Human-machine Interaction in the Age of Generative AI

Generative artificial intelligence (Gen-AI) powered technologies are increasingly integrated across virtually all fields, including oncology, poised to fundamentally transform human-machine interaction (HMI). In biomedicine and oncology, Gen-AI tools are forming the foundation for intuitive patient-facing and clinician-facing interfaces that increase accessibility and efficiency of health care applications, enhance patient experience, and improve clinical workflows, ultimately optimizing patient outcomes. Despite Gen-AI's great potential in health care, limitations related to data quality and learning algorithms can create persistent challenges to patient safety, warranting a thorough HMI evaluation by end-users and experts that goes beyond traditional statistical validation. In parallel, a legal framework for assigning liability among developers, deployers, maintainers, and end-users is essential to ensure fairness and promote safe and beneficial application of clinical AI.

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Publication Details

Journal
The Cancer Journal
Published
2025-11-01
DOI
https://doi.org/10.1097/ppo.0000000000000797
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Human-machine Interaction in the Age of Generative AI

Dipesh Niraula, Issam El Naqa, Monique Shotande
The Cancer Journal
Artificial Intelligence in Healthcare and Education
article

Human-machine Interaction in the Age of Generative AI

Dipesh Niraula, Issam El Naqa, Monique Shotande
article en

Abstract

Generative artificial intelligence (Gen-AI) powered technologies are increasingly integrated across virtually all fields, including oncology, poised to fundamentally transform human-machine interaction (HMI). In biomedicine and oncology, Gen-AI tools are forming the foundation for intuitive patient-facing and clinician-facing interfaces that increase accessibility and efficiency of health care applications, enhance patient experience, and improve clinical workflows, ultimately optimizing patient outcomes. Despite Gen-AI's great potential in health care, limitations related to data quality and learning algorithms can create persistent challenges to patient safety, warranting a thorough HMI evaluation by end-users and experts that goes beyond traditional statistical validation. In parallel, a legal framework for assigning liability among developers, deployers, maintainers, and end-users is essential to ensure fairness and promote safe and beneficial application of clinical AI.

The Cancer JournalVol. 31(6)
Moffitt Cancer Center (US)
Openalex Percentile: Top 72%
Artificial Intelligence in Healthcare and Education
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Human-machine Interaction in the Age of Generative AI — Dipesh Niraula, Issam El Naqa, et al. · The Cancer Journal (2025) | TGRS Research Map | TGRS