Solutions for optimizing cognitive load
CoT-Lab addresses cognitive load in human-computer collaboration through the following core mechanisms:
- cognitive synchronization functionAdjust the "Thinking Synchronization Throughput" parameter (5-10 tokens/second is recommended) to match the AI output with human reading speed. Specific operation: Select "read aloud" or "follow" mode in the slider on the right side of the interface to avoid information overload.
- chunking: The system automatically breaks down complex information into modules (usually 4±1 chunks of information) that meet working memory limits. Users can adjust the chunking granularity by modifying the chunk_size parameter in the configuration file.
- Active Suspension Mechanism: Enable the "Human Rhythm of Thought" function (recommended to pause every 3-5 segments) and manually intervene with Shift+Enter to buffer the thought. Experimental data show that this approach can reduce the cognitive stress of 23%.
Advanced tips: incorporate an interface color marking system (blue = original input, green = human editing, orange = AI supplementation) to create a visual cognitive map to further reduce the memory burden.
This answer comes from the articleCoT-Lab: an experimental dialog tool for exploring iterative thinking about human-computer collaborationThe
May not be reproduced without permission:AI productivity tools " How to Optimize the Cognitive Load Problem in Human-Computer Collaboration Using CoT-Lab?
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