Large Language Model (LLM) and economic thought. A simple experiment with Maffeo Pantaleoni

Despite due caution in the face of any new technology, we accept and support the idea that Large Language Models (LLMs) and their applications in economic research affect almost seven working categories of an economist: ideation and feedback, writing, background research, coding, data analysis, mathematical derivations, and research promotion (Korinek, 2024). Even in a different stage, these categories also matter to the historian of economic thought. Every researcher in the economic area faces the question of how advances in AI would affect their specific studies. The need for economists to rethink optimal research methodology is now imminent, and to do so quickly because the ability to be good researchers and perform particular tasks, thanks to AI, will have to improve dramatically shortly. Although the LLM used here will undoubtedly be obsolete by the time this work is printed – the theme is more of a working paper than a traditional book – as a group of scholars, we attempt to realize an initial technological transition by both testing the power of AI and giving it a slice of responsibility, in the belief that it will increase, rather than decrease, the quality and impact of our work. A book dedicated to the great Italian economist Maffeo Pantaleoni, one hundred years after his death, seems to us a somewhat unconventional but stimulating opportunity to test the effects of AI on our work as experts in computer engineering, economic history and public economics.