The Real Space for Mental Models to Come In

The real space for mental models to come in is between the transition from raw data to information, where existing models heavily shape the categorization process. These mental models guide the filtering of data into information by determining which variables are relevant and how they interact. While linear models are proficient in analyzing past data due to their calibration, they lack future-oriented insights. In contrast, human input can provide anticipatory perspectives, especially in assessing design aesthetics or innovative features. The optimal approach lies in a balanced combination of linear models and human judgment, where discrepancies prompt further investigation to enhance predictive accuracy. Successful outcomes often result from a symbiotic relationship between linear models and human insights, leveraging diversity for comprehensive analysis.