Ethical Considerations in the Use of Artificial Intelligence in Pain Medicine.

Marco Cascella, Mohammed Naveed Shariff, Omar Viswanath, Matteo Luigi Giuseppe Leoni, Giustino Varrassi
Author Information
  1. Marco Cascella: Anesthesia and Pain Medicine, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, Via S. Allende, Baronissi, 84081, Italy. mcascella@unisa.it.
  2. Mohammed Naveed Shariff: Department of AI&DS, Rajalakshmi Institute of Technology, Chennai, Tamil Nadu, India.
  3. Omar Viswanath: Department of Anesthesiology, Creighton University School of Medicine, Phoenix, AZ, USA.
  4. Matteo Luigi Giuseppe Leoni: Department of Medical and Surgical Sciences and Translational Medicine, Sapienza University of Roma, Roma, Italy.
  5. Giustino Varrassi: Fondazione Paolo Procacci, Roma, 00193, Italy.

Abstract

Although the integration of artificial intelligence (AI) into medicine and healthcare holds transformative potential, significant challenges must be necessarily addressed. This technological innovation requires a commitment to ethical principles. Key issues concern autonomy, reliability, and bias. Furthermore, AI development must guarantee rigorous data privacy and security standards. Effective AI implementation demands thorough validation, transparency, and the involvement of multidisciplinary teams to oversee ethical considerations. These issues also concern pain medicine where careful assessment of subjective experiences and individualized care are crucial. Notably, in this rapidly evolving technological landscape, politics plays a pivotal role in establishing rules and regulations. Regulatory frameworks, such as the European Union's Artificial Intelligence Act and recent U.S. executive orders, provide essential guidelines for the responsible use of AI. This step is crucial for balancing innovation with rigorous ethical standards, ultimately leveraging the incredible AI's benefits. As the field evolves rapidly and concepts like algorethics and data ethics become more widespread, the scientific community is increasingly recognizing the need for specialists in this area, such as AI Ethics Specialists.

