AI Knowledge and Reasoning: Emulating Expert Creativity in Scientific Research
arxiv(2024)
摘要
We investigate whether modern AI can emulate expert creativity in complex
scientific endeavors. We introduce novel methodology that utilizes original
research articles published after the AI's training cutoff, ensuring no prior
exposure, mitigating concerns of rote memorization and prior training. The AI
are tasked with redacting findings, predicting outcomes from redacted research,
and assessing prediction accuracy against reported results. Analysis on 589
published studies in four leading psychology journals over a 28-month period,
showcase the AI's proficiency in understanding specialized research, deductive
reasoning, and evaluating evidentiary alignment–cognitive hallmarks of human
subject matter expertise and creativity. These findings suggest the potential
of general-purpose AI to transform academia, with roles requiring
knowledge-based creativity become increasingly susceptible to technological
substitution.
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