Gender, Age, and Technology Education Influence the Adoption and Appropriation of LLMs

Authors:
  • FDFiona Draxler
    Fiona Draxler
  • DBDaniel Buschek
    Daniel Buschek
  • MTMikke Tavast
    Mikke Tavast
  • PHPerttu Hämäläinen
    Perttu Hämäläinen
  • ASAlbrecht Schmidt
    Albrecht Schmidt
  • JKJuhi Kulshrestha
    Juhi Kulshrestha
  • RWRobin Welsch
    Robin Welsch
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Abstract
Large Language Models (LLMs) such as ChatGPT have become increasingly integrated into critical activities of daily life, raising concerns about equitable access and utilization across diverse demographics. This study investigates the usage of LLMs among 1,500 representative US citizens. Remarkably, 42% of participants reported utilizing an LLM. Our findings reveal a gender gap in LLM technology adoption (more male users than female users) with complex interaction patterns regarding age. Technology-related education eliminates the gender gap in our sample. Moreover, expert users are more likely than novices to list professional tasks as typical application scenarios, suggesting discrepancies in effective usage at the workplace. These results underscore the importance of providing education in artificial intelligence in our technology-driven society to promote equitable access to and benefits from LLMs. We urge for both international replication beyond the US and longitudinal observation of adoption.
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