AI-driven discovery bottleneck: Scientific evidence trapped in a predigital system
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A new article highlights the need to modernize the scientific record, as the current paper-based model is hindering the progress of AI-driven discoveries. The article argues that a data-native ecosystem is necessary to bridge the gap between rapid AI innovation and slow formal validation.
Researchers are calling for a change in the way scientific discoveries are published. The current system is based on a 17th-century model that is slowing down the progress of AI-driven discoveries. A new data-native ecosystem is needed to bridge the gap between rapid AI innovation and slow formal validation. This would allow for more transparency and reproducibility in scientific research. The current system is also creating access and equity issues, with top-tier research universities spending millions on subscriptions and authors facing high processing charges. A new operating system for science is necessary to ensure rigorous reporting and transparency.
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