Research on ChatGPT-4's predictive capabilities shows that employing narrative prompts significantly boosts the model's accuracy in forecasting events like the Academy Awards and macroeconomic variables. While it performs well in most areas, its predictions can become less reliable if subjected to excessive detail or critical information. This study highlights the dichotomy between direct predictions and narrative-based forecasts, suggesting that the latter may be more effective where public opinion plays a key role. Overall, the findings emphasize the importance of narrative context in enhancing predictive performance.
The study indicates that using narrative prompts significantly enhances the predictive accuracy of ChatGPT-4 compared to direct prediction methods across diverse fields.
Our findings suggest that while ChatGPT-4 can effectively forecast events like the Academy Awards, its predictive abilities may falter due to oversaturating the input data.
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