AI Aids and Abets Science, But Beware Putting Too Much Stock in Its Objectivity
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Machine learning models are increasingly being used in scientific research to aid discoveries, but attributing too much authority and trust to AI systems poses risks.
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Scientists are exploring using AI as surrogates for human participants, to synthesize research, to process huge datasets, and to evaluate studies.
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Overreliance on AI risks creating "monocultures" where certain questions and perspectives dominate, leading to illusions about the breadth and objectivity of research.
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Mitigation strategies involve transparency about AI funding/motivations, protecting diverse research approaches, and questioning narratives of technological inevitability.
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Keeping human perspectives vital in science is important; being skeptical of AI doesn't require being anti-AI.