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The Situation Awareness, Decision, and Execution (SADE) Ladder: A Framework for Human-AI Collaborative Decision-Making

Author

Listed:
  • Joerg Beringer

    (ProContext)

  • Alexander J. Karran

    (HEC Montreal)

  • Constantinos K. Coursaris

    (HEC Montreal)

  • Pierre-Majorique Léger

    (HEC Montreal)

Abstract

In order to implement intelligent systems that exhibit autonomous behavior, the system must develop its own situation awareness and ability to execute the decisions being made. To model these end-to-end decision loops, we propose a framework that combines situation awareness, decision-making, and action-planning theories into one decision ladder that helps to understand the requisite anatomy and ergonomics of intelligent systems. This Situation Awareness and Decision Execution (SADE) Ladder acts as a catalyst bringing together different research disciplines specialized in each of the three referenced domains. This synergistic view across multiple research agendas manifests in a conceptual framework to understand better the interaction dynamics in human-AI interactions and the importance of transparency and explainability in multi-agent networks to help the human experts understand the locality of artificial system intelligence and the underlying rationale of system-generated decisions and action plans. Identifying the different cognitive demands and sub-functions within the SADE Ladder enables practitioners to derive the appropriate requirements from cognitive work analysis and design intelligent systems for workplaces that are trusted and accepted by their users.

Suggested Citation

  • Joerg Beringer & Alexander J. Karran & Constantinos K. Coursaris & Pierre-Majorique Léger, 2025. "The Situation Awareness, Decision, and Execution (SADE) Ladder: A Framework for Human-AI Collaborative Decision-Making," Progress in IS,, Springer.
    • Handle: RePEc:spr:prochp:978-3-031-83512-4_2
    DOI: 10.1007/978-3-031-83512-4_2
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