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AI System Achieves Autonomous Scientific Discovery in Cognitive Psychology

Brisbane, Australia – In a significant leap towards truly autonomous scientific inquiry, researchers have developed an AI system that can independently conduct scientific research, from formulating hypotheses to publishing findings. The system, described in a new paper, successfully executed three distinct studies in cognitive psychology, generating complete manuscripts that were then evaluated by human experts.

This “Virtuous Machines: Towards Artificial General Science” system represents a major advancement beyond specialized AI tools like AlphaFold, which excel in narrow domains but require substantial human oversight. This new AI, however, is designed to navigate the entire scientific workflow. It can independently generate hypotheses, design experiments, collect data from human participants, analyze the results, and write up findings in a publishable format.

In their demonstration, the AI system independently conceived, designed, and executed three studies focusing on visual working memory, mental rotation, and imagery vividness. It managed the entire process, including recruiting 288 participants for an online study and analyzing a complex dataset. The system autonomously wrote three full manuscripts, which the researchers then subjected to expert review.

While the AI demonstrated impressive capabilities, achieving a methodological rigor comparable to experienced researchers, the human evaluation identified some limitations. The AI occasionally struggled with conceptual nuance and the interpretation of theoretical frameworks, sometimes presenting overly broad or overly cautious conclusions. These issues, the researchers note, are not entirely dissimilar to challenges encountered in human-authored scientific papers.

The research highlights the potential of AI to accelerate scientific discovery by automating laborious tasks and overcoming human cognitive limitations. The system’s ability to process vast amounts of information and meticulously follow scientific protocols could be particularly beneficial in complex, multi-stage research projects. The authors envision this AI as a powerful collaborative tool that can augment human researchers, freeing them to focus on creative aspects of science, such as problem formulation and ethical oversight.

This development marks a crucial step towards embodied AI that can interact with the real world, test hypotheses through experimentation, and autonomously explore scientific questions that might otherwise remain unanswered due to human constraints. The work also raises important questions about the nature of scientific understanding and how credit should be attributed in AI-assisted research. The researchers emphasize that while AI can emulate the structure of scientific reasoning, the nuanced judgment that comes from deep conceptual familiarity and years of experience remains a frontier for development.