Can Technology Make Pathology More Human? Part 3

Our panel discusses AI accountability, user trust, and desirable outcomes

By
Helen Bristow
September 9, 2026
20 min

The Pathologist

Objective:

To discuss the ethics of integrating AI into pathology and the management of AI validation data.

Approach:

Expert Debate: Experts debate the balance between automation and human judgment in pathology, emphasizing the importance of trust between pathologists and AI.
Case Study: The discussion includes examples from primary care where AI tools assist without replacing clinical judgment.
Pathology Challenges: Pathologists face unique challenges due to their specialized knowledge, which complicates the integration of AI.
Trust and Data: Trust in AI tools is linked to understanding their development and validation, requiring pathologists to ask critical questions about AI performance.

Key Findings:

Trust between pathologists and AI will evolve over time as confidence in technology grows.
The gold standard in pathology remains the judgment of experienced pathologists.
Pathologists must determine which tasks can be delegated to AI while ensuring quality patient care.
Cognitive biases of pathologists can influence their interpretation of AI recommendations.
A formal due diligence framework is necessary for evaluating AI technologies in clinical use.

Interpretation:

The integration of AI in pathology requires careful consideration of human oversight, trust, and the unique challenges posed by the specialized nature of the field.

Limitations:

The complexity of pathology expertise makes it difficult to translate knowledge into AI systems.
Skepticism towards AI may shift to overconfidence as reliance on technology increases.