Building Trust in Artificial Intelligence for Healthcare: Lessons from Clinical Oncology

A new review, published in the peer-reviewed journal AI in Precision Oncology, explores the multifaceted reasons behind the skepticism surrounding artificial intelligence (AI) technologies in healthcare and advocates for approaches to build confidence in AI applications.

David Waterhouse, MD, MPH, from Chief Innovation Officer of Oncology Hematology Care, and an Editorial Board Member of AI in Precision Oncology, Terence Cooney-Waterhouse, from VandHus LLC, and coauthors, emphasize the importance of trust as a prerequisite for successful integration of AI into clinical practice.

Despite recognizing the potential benefits of AI, patients express significant concerns about data privacy, algorithmic bias, and the lack of transparency in AI decision-making processes. Physicians tend to be driven by doubts about the clinical validation and interpretability of AI systems.

To build confidence in AI applications, the authors advocate "for the implementation of robust data governance frameworks, enhanced transparency, and active involvement of stakeholders in AI development." They underscore "the necessity of addressing ethical implications and ensuring equitable access to AI-driven innovations."

"Integrating artificial intelligence into oncology care is much like introducing a new colleague to an established clinical team. Just as we wouldn't immediately trust a new team member with critical decisions without proper vetting, training, and transparency, we must approach AI implementation with similar rigor and care. Trust isn't granted - it's earned through demonstrated reliability, transparent processes, and consistent results. By prioritizing ethical frameworks, clinical validation, and patient-centered approaches, we can transform AI from a misunderstood technological tool into a trusted ally in the fight against cancer," says Douglas Flora, MD, Editor-in-Chief of AI in Precision Oncology.

Cooney-Waterhouse T, Ou W, Mukherji S, Frytak J, Saha P, Waterhouse D.
Bridging the Trust Gap in Artificial Intelligence for Health care: Lessons from Clinical Oncology.
AI in Precision Oncology, 2025. doi: 10.1089/aipo.2025.0001

Most Popular Now

Do Fitness Apps do More Harm than Good?

A study published in the British Journal of Health Psychology reveals the negative behavioral and psychological consequences of commercial fitness apps reported by users on social media. These impacts may...

AI Tool Beats Humans at Detecting Parasi…

Scientists at ARUP Laboratories have developed an artificial intelligence (AI) tool that detects intestinal parasites in stool samples more quickly and accurately than traditional methods, potentially transforming how labs diagnose...

Making Cancer Vaccines More Personal

In a new study, University of Arizona researchers created a model for cutaneous squamous cell carcinoma, a type of skin cancer, and identified two mutated tumor proteins, or neoantigens, that...

AI can Better Predict Future Risk for He…

A landmark study led by University' experts has shown that artificial intelligence can better predict how doctors should treat patients following a heart attack. The study, conducted by an international...

A New AI Model Improves the Prediction o…

Breast cancer is the most commonly diagnosed form of cancer in the world among women, with more than 2.3 million cases a year, and continues to be one of the...

AI System Finds Crucial Clues for Diagno…

Doctors often must make critical decisions in minutes, relying on incomplete information. While electronic health records contain vast amounts of patient data, much of it remains difficult to interpret quickly...