Keywords

References

Xu Y, Liu X, Cao X, Huang C, Liu E, Qian S, Liu X, Wu Y, Dong F, Qiu CW, Qiu J, Hua K, Su W, Wu J, Xu H, Han Y, Fu C, Yin Z, Liu M, Roepman R, Dietmann S, Virta M, Kengara F, Zhang Z, Zhang L, Zhao T, Dai J, Yang J, Lan L, Luo M, Liu Z, An T, Zhang B, He X, Cong S, Liu X, Zhang W, Lewis JP, Tiedje JM, Wang Q, An Z, Wang F, Zhang L, Huang T, Lu C, Cai Z, Wang F, Zhang J. Artificial intelligence: a powerful paradigm for scientific research. Innov (Camb). 2021;2(4):100179. https://doi.org/10.1016/j.xinn.2021.100179 . [DOI: 10.1016/j.xinn.2021.100179]
Laupichler MC, Aster A, Schirch J, Raupach T. Artificial intelligence literacy in higher and adult education: a scoping literature review. Computers Education: Artif Intell. 2022;3:100101. https://doi.org/10.1016/j.caeai.2022.100101 . [DOI: 10.1016/j.caeai.2022.100101]
Alowais SA, Alghamdi SS, Alsuhebany N, Alqahtani T, Alshaya AI, Almohareb SN, Aldairem A, Alrashed M, Bin Saleh K, Badreldin HA, Al Yami MS, Al Harbi S, Albekairy AM. Revolutionizing healthcare: the role of artificial intelligence in clinical practice. BMC Med Educ. 2023;23(1):689. https://doi.org/10.1186/s12909-023-04698-z . [DOI: 10.1186/s12909-023-04698-z]
Chua IS, Gaziel-Yablowitz M, Korach ZT, Kehl KL, Levitan NA, Arriaga YE, Jackson GP, Bates DW, Hassett M. Artificial intelligence in oncology: path to implementation. Cancer Med. 2021;10(12):4138–49. https://doi.org/10.1002/cam4.3935 . [DOI: 10.1002/cam4.3935]
Manson EN, Hasford F, Trauernicht C, Ige TA, Inkoom S, Inyang S, Samba O, Khelassi-Toutaoui N, Lazarus G, Sosu EK, Pokoo-Aikins M, Stoeva M. Africa’s readiness for artificial intelligence in clinical radiotherapy delivery: medical physicists to lead the way. Phys Med. 2023;113:102653. https://doi.org/10.1016/j.ejmp.2023.102653 . [DOI: 10.1016/j.ejmp.2023.102653]
Seager A, Sharp L, Neilson LJ, Brand A, Hampton JS, Lee TJW, Evans R, Vale L, Whelpton J, Bestwick N, Rees CJ, COLO-DETECT trial team. Polyp detection with colonoscopy assisted by the GI genius artificial intelligence endoscopy module compared with standard colonoscopy in routine colonoscopy practice (COLO-DETECT): a multicentre, open-label, parallel-arm, pragmatic randomised controlled trial. Lancet Gastroenterol Hepatol. 2024;S2468–1253(2400161–4). https://doi.org/10.1016/S2468-1253(24)00161-4 .
Li YH, Li YL, Wei MY, Li GY. Innovation and challenges of artificial intelligence technology in personalized healthcare. Sci Rep. 2024;14(1):18994. https://doi.org/10.1038/s41598-024-70073-7 . [DOI: 10.1038/s41598-024-70073-7]
Arzamasov K, Vasilev Y, Zelenova M, Pestrenin L, Busygina Y, Bobrovskaya T, Chetverikov S, Shikhmuradov D, Pankratov A, Kirpichev Y, Sinitsyn V, Son I, Omelyanskaya O. Independent evaluation of the accuracy of 5 artificial intelligence software for detecting lung nodules on chest X-rays. Quant Imaging Med Surg. 2024;14(8):5288–303. https://doi.org/10.21037/qims-24-160 . [DOI: 10.21037/qims-24-160]
Dasgupta P, Hemal A, Preminger G, Sur R. The rise of AI in endourology and robotic surgery. J Endourol. 2024;38(8):711. https://doi.org/10.1089/end.2024.32789.pd . [DOI: 10.1089/end.2024.32789.pd]
Wangpitipanit S, Lininger J, Anderson N. Exploring the deep learning of artificial intelligence in nursing: a concept analysis with Walker and Avant’s approach. BMC Nurs. 2024;23(1):529. https://doi.org/10.1186/s12912-024-02170-x . [DOI: 10.1186/s12912-024-02170-x]
Khan MA, Koh RGL, Rashidiani S, Liu T, Tucci V, Kumbhare D, Doyle TE. Cracking the Chronic Pain code: a scoping review of Artificial Intelligence in Chronic Pain research. Artif Intell Med. 2024;151:102849. https://doi.org/10.1016/j.artmed.2024.102849 . [DOI: 10.1016/j.artmed.2024.102849]
Cascella M, Schiavo D, Cuomo A, Ottaiano A, Perri F, Patrone R, Migliarelli S, Bignami EG, Vittori A, Cutugno F. Artificial Intelligence for Automatic Pain Assessment: Research methods and perspectives. Pain Res Manag. 2023;2023:6018736. https://doi.org/10.1155/2023/6018736 . [DOI: 10.1155/2023/6018736]
