SCSP / Analysis / Report
Report
Special Resources

Leveraging Human–Machine Teaming

This RUSI–SCSP policy guide argues that US and UK militaries should integrate human–machine collaboration and teaming to offset adversary advantages and improve operations in denied environments.

Authors
Sidharth Kaushal, Justin Lynch, Juliana Suess, Jung-Ju Lee
Published
January 2024
Length
49 pages
Reading time
35 min read
Key Findings
  • The guide distinguishes HMC from HMT by treating HMC as focused on cognitive optimisation, while HMT involves feedback loops between humans and machines that shape the behaviour of both.
  • The authors argue that US and UK offset strategies cannot rest on assumed technological overmatch in AI, autonomy, computing or other militarily relevant science and technology fields.
  • The report identifies decreasing friendly human, economic and political costs, achieving decision advantage, imposing adversary dilemmas, and generating awareness in denied environments as central objectives for HMC and HMT.
  • Near-term priority capabilities include tools for sensing and planning, lower-cost sensing and attack platforms, uncrewed sustainment for expeditionary forces, enhanced operational deception, and predictive maintenance.
  • The guide argues that adoption depends on enablers including new operating concepts, effective human–machine interfaces, workforce models, ethical guidelines, experimentation spaces, fielded experimentation, and acquisition reform.
Overview

Leveraging Human–Machine Teaming is a RUSI Special Resources policy guide produced through a partnership between the Special Competitive Studies Project and RUSI, with separate collaborations involving the US Marine Warfighting Lab and the UK Ministry of Defence. The project drew on three simultaneous London and Washington, DC workshops held between November 2022 and February 2023, supplemented by a literature review and expert consultations. The guide defines human–machine collaboration as focused on cognitive tasks, especially decision-making, and human–machine teaming as broader military processes in which feedback loops between humans and machines affect both. It argues that the US and UK cannot assume enduring technological overmatch in AI, autonomy, computing or related military technologies, especially against competitors such as China. Instead, it presents HMC and HMT as parts of a broader offset strategy built around Western organisational advantages, including adaptation at lower levels and combined-arms experience. Principal priorities include improved sensing, analysis, planning and decision-making; lower-cost attritable platforms; uncrewed sustainment; operational deception; and predictive maintenance. The guide’s policy relevance lies in its implementation framework, which stresses political vision, new operating concepts, acquisition reform, experimentation, workforce development, ethical guidelines, and closer public–private collaboration.

Interdependent human–machine teams will be a key component of future Western efforts to deter great power war and, if deterrence fails, win.

SCSP
Recommendations
  1. Articulate a clear vision of warfighting to drive HMC and HMT implementation. Senior leaders must communicate and resource this vision aggressively to spur services to implement HMC and HMT as an integral part of the solution…
  2. Integrate HMC and HMT development into a broader defense strategy. The development and employment of HMC and HMT must be integrated components of a broad strategy, rather than being left to experimentation in small…
  3. Articulate priority capability categories with an initial emphasis on enhancing existing force design. Any implementation plan should articulate a list of priority capability categories for HMC and HMT, such as the provision of low-cost sensing.
  4. Establish structured spaces for HMC and HMT experimentation. The DoD and MoD can incentivize the use of structured spaces as dedicated areas for trialling and prototyping high-risk capabilities.
From the report
Documents
Publication

Published by the Special Competitive Studies Project. Co-publishers and external authors, where they exist, are credited in the byline above.

Explore more SCSP analysis

Browse the library