{"ID":2857712,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.15951","arxiv_id":"2510.15951","title":"Attention to Non-Adopters","abstract":"Although language model-based chat systems are increasingly used in daily life, most Americans remain non-adopters of chat-based LLMs -- as of June 2025, 66% had never used ChatGPT. At the same time, LLM development and evaluation rely mainly on data from adopters (e.g., logs, preference data), focusing on the needs and tasks for a limited demographic group of adopters in terms of geographic location, education, and gender. In this position paper, we argue that incorporating non-adopter perspectives is essential for developing broadly useful and capable LLMs. We contend that relying on methods that focus primarily on adopters will risk missing a range of tasks and needs prioritized by non-adopters, entrenching inequalities in who benefits from LLMs, and creating oversights in model development and evaluation. To illustrate this claim, we conduct case studies with non-adopters and show: how non-adopter needs diverge from those of current users, how non-adopter needs point us towards novel reasoning tasks, and how to systematically integrate non-adopter needs via human-centered methods.","short_abstract":"Although language model-based chat systems are increasingly used in daily life, most Americans remain non-adopters of chat-based LLMs -- as of June 2025, 66% had never used ChatGPT. At the same time, LLM development and evaluation rely mainly on data from adopters (e.g., logs, preference data), focusing on the needs an...","url_abs":"https://arxiv.org/abs/2510.15951","url_pdf":"https://arxiv.org/pdf/2510.15951v1","authors":"[\"Kaitlyn Zhou\",\"Kristina Gligorić\",\"Myra Cheng\",\"Michelle S. Lam\",\"Vyoma Raman\",\"Boluwatife Aminu\",\"Caeley Woo\",\"Michael Brockman\",\"Hannah Cha\",\"Dan Jurafsky\"]","published":"2025-10-10T18:00:40Z","proceeding":"cs.CY","tasks":"[\"cs.CY\",\"cs.CL\",\"cs.HC\",\"cs.LG\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}