Scientists say the system could be used to find ‘hidden gems’ of research and guide research funding allocations.
An artificial intelligence system trained on almost 40 years of the scientific literature correctly identified 19 out of 20 research papers that have had the greatest scientific impact on biotechnology – and has selected 50 recent papers it predicts will be among the ‘top 5%’ of biotechnology papers in the future.1
Scientists say the system could be used to find ‘hidden gems’ of research overlooked by other methods, and even to guide decisions on funding allocations so that it will be most likely to target promising research.
But it’s sparked outrage among some members of the scientific community, who claim it will entrench existing biases.
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