The lethal diamond of AI issue in critical care medicine: Great Power, Great Risk

The integration of artificial intelligence (AI) into critical care promises transformative advancements in diagnostics, treatment, and resource allocation. However, the realization of AI’s potential is hampered by critical gaps in data quality, ethical considerations, clinician education, and validation. This article introduces the “Lethal Diamond” framework, expanding on the traditional “Lethal Triad”, to encompass these interconnected challenges that threaten AI’s safe and effective deployment in high-stake critical care settings. It further proposes a shift from the reactive approach of “Garbage In, Garbage Out” (GIGO) to a proactive “Digging In, Diamonds Out” (DIDO) paradigm to cultivate excellence in AI implementation, ensuring AI systems enhance and augment, rather than undermine, healthcare delivery.

AI; Data quality; Ethical; Validation; GIGO; Healthcare; Anesthesia; Critical care; Machine learning; Medical education

[1] Pinsky MR, Bedoya A, Bihorac A, Celi L, Churpek M, Economou-Zavlanos NJ, et al. Use of artificial intelligence in critical care: opportunities and obstacles. Critical Care. 2024; 28: 113.

[2] Cai X, Wang X, Zhu Y, Yao Y, Chen J. Advances in automated anesthesia: a comprehensive review. Anesthesiology and Perioperative Science. 2025; 3: 3.

[3] Porcellato E, Lanera C, Ocagli H, Danielis M. Exploring applications of artificial intelligence in critical care nursing: a systematic review. Nursing Reports. 2025; 15: 55.

[4] Bellini V, Montomoli J, Bignami E. Poor quality data, privacy, lack of certifications: the lethal triad of new technologies in intensive care. Intensive Care Medicine. 2021; 47: 1052–1053.

[5] Cecconi M, Greco M, Shickel B, Angus DC, Bailey H, Bignami E, et al. Implementing artificial intelligence in critical care medicine: a consensus of 22. Critical Care. 2025; 29: 290.

[6] Cao Y, Wang Y, Liu H, Wu L. Artificial intelligence revolutionizing anesthesia management: advances and prospects in intelligent anesthesia technology. Frontiers in Medicine. 2025; 12: 1571725.

[7] Price WN, Zhang A. Legal and policy barriers to fairness in AI. In Dubber MD, Pasquale F, Das S (eds.) The Oxford handbook of ethics of AI (pp. 123–145). 1st edn. Oxford University Press: New York, NY. 2020.

[8] Berkhout WEM, van Wijngaarden JJ, Workum JD, van de Sande D, Hilling DE, Jung C, et al. Operationalization of artificial intelligence applications in the intensive care unit: a systematic review. JAMA Network Open. 2025; 8: e2522866.

[9] Official Journal of the European Union. Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024. 2024. Available at: http://data.europa.eu/eli/reg/2024/1689/oj (Accessed: 03 July 2025).

[10] Pham T. Ethical and legal considerations in healthcare AI: innovation and policy for safe and fair use. Royal Society Open Science. 2025; 12: 241873.

[11] Mennella C, Maniscalco U, De Pietro G, Esposito M. Ethical and regulatory challenges of AI technologies in healthcare: a narrative review. Heliyon. 2024; 10: e26297.

[12] World Health Organization. Ethics and governance of artificial intelligence for health. 2021. Available at: https://www.who.int/publications/i/item/9789240029200 (Accessed: 05 July 2025).

[13] Montomoli J, Bitondo MM, Cascella M, Rezoagli E, Romeo L, Bellini V, et al. Algor-ethics: charting the ethical path for AI in critical care. Journal of Clinical Monitoring and Computing. 2024; 38: 931–939.

[14] Tolentino R, Baradaran A, Gore G, Pluye P, Abbasgholizadeh-Rahimi S. Curriculum frameworks and educational programs in AI for medical students, residents, and practicing physicians: scoping review. JMIR Medical Education. 2024; 10: e54793.

[15] Valikodath NG, Cole E, Ting DSW, Campbell JP, Pasquale LR, Chiang MF, et al.; American Academy of Ophthalmology Task Force on Artificial Intelligence. Impact of artificial intelligence on medical education in ophthalmology. Translational Vision Science & Technology. 2021; 10: 14.

[16] European Commission. AI talent, skills and literacy. 2024. Available at: https://digital-strategy.ec.europa.eu/en/policies/ai-talent-skills-and-literacy (Accessed: 15 January 2025).

[17] US Food and Drug Administration. Digital Health Software Precertification (Pre-Cert) Pilot Program. 2024. Available at: https://www.fda.gov/medical-devices/digital-health-center-excellence/digital-health-software-precertification-pre-cert-pilot-program (Accessed: 15 January 2025).

[18] UK Government. AI airlock: the regulatory sandbox for AIaMD. 2024. Available at: https://www.gov.uk/government/collections/ai-airlock-the-regulatory-sandbox-for-aiamd (Accessed: 15 January 2025).

[19] Elendu C, Amaechi DC, Elendu TC, Jingwa KA, Okoye OK, John Okah M, et al. Ethical implications of AI and robotics in healthcare: a review. Medicine. 2023; 102: e36671.

[20] Nauka PC, Kennedy JN, Brant EB, Komorowski M, Pirracchio R, Angus DC, et al. Challenges with reinforcement learning model transportability for sepsis treatment in emergency care. NPJ Digital Medicine. 2025; 8: 91.

[21] Lin C, Liu WT, Chang CH, Lee CC, Hsing SH, Fang WH, et al. Artificial intelligence–powered rapid identification of ST-elevation myocardial infarction via electrocardiogram (ARISE)—a pragmatic randomized controlled trial. NEJM AI. 2024; 1: AIoa2400190.

[22] Boussina A, Shashikumar SP, Malhotra A, Owens RL, El-Kareh R, Longhurst CA, et al. Impact of a deep learning sepsis prediction model on quality of care and survival. NPJ Digital Medicine. 2024; 7: 14.

[23] Tierney AA, Gayre G, Hoberman B, Mattern B, Ballesca M, Hannay SBW, et al. Ambient artificial intelligence scribes: learnings after 1 year and over 2.5 million uses. NEJM Catalyst Innovations in Care Delivery. 2025; 6: CAT.25.0040.

[24] European Data Protection Board. Opinion 28/2024 on certain data protection aspects related to the processing of personal data in the context of AI models. 2024. Available at: https://www.edpb.europa.eu/our-work-tools/our-documents/opinion-board-art-64/opinion-282024-certain-data-protection-aspects_en (Accessed: 15 January 2025).