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Our research activities would be better served if they were communicated in a manner that is openly accessible to the public and all researchers. The research we share is often limited to representative data included in research papers—science would be much more efficient if all reproducible research data were shared alongside detailed methods and protocols, in the paradigm called Open Science. On the other hand, one primary function of research journals is to select manuscripts of good quality, verify the authenticity of the data and its impact, and deliver to the appropriate audience for critical evaluation and verification. In the current paradigm, where publication in a subset of journals is intimately linked to research evaluation, a hypercompetitive "market" has emerged where authors compete to access a limited number of top‐tier journals, leading to high rejection rates. Competition among publishers and scientific journals for market dominance resulted in an increase in both the number of journals and the cost of publishing and accessing scientific papers. Here we summarize the current problems and potential solutions from the development of AI technology discussed in the seminar at the 46th Annual Meeting of the Molecular Biology Society of Japan. [ABSTRACT FROM AUTHOR]