - Presentation Material A021: DI-MISC-80508B/T – Technical Report - Study/Services A022: DI-QCIC-80553/T - Acceptance Test Plan (ATP) A023: DI-IPSC-81427A/T - Software Development Plan (SDP) A026: DI-MISC-80711A/T - System Security Plan