Gender, Age, and Technology Education Influence the Adoption and Appropriation of LLMs
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Abstract (arXiv)
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.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Oct 2023.
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Citing papers per year: 2024: 3; 2025: 3; 2026: 3.
9 papers.
- 2024LLMs as Research Tools: A Large Scale Survey of Researchers' Usage and Perceptionscited by 45
- 2024MeMemo: On-device Retrieval Augmentation for Private and Personalized Text Generationcited by 12
- 2024The Generation Gap: Exploring Age Bias in the Value Systems of Large Language Modelscited by 5
- 2025Do Prompt Patterns Affect Code Quality? A First Empirical Assessment of ChatGPT-Generated Codecited by 4
- 2025Being Kind Isn't Always Being Safe: Diagnosing Affective Hallucination in LLMscited by 3
- 2025WebANNS: Fast and Efficient Approximate Nearest Neighbor Search in Web Browserscited by 1
- 2026Shopping with a Platform AI Assistant: Who Adopts, When in the Journey, and What Forcited by 0
- 2026How Early Adopters Used Generative AI Worldwide: Variation by Country Income and Languagecited by 0
- 2026AI Literacy: An Exercise in Power-Knowledgecited by 0
- 2026AI Literacy: An Exercise in Power-Knowledge30 Jul 2026
- 2026How Early Adopters Used Generative AI Worldwide: Variation by Country Income and Language29 May 2026
- 2026Shopping with a Platform AI Assistant: Who Adopts, When in the Journey, and What For26 Mar 2026
- 2025Being Kind Isn't Always Being Safe: Diagnosing Affective Hallucination in LLMs23 Aug 2025
- 2025WebANNS: Fast and Efficient Approximate Nearest Neighbor Search in Web Browsers1 Jul 2025
- 2025Do Prompt Patterns Affect Code Quality? A First Empirical Assessment of ChatGPT-Generated Code18 Apr 2025
- 2024LLMs as Research Tools: A Large Scale Survey of Researchers' Usage and Perceptions30 Oct 2024
- 2024MeMemo: On-device Retrieval Augmentation for Private and Personalized Text Generation2 Jul 2024
- 2024The Generation Gap: Exploring Age Bias in the Value Systems of Large Language Models12 Apr 2024