Multimodal Conflict Prediction & Auto-Mediation
Developing an autonomous system that predicts interpersonal conflict before escalation and deploys adaptive mediation strategies using real-time multimodal signals.
Abstract
This research investigates whether interpersonal conflict can be detected and mitigated proactively using continuous analysis of voice, language, and interaction dynamics. The system aims to identify early indicators of tension, misalignment, and breakdown in shared mental models - enabling preventive mediation rather than reactive intervention. The work targets high-risk, high-isolation environments where delayed or unavailable human support amplifies the cost of conflict.
Problem
Interpersonal conflict is a leading cause of team performance degradation, psychological stress, and mission failure. Current approaches are reactive, human-dependent, and not scalable to isolated or autonomous environments. There is no widely deployed system capable of early, autonomous conflict detection and mitigation.
Hypothesis
Continuous multimodal monitoring of communication patterns can reveal pre-conflict signals - such as divergence in tone, timing, trust markers, and shared context - hours or days before overt conflict. Autonomous, context-aware mediation can reduce escalation and preserve team cohesion.
Methods
- •Multimodal signal capture (Voice prosody + Linguistic features + Interaction dynamics)
- •Shared mental model analysis (Divergence detection + Conversational coherence)
- •Conflict prediction modeling (Temporal escalation forecasting + Confidence estimation)
- •Autonomous mediation strategies (Context-aware prompts + Adaptive role restructuring)
- •Ethical & safety constraints (Non-manipulative interventions + Transparency + Human override)
System Architecture
Pipeline
Key Outputs
Conflict Prediction Model
Early-warning indicators with confidence bounds.
Autonomous Mediation Engine
De-escalation and task-adaptation strategies.
Ethical Mediation Framework
Transparency and consent-driven safeguards.
Progress Timeline
Signal & Theory Mapping
2025-07-01Identification of early conflict indicators.
Predictive Modeling
2025-08-25Prototype escalation forecasting models.
Mediation Evaluation
2025-10-15Testing adaptive intervention strategies in simulations.
Integrated Simulation Trials
2025-11-18Full-loop testing in high-fidelity VR isolated environments.
User Acceptance Testing
2025-12-15Validation with expert cohorts in simulated high-stress scenarios.
Field Deployment Readiness
2026-01-03Final safety checks and packaging for limited real-world deployment.
Outputs
Ethics & Safety Note
The system is designed to support human collaboration, not replace human judgment. All interventions prioritize autonomy, consent, and transparency.