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The New Gravity: How Generative AI Remapped Innovation and What Academia Must Do Next (Preprint)

2025·0 ZitationenOpen Access
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5

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2025

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Abstract

<sec> <title>UNSTRUCTURED</title> Artificial intelligence is rapidly reshaping clinical research, diagnostics, and medical education, yet the center of gravity for AI innovation has shifted from academia to industry. This structural transition, driven by concentrated computational power, proprietary datasets, and the migration of AI expertise into private laboratories, creates a critical challenge for academic medical centers. Without a clearly defined role, academic institutions risk losing influence over the development, validation, and deployment of clinical AI systems. We propose that academic medical centers retain four responsibilities that industry cannot substitute. These include determining the biological mechanisms underlying AI predictions, integrating clinical, ethical, and sociotechnical perspectives, providing transparent and methodologically independent evaluation of clinical AI tools, and serving as stewards of ethical governance for patient populations that are systematically underrepresented in commercial datasets. These responsibilities are essential for protecting groups such as Medicaid beneficiaries, Medicare patients with complex multimorbidity, and recent immigrant communities whose data are rarely included in industry-held training corpora. Academic medical centers maintain longitudinal clinical datasets with deep phenotyping that are rarely matched in commercial environments. This Perspective presents a practical framework for academic medical centers to modernize medical education, strengthen institutional governance of AI, reinforce safeguards against conflicts of interest, and build equitable partnerships with industry and regulatory bodies. By anchoring clinical AI in scientific rigor, fairness, and public accountability, academic medicine can help ensure that the next era of medical innovation advances patient welfare rather than commercial interests. The future of safe and equitable AI-enabled healthcare depends on academic medical centers reaffirming and adapting their unique role at this pivotal moment. </sec>

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Artificial Intelligence in Healthcare and EducationMachine Learning in HealthcareBiomedical and Engineering Education
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