Literary characters and GPT-4: from William Shakespeare to Elena Ferrante. - Abrams, Gabriel (Digital Scholarship in the Humanities, 2025)
We prompted GPT-4 (a large language model) to play the Dictator game, a classic behavioral economics experiment, as 148 literary fictional characters from the 17th century to the 21st century. There is a general and mainly monotonic decrease in selfish behavior over time in literary characters. Fifty per cent of the decisions of characters from the 17th century are selfish compared to just 19 per cent from the 21st century. Historical literary characters have a surprisingly strong net positive valence across 2,785 personality traits generated by GPT-4 (3.2× more positive than negative). However, valence varied significantly across centuries. Positive traits were 10× more common than negative in the 21st century, but just 1.8× more common in the 17th century. 'Empathetic', 'fair', and 'selfless', were the most overweight traits in the 20th century. Conversely, 'manipulative', 'ambitious', and 'ruthless' were the most overweight traits in the 17th century. Male characters were more selfish than female characters. The skew was highest in the 17th century, where selfish decisions for male and female were 62 and 20 per cent, respectively. This analysis also offers a quantifiable partial Turing test. The key human-like characteristics of the model are the zero price effect, lack of spitefulness, and altruism. However, the model does not have human sensitivity to relative ordinal position and has significantly lower price elasticity than humans.