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Description: This project introduces the Clarification Seeking Engine (CSE), a novel framework designed to enhance AI systems’ ability to handle uncertainty and ambiguity in human communication. CSE addresses the limitations of traditional AI models by employing a 13-level temperature scale to quantify the AI’s confidence in its understanding of user input. Key components of the CSE framework include: Temperature Scaling System: A dynamic scale that adjusts AI responses from direct answers at high confidence to clarification requests and hypotheticals as ambiguity increases. Proactive Hinting: The AI offers real-time suggestions or prompts to guide conversations, ensuring smooth communication and minimizing misunderstandings. User-Specific Modeling: CSE builds adaptive models based on individual user communication styles, improving AI’s ability to personalize interactions. Confidence Estimation Mechanisms: These mechanisms detect inconsistencies, contradictions, and missing information, allowing the AI to proactively address gaps in understanding. By integrating these features, CSE provides a more ethical, transparent, and effective approach to AI communication, with broad applications across fields such as policy-making, education, and business strategy. This project is a collaborative effort from the Earth Refocus Institute and aims to push the boundaries of how AI manages complex communication. The full framework, technical details, and research documentation are available within this repository.