El-Tallawy SN, Pergolizzi JV, Vasiliu-Feltes I, Ahmed RS, LeQuang JK, Alzahrani T, Varrassi G, Awaleh FI, Alsubaie AT, Nagiub MS. Innovative applications of Telemedicine and Other Digital Health Solutions in Pain Management: A literature review. Pain Ther. 2024;13(4):791–812. https://doi.org/10.1007/s40122-024-00620-7 . [DOI: 10.1007/s40122-024-00620-7]
Ranger M, Glinas C. Innovating in pain assessment of the critically ill: exploring cerebral near-infrared spectroscopy as a bedside approach. Pain Manage Nurs. 2014;15(2):519–29. [DOI: 10.1016/j.pmn.2012.03.005]
Zamzmi G, Kasturi R, Goldgof D, Zhi R, Ashmeade T, Sun Y. A review of Automated Pain Assessment in infants: features, classification tasks, and databases. IEEE Rev Biomed Eng. 2018;11:77–96. https://doi.org/10.1109/RBME.2017.2777907 . [DOI: 10.1109/RBME.2017.2777907]
Sarker IH. AI-Based modeling: techniques, applications and Research issues towards automation, Intelligent and Smart systems. SN Comput Sci. 2022;3(2):158. https://doi.org/10.1007/s42979-022-01043-x . [DOI: 10.1007/s42979-022-01043-x]
An Q, Rahman S, Zhou J, Kang JJ. A Comprehensive Review on Machine Learning in Healthcare Industry: classification, restrictions, opportunities and challenges. Sens (Basel). 2023;23(9):4178. https://doi.org/10.3390/s23094178 . [DOI: 10.3390/s23094178]
Cascella M, Semeraro F, Montomoli J, Bellini V, Piazza O, Bignami E. The breakthrough of large Language models Release for Medical Applications: 1-Year Timeline and perspectives. J Med Syst. 2024;48(1):22. https://doi.org/10.1007/s10916-024-02045-3 . [DOI: 10.1007/s10916-024-02045-3]
Hutson M. Will superintelligent AI sneak up on us? New study offers reassurance. Nature. 2024;625(7994):223. https://doi.org/10.1038/d41586-023-04094-z . [DOI: 10.1038/d41586-023-04094-z]
Bellini V, Cascella M, Cutugno F, Russo M, Lanza R, Compagnone C, Bignami EG. Understanding basic principles of Artificial Intelligence: a practical guide for intensivists. Acta Biomed. 2022;93(5):e2022297. https://doi.org/10.23750/abm.v93i5.13626 . [DOI: 10.23750/abm.v93i5.13626]
Montomoli J, Bitondo MM, Cascella M, Rezoagli E, Romeo L, Bellini V, Semeraro F, Gamberini E, Frontoni E, Agnoletti V, Altini M, Benanti P, Bignami EG. Algor-ethics: charting the ethical path for AI in critical care. J Clin Monit Comput. 2024. https://doi.org/10.1007/s10877-024-01157-y . [DOI: 10.1007/s10877-024-01157-y]
Bignami E, Montomoli J, Bellini V, Cascella M. Uncovering the power of synergy: a hybrid human-machine model for maximizing AI properties and human expertise. Crit Care. 2023;27(1):330. https://doi.org/10.1186/s13054-023-04598-0 . [DOI: 10.1186/s13054-023-04598-0]
Benanti P. The urgency of an algorethics. Discov Artif Intell. 2023;3:11. https://doi.org/10.1007/s44163-023-00056-6 .
Allen C, Wallach W, Smit I. Why machine ethics? IEEE Intell Syst. 2006;21(4):12–7. [DOI: 10.1109/MIS.2006.83]
Cascella M, Montomoli J, Bellini V, Vittori A, Biancuzzi H, Dal Mas F, Bignami EG. Crossing the AI Chasm in Neurocritical Care. Computers. 2023;12(4):83. https://doi.org/10.3390/computers12040083 . [DOI: 10.3390/computers12040083]
Floridi L, Taddeo M. What is data ethics? Philos Trans Math Phys Eng Sci. 2016;374(2083):20160360. https://doi.org/10.1098/rsta.2016.0360 . [DOI: 10.1098/rsta.2016.0360]
Health Insurance Portability and Accountability Act of 1996 (HIPAA). Available online: https://www.cdc.gov/phlp/php/resources/health-insurance-portability-and-accountability-act-of-1996-hipaa.html?CDC_AAref_Val=https://www.cdc.gov/phlp/publications/topic/hipaa.html (Last retrieved: June 23, 2024).
McGregor S. (2016) An incident database. Incident number 6. Available: https://incidentdatabase.ai/cite/6 . (Last retrieved: July 24, 2024).
Gomutbutra P, Kittisares A, Sanguansri A, Choosri N, Sawaddiruk P, Fakfum P, Lerttrakarnnon P, Saralamba S. Classification of elderly pain severity from automated video clip facial action unit analysis: a study from a Thai data repository. Front Artif Intell. 2022;5:942248. https://doi.org/10.3389/frai.2022.942248 . [DOI: 10.3389/frai.2022.942248]
