Sally Maynard

Papers

Total Citations

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About

Sally Maynard is a researcher whose work lies at the intersection of artificial intelligence, multiagent systems, and human-machine teaming, with a particular focus on trust and decision-making in dynamic, high-stakes environments. Her most cited paper, "Steps towards Satisficing Distributed Dynamic Team Trust" (2024), makes a foundational contribution by defining and operationalizing trust within distributed, rapidly evolving teams—a critical challenge for defense and security domains. In this work, Maynard addresses how autonomous agents and human operators can maintain calibrated trust when goals and team composition shift in real time, proposing a satisficing approach that balances performance with reliability. While her citation count is still growing, this paper has already garnered attention for tackling a pressing gap in multiagent trust research. Maynard’s work is notable for its practical orientation, aiming to ensure that team members—whether human or artificial—can be trusted to work toward shared goals and uphold common values, even under uncertainty. Her research is essential reading for anyone interested in building resilient, trustworthy AI systems for collaborative, mission-critical applications.