AI Receptivity or AI Adoption Breadth? A Tool-Specific Reanalysis of the Lower-Literacy/Higher-Usage Link
arXiv:2606.13734v1 Announce Type: new Abstract: Recent evidence reported by Tully, Longoni, and Appel (2025) suggests that lower artificial intelligence (AI) literacy predicts greater receptivity toward AI. We revisit this claim using the public data from Study 3 of that article, which measures past usage of five AI tool categories on a five-point frequency scale. We first reproduce the negative association between AI literacy and aggregate AI usage using OLS on participant-level averages, binary logit, ordered logit, and multinomial logit specifications. We then show that the aggregate relati
This research is a re-examination of a widely cited claim from 2025, offering a more nuanced understanding of AI receptivity and adoption as AI tools become more prevalent.
Understanding how AI literacy influences adoption and receptivity is crucial for policymakers, educators, and developers to design effective AI integration strategies and mitigate potential societal divides.
The prior assumption that lower AI literacy directly predicts greater receptivity is refined, suggesting that it might be more about breadth of usage for specific tools rather than overall receptivity.
- · AI ethicists
- · Educators developing AI literacy programs
- · AI tool developers focusing on user experience
- · Companies with complex, non-intuitive AI interfaces
- · Researchers making broad claims about AI receptivity without tool-specific analy
The reanalysis provides a more granular view of AI adoption patterns across different user groups.
This improved understanding could lead to more targeted AI education and development, addressing specific user needs and literacy gaps.
Over time, this might contribute to the design of AI systems that are more democratically adopted and less likely to exacerbate digital divides based on perceived literacy.
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Read at arXiv cs.AI