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Human-machine Interaction in the Age of Generative AI.

Dipesh Niraula1, Monique O Shotande, Issam El Naqa

  • 1Department of Machine Learning, Moffitt Cancer Center, Tampa, FL.

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|November 18, 2025
PubMed
Summary
This summary is machine-generated.

Generative artificial intelligence (Gen-AI) is transforming oncology by improving healthcare accessibility and efficiency. Thorough human-machine interaction (HMI) evaluation and a legal framework are crucial for patient safety and responsible AI deployment.

Keywords:
AI agentsHuman-machine interactionethicsfoundation modelsgenerative artificial intelligencehealth care AIhuman-AI interactionhuman-computer interactionliabilityoncology

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Area of Science:

  • Biomedicine
  • Oncology
  • Artificial Intelligence

Background:

  • Generative artificial intelligence (Gen-AI) is increasingly integrated into various fields, including oncology.
  • Gen-AI technologies are poised to fundamentally transform human-machine interaction (HMI).

Purpose of the Study:

  • To explore the transformative potential of Gen-AI in oncology and healthcare.
  • To highlight the importance of human-machine interaction (HMI) evaluation and legal frameworks for clinical AI.

Main Methods:

  • Review of Gen-AI applications in oncology.
  • Analysis of human-machine interaction (HMI) considerations.
  • Discussion of legal and ethical frameworks for AI in healthcare.

Main Results:

  • Gen-AI enables intuitive patient- and clinician-facing interfaces, enhancing healthcare accessibility, efficiency, and patient experience.
  • Limitations in data quality and algorithms pose challenges to patient safety.
  • A robust legal framework is essential for assigning liability and ensuring safe AI application.

Conclusions:

  • Gen-AI offers significant potential to optimize patient outcomes in oncology through improved clinical workflows and enhanced HMI.
  • Rigorous HMI evaluation beyond traditional validation is necessary.
  • Establishing clear legal liability is critical for the safe and beneficial adoption of clinical AI.