🤖 AI Summary
This study investigates the drivers behind the rise of preprint culture in artificial intelligence and human-computer interaction, and its structural implications for traditional scholarly publishing. Method: Employing qualitative research, we conducted semi-structured interviews with 15 domain scholars and applied thematic analysis to identify core perceptions and practice logics. Contribution/Results: For the first time, the study systematically reveals—through the lens of the scholarly community—the deep interplay between computational disciplines’ preprint practices and field-specific challenges: paper deluge, priority race, peer-review delays, and insufficient transparency. Findings indicate preprints primarily serve to mitigate publication lag, prevent idea appropriation, enhance visibility, and improve collaborative efficiency; their proliferation is actively reshaping publishing workflows. We propose a hybrid publishing ecosystem that balances speed, rigor, and equity—offering empirically grounded insights and theoretical foundations for rethinking scholarly communication in the digital age.
📝 Abstract
Preprinting has become a norm in fast-paced computing fields such as artificial intelligence (AI) and human-computer interaction (HCI). In this paper, we conducted semistructured interviews with 15 academics in these fields to reveal their motivations and perceptions of preprinting. The results found a close relationship between preprinting and characteristics of the fields, including the huge number of papers, competitiveness in career advancement, prevalence of scooping, and imperfect peer review system - preprinting comes to the rescue in one way or another for the participants. Based on the results, we reflect on the role of preprinting in subverting the traditional publication mode and outline possibilities of a better publication ecosystem. Our study contributes by inspecting the community aspects of preprinting practices through talking to academics.