Ethics Over Algorithms: What Really Drives Trust in AI-Assisted Anaesthesia? Research reveals

The rise of artificial intelligence (AI) in perioperative care is transforming anaesthesia practice—from predicting hypotension to supporting complex clinical decisions. But as AI tools become more common, are anaesthesiologists ethically and practically ready to trust and use them? A new national survey in the Indian Journal of Anaesthesia explores where clinicians stand on AI readiness and trust, revealing some surprising findings.

Background: Beyond Algorithms—The Human Side of AI

AI promises to enhance clinical vigilance, reduce errors, and optimize outcomes. Yet implementation is not just a technical hurdle. For safe, responsible use, clinicians must balance trust, oversight, and ethical judgment—especially when many AI systems remain “black boxes,” with recommendations that are hard to explain or challenge. Recent reviews highlight that informed consent, transparency, and clear lines of responsibility are as critical as technical accuracy.

Study Design: Surveying Indian Anaesthesia Professionals

Researchers conducted a cross-sectional, anonymous online survey of 255 anaesthesia professionals across Indian government, private, and corporate hospitals. Participants included junior and senior residents, consultants, and faculty, all with at least 6 months of perioperative experience. The survey measured five domains:

Knowledge: Understanding of AI concepts and tools

Utility and Trust: Perceived usefulness and willingness to use AI

Ethical Readiness: Comfort with explaining AI, balancing clinical judgment, and discussing risks

Transparency and Control: Concerns about explainability and clinician override

Institutional Support: Training, legal clarity, and access to AI platforms

A composite “AI Ethical Trust and Readiness Index” (AETRI) summarized overall preparedness.

Key Findings: Ethics and Transparency Outrank Technical Knowledge

Moderate Readiness: The mean AETRI was 57.2/100, reflecting moderate readiness for AI integration.

Ethical Readiness and Transparency Predict Trust: These two domains were the strongest predictors of AETRI, outweighing technical knowledge or confidence alone.

Knowledge Gaps: Faculty and consultants scored higher in AI knowledge than residents, but knowledge alone was not enough for overall readiness.

Low Institutional Support: Across all groups, the lowest scores were for institutional support—clinicians cited lack of access to validated AI tools, unclear legal frameworks, and insufficient training as top barriers.

Prior AI Exposure Not Enough: Previous exposure to AI (e.g., chatbots, conferences) did not translate into higher trust or readiness, highlighting the need for structured, context-specific training rather than passive experience.

Why This Matters: Implications for Practice and Policy

Building trust in AI systems means more than teaching clinicians about algorithms. It requires robust ethics training, transparent AI design, clear override mechanisms, and strong institutional and legal frameworks. Without these, even the most accurate AI tools may fail to gain traction in clinical practice.

Conclusion

For anaesthesia professionals, ethical readiness and transparency—not just technical know-how—are critical for safe and responsible AI integration. Institutions and policymakers should prioritize structured ethics education, transparent AI systems, and clear governance to support clinicians on the front lines of digital transformation.

KEY points

Ethical readiness and transparency are stronger predictors of AI trust than technical knowledge alone.

Most clinicians report moderate overall readiness but low institutional support for AI in anaesthesia.

Faculty and consultants have higher AI knowledge, but structured ethics-focused training is needed across all levels.

Prior exposure to AI tools does not guarantee preparedness for clinical integration.

National policies and clear governance are essential for safe and ethical AI adoption in perioperative care.

Citation:

Jamir T, Singh R, Gondode P, Aggarwal K, Nayak SS, Sirohiya P. Ethical readiness and trust in artificial intelligence–assisted anaesthesia: A cross-sectional survey study among anaesthesia professionals in India. Indian Journal of Anaesthesia. 2026;70(9):1019-25. DOI: 10.4103/ija.ija_106_26