Human-AI Decision Systems
Learn how to create high performance Human-AI decision systems
Informed decision-making is one of the core tenants of military operations, however, the nature of modern security threats, the democratization of technology globally, and the speed and scope of information flows are stressing traditional operational paradigms, necessitating a fundamental shift to better integrate machine-assistance into the decision-making process. In this course, we cover the current state of decision systems and propose four concepts to guide the creation of high-performance human-AI decision systems. These concepts are inspired by successes within the commercial sector and academia that successfully integrate information across multiple domains and jointly leverages the strengths of both humans and AI capabilities. The first concept is an approach for measuring and analyzing the contributions of both humans and technology in-context to determine which areas the decision process and the workforce are most amenable to AI assist. The second concept is a framework for the integration of AI capabilities into the enterprise that optimizes trust and performance within the workforce. The third is an approach for facilitating multi-domain operations though real-time creation of multi-domain task teams by dynamic management of information abstraction, teaming, and risk control. Lastly, we describe a new paradigm for multi-level data security and multi-organization data sharing that will be a key enabler of AI-enhanced multi-domain decision-making in the future.
Designed for senior managers in any industry who want to enhance their ability to lead, develop, and deploy AI systems. In particular, this course will benefit individuals who are responsible for defining technology strategy; for example, those with titles such as Chief Technology Officer, Chief Information Officer, Technical Manager, Project Manager, and AI Design Engineer.
This course is appropriate for individuals at any company—from global corporations to small start-ups—that develops AI system capabilities or is a user/buyer of AI systems. Participants are welcome from a wide range of industries including energy, consumer AI products and services, aerospace, transportation, robotics systems, finance, national security, and health. Participants interested in human-AI decision systems are especially encouraged to participate.
Alex Pentland (MIT Media Lab), Matt Daggett (Lincoln Laboratory)
Course overview and introduction to key concepts
Overview of collaborative human decision making and discussion of the potential for enhancement with AI
Basics and foundations of AI technologies and their application joint human-AI decision systems
Measuring and understanding the performance of humans and sociotechnical systems in-context
Discussion and brainstorming sessions with students on challenges from their organizations and how to identify which concepts and technologies best apply
Overview of applications of human-AI decision systems within the U.S. Air Force
Discussion and brainstorming with students on lessons learned from their organizations and experience
Fundamentals of transparency, reliance, and trust-calibration in human-AI constructs
Optimization of joint human-AI performance and effectiveness within the workforce
Enabling multi-domain operations though facilitation of multi-organization multi-domain task teams that balances information abstraction, collaboration, and risk
New paradigms for multi-level data security and multi-organization information sharing for joint operations
Strategies for the adoption of human-AI technologies within the requirements and acquisition process
There are no pre-requisites to this course.