Cascella M, Tracey MC, Petrucci E, Bignami EG. Exploring Artificial Intelligence in Anesthesia: a primer on Ethics, and clinical applications. Surgeries. 2023;4(2):264–74. https://doi.org/10.3390/surgeries4020027 . [DOI: 10.3390/surgeries4020027]
Collins GS, Dhiman P, Andaur Navarro CL, et al. Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence. BMJ Open. 2021;11(7):e048008. [DOI: 10.1136/bmjopen-2020-048008]
Zednik C. Solving the black box problem: a normative framework for explainable artificial intelligence. Philos Technol. 2021;34:265–88. [DOI: 10.1007/s13347-019-00382-7]
Marcus E, Teuwen J. Artificial intelligence and explanation: how, why, and when to explain black boxes. Eur J Radiol. 2024;173:111393. https://doi.org/10.1016/j.ejrad.2024.111393 . [DOI: 10.1016/j.ejrad.2024.111393]
Shafiabady N, Hadjinicolaou N, Hettikankanamage N, MohammadiSavadkoohi E, Wu RMX, Vakilian J. eXplainable Artificial Intelligence (XAI) for improving organisational regility. PLoS ONE. 2024;19(4):e0301429. https://doi.org/10.1371/journal.pone.0301429 . [DOI: 10.1371/journal.pone.0301429]
Räz T, Beisbart C. The importance of understanding deep learning. Erkenn. 2024;89:1823–40. https://doi.org/10.1007/s10670-022-00605-y . 8oi:. [DOI: 10.1007/s10670-022-00605-y]
Tagaris T, Sdraka. M, Stafylopatis A, High-Resolution Class Activation M. 2019 IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan, 2019, pp. 4514–4518. https://doi.org/10.1109/ICIP.2019.8803474
Ali S, Akhlaq F, Imran AS, Kastrati Z, Daudpota SM, Moosa M. The enlightening role of explainable artificial intelligence in medical & healthcare domains: a systematic literature review. Comput Biol Med. 2023;166:107555. https://doi.org/10.1016/j.compbiomed.2023.107555 . [DOI: 10.1016/j.compbiomed.2023.107555]
Cascella M, Laudani A, Scarpati G, Piazza O. Ethical issues in pain and palliation. Curr Opin Anaesthesiol. 2024;37(2):199–204. https://doi.org/10.1097/ACO.0000000000001345 . [DOI: 10.1097/ACO.0000000000001345]
Soin A, Hirschbeck M, Verdon M, Manchikanti L. A pilot study implementing a machine learning algorithm to Use Artificial Intelligence to diagnose spinal conditions. Pain Physician. 2022;25(2):171–8. [PMID: 35322974]
Andres JE, Ten-Esteve A, Harutyunyan A, et al. Predictive clinical decision system using machine learning and imaging biomarkers in patients with neurostimulation therapy: a pilot study. Pain Physician. 2021;24:E1279–90. [PMID: 34793655]
Piette JD, Newman S, Krein SL, Marinec N, Chen J, Williams DA, Edmond SN, Driscoll M, LaChappelle KM, Kerns RD, Maly M, Kim HM, Farris KB, Higgins DM, Buta E, Heapy AA. Patient-centered Pain Care using Artificial Intelligence and Mobile Health tools: a randomized comparative effectiveness trial. JAMA Intern Med. 2022;182(9):975–83. https://doi.org/10.1001/jamainternmed.2022.3178 . [DOI: 10.1001/jamainternmed.2022.3178]
Saheb T, Saheb T. Topical review of artificial intelligence national policies: a mixed method analysis. Technol Soc. 2023;102316. https://doi.org/10.1016/j.techsoc.2023.102316 .
European Parliament. Artificial Intelligence Act. Available at: https://ai-act-law.eu/ (Last retrieved: July 20, 2024).
The White House. Executive order on the safe secure and trustworthy development and use of artificial intelligence. Available at: https://www.whitehouse.gov/briefing-room/presidential-actions/2023/10/30/executive-order-on-the-safe-secure-and-trustworthy-development-and-use-of-artificial-intelligence/ . (Last retrieved: July 29, 2024).
Huang C, Zhang Z, Mao B, Yao X. An overview of Artificial Intelligence Ethics. IEEE Trans Artif Intell. 2023;4(4):799–819. https://doi.org/10.1109/TAI.2022.3194503 . [DOI: 10.1109/TAI.2022.3194503]
Elendu C, Amaechi DC, Elendu TC, Jingwa KA, Okoye OK, John Okah M, Ladele JA, Farah AH, Alimi HA. Ethical implications of AI and robotics in healthcare: a review. Med (Baltim). 2023;102(50):e36671. https://doi.org/10.1097/MD.0000000000036671 . [DOI: 10.1097/MD.0000000000036671]

MeSH Term

Artificial Intelligence
Humans
Pain Management

Word Cloud

Similar Articles

Cited By