Human-AI teams in complex military operations: Soldiers’ perception of intelligent AI agents as teammates in human-AI teams

Abstract

Military decision-making frequently involves complex problems in non-routine situations with minimal rule-based or automated solutions. As human information processing capabilities are limited, processing the required scale of information increases the decision-makers’ workload, impacting their situational awareness and affecting the quality of soldiers’ decisions. This study uses a route clearance task as a use-case scenario to understand the issues in team-level decision-making in military tasks, the challenges in successfully completing the mission, and the demands placed on AI teammates when working in a human-AI team. We interviewed eight subject matter experts with prior experience in route clearance operations. The themes generated by analyzing the interview transcripts provide insights into soldiers’ perceptions of AI teammates as well as recommendations for successfully integrating human-AI teams in military settings.

Keywords

Human-AI teaming AI integration Situational awareness

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References

Bosch

Bronkhorst

A. W.

(2018, January). Human-AI cooperation to benefit military decision-making. NATO.

Ezer

Bruni

Cai

Hepenstal

S. J.

Miller

C. A.

Schmorrow

D. D.

(2019). Trust engineering for human-ai teams. In Proceedings of the human factors and ergonomics society annual meeting (Vol. 63, pp. 322–326).

Gunning

Aha

(2019). DARPA’s Explainable Artificial Intelligence (XAI) program. AI magazine, 40(2), 44-58.

Harari

Y. N.

(2016). Homo Deus: A brief history of tomorrow. Random House.

Zhang

Ren

Sun

(2015). Delving deep into rectifiers: Surpassing human-level performance on image net classification. In Proceedings of the IEEE International Conference on Computer Vision (pp. 1026-1034).

Kim

Jang

Sunwoo

(2014). Development of autonomous car—Part I: Distributed system architecture and development process. IEEE Transactions on Industrial Electronics, 61(12), 7131–7140.

Jong

I. M.

de Daalen

J. A.

van Dekkers

P. A. P.

(2014). Op weg naar de Landmacht van Overmorgen. Militaire Spectator, 183(4), 179–190.

Kahneman

(2011). Thinking, fast and slow. Macmillan.

McNeese

N. J.

Demir

Cooke

N. J.

Myers

(2018). Teaming with a synthetic teammate: Insights into human-autonomy teaming. Human factors, 60(2), 262-273.

10.

McNeese

N. J.

Schelble

B. G.

Canonico

L. B.

Demir

(2021). Who/What Is My Teammate? Team Composition Considerations in Human–AI Teaming. IEEE Transactions on Human-Machine Systems, 51(4), 288-299.

11.

Nixon

Leggatt

Campbell

(2015). The development and assessment of behavioural markers to support counter-IED training. Applied Ergonomics, 48, 130-137.

12.

Olinover

Gidron

Yarmolovsky

Geva

(2021). Strategies for improving decision making of leaders with ADHD and without ADHD in combat military context. The Leadership Quarterly, 101575.

13.

O’Neill

McNeese

Barron

Schelble

(2020). Human–autonomy teaming: A review and analysis of the empirical literature. Human factors, 0018720820960865.

14.

Paparone

C. R.

Reed

G. E.

(2011). The Reflective Military Practioner: How Military Professionals Think in Action. Military Review, 67.

15.

Sawant

Mallick

McNeese

Chalil Madathil

(2022, September). Mutually beneficial decision making in Human-AI teams: Understanding soldier’s perception and expectations from AI teammates in human-AI teams. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 66, No. 1, pp. 287–289).

16.

Wilson

(2007, November). Improvised explosive devices (IEDs) in Iraq and Afghanistan: effects and countermeasures. library of congress washington dc congressional research service.

17.

Zhang

McNeese

N. J.

Freeman

Musick

(2021). " An Ideal Human" Expectations of AI Teammates in Human-AI Teaming. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW3), 1-25