Open and Sustainable AI: challenges, opportunities and the road ahead in the life sciences

• URL: http://arxiv.org/abs/2505.16619v1
• Date: Thu, 22 May 2025 12:52:34 GMT
• Title: Open and Sustainable AI: challenges, opportunities and the road ahead in the life sciences
• Authors: Gavin Farrell, Eleni Adamidi, Rafael Andrade Buono, Mihail Anton, Omar Abdelghani Attafi, Salvador Capella Gutierrez, Emidio Capriotti, Leyla Jael Castro, Davide Cirillo, Lisa Crossman, Christophe Dessimoz, Alexandros Dimopoulos, Raul Fernandez-Diaz, Styliani-Christina Fragkouli, Carole Goble, Wei Gu, John M. Hancock, Alireza Khanteymoori, Tom Lenaerts, Fabio G. Liberante, Peter Maccallum, Alexander Miguel Monzon, Magnus Palmblad, Lucy Poveda, Ovidiu Radulescu, Denis C. Shields, Shoaib Sufi, Thanasis Vergoulis, Fotis Psomopoulos, Silvio C. E. Tosatto,
• Abstract summary: We review the increased erosion of trust in AI research outputs, driven by the issues of poor reusability.<n>We discuss the fragmented components of the AI ecosystem and lack of guiding pathways to best support Open and Sustainable AI.<n>Our work connects researchers with relevant AI resources, facilitating the implementation of sustainable, reusable and transparent AI.
• Score: 50.9036832382286
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Artificial intelligence (AI) has recently seen transformative breakthroughs in the life sciences, expanding possibilities for researchers to interpret biological information at an unprecedented capacity, with novel applications and advances being made almost daily. In order to maximise return on the growing investments in AI-based life science research and accelerate this progress, it has become urgent to address the exacerbation of long-standing research challenges arising from the rapid adoption of AI methods. We review the increased erosion of trust in AI research outputs, driven by the issues of poor reusability and reproducibility, and highlight their consequent impact on environmental sustainability. Furthermore, we discuss the fragmented components of the AI ecosystem and lack of guiding pathways to best support Open and Sustainable AI (OSAI) model development. In response, this perspective introduces a practical set of OSAI recommendations directly mapped to over 300 components of the AI ecosystem. Our work connects researchers with relevant AI resources, facilitating the implementation of sustainable, reusable and transparent AI. Built upon life science community consensus and aligned to existing efforts, the outputs of this perspective are designed to aid the future development of policy and structured pathways for guiding AI implementation.

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