Managing Ambiguity: A Proof of Concept of Human-AI Symbiotic Sense-making
This study presents a proof of concept for the LAIZA human-AI augmented symbiotic intelligence system, which aims to help organizations manage ambiguity in volatile, uncertain, complex, and ambiguous (VUCA) environments.
Why it matters
This research addresses a critical gap in management science by proposing a novel human-AI system to help organizations effectively manage ambiguity in volatile and complex environments.
Key Points
- 1Addresses the gap in management science regarding how human-AI systems can responsibly manage ambiguity
- 2Introduces the LAIZA system and its patented process: Quantum-Inspired Rogue Variable Modeling, Human-in-the-Loop Decoherence, and Collective Cognitive Inference
- 3Operationalizes ambiguity as a non-collapsed cognitive state and detects persistent interpretive breakdowns (rogue variables)
- 4Activates structured human-in-the-loop clarification when autonomous inference becomes unreliable
- 5Empirical case study shows that preserving interpretive plurality enabled early scenario-based preparation and proactive action
Details
The study presents a proof of concept for the LAIZA human-AI augmented symbiotic intelligence system, which aims to help organizations manage ambiguity in volatile, uncertain, complex, and ambiguous (VUCA) environments. The system operationalizes ambiguity as a non-collapsed cognitive state and uses a patented process to detect persistent interpretive breakdowns (rogue variables) and activate structured human-in-the-loop clarification when autonomous inference becomes unreliable. The goal is to preserve interpretive plurality and enable early scenario-based preparation, allowing for decisive and disruption-free action once ambiguity collapses. The study contributes to management theory by reframing ambiguity as a first-class construct and demonstrates the practical value of human-AI symbiosis for organizational resilience in VUCA environments.
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