Regulatory and Ethical Considerations on Artificial Intelligence for Occupational Medicine
Contenuto principale dell'articolo
Keywords
Abstract
Generative artificial intelligence and Large Language Models are reshaping labor dynamics and occupational health practices. As AI continues to evolve, there's a critical need to customize ethical considerations for its specific impacts on occupational health. Recognizing potential ethical challenges and dilemmas, stakeholders and physicians are urged to proactively adjust the practice of occupational medicine in response to shifting ethical paradigms. By advocating for a comprehensive review of the International Commission on Occupational Health ICOH code of Ethics, we can ensure responsible medical AI deployment, safeguarding the well-being of workers amidst the transformative effects of automation in healthcare.
Riferimenti bibliografici
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21. Blobel B, Kalra D. Editorial: Managing healthcare transformation towards P5 medicine. Front Med (Lau-sanne). 2023 Aug 25;10:1244100. Doi: 10.3389/fmed.2023.1244100. PMID: 37692783; PMCID: PMC10485846
22. Kamel Boulos MN, Zhang P. Digital Twins: From Personalised Medicine to Precision Public Health. J Pers Med 2021; 11(8):745. Doi: https://doi.org/10.3390/jpm11080745
23. Armeni P, Polat I, Maria De Rossi L. (2023). Digital Twins for Health: Opportunities, Barriers and a Path For-ward. IntechOpen. Doi: 10.5772/intechopen.112490
24. Shoja MM, Van de Ridder JMM, Rajput V. The Emerging Role of Generative Artificial Intelligence in Medical Education, Research, and Practice. Cureus. 2023 Jun 24;15(6):e40883. Doi: 10.7759/cureus.40883. PMID: 37492829; PMCID: PMC10363933).
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26. Lee, Peter et al. “Benefits, Limits, and Risks of GPT-4 as an AI Chatbot for Medicine. Reply.” New Eng J Med vol. 388,25 (2023): 2400. Doi: 10.1056/NEJMc2305286)
27. Thirunavukarasu AJ, Ting DSJ, Elangovan K, Gutierrez L, Tan TF, Ting DSW. Large language models in medi-cine. Nat Med. 2023;29(8). Doi: 10.1038/s41591-023-02448-8).
28. Naveed H, Khan AU, Qiu, S, et al. A Comprehensive Overview of Large Language Models. arXiv 2023, arXiv:2307.06435
29. Chakraborty, Chiranjib et al. “Overview of Chatbots with special emphasis on artificial intelligence-enabled ChatGPT in medical science.” Front Artif Intell vol. 6 1237704. 31 Oct. 2023, Doi: 10.3389/frai.2023.1237704
30. Sridi C, Brigui S. The use of ChatGPT in Occupational Medicine: opportunities and threats. Ann Occup Environ Med. 2023 Oct 23;35:e42. Doi: 10.35371/aoem.2023.35.e42. PMID: 38029273; PMCID: PMC10654530)
31. Padovan M, Cosci B, Petillo A, et al. ChatGPT in Occupational Medicine: A Comparative Study with Human Experts. Bioengineering. 2024; 11(1):57.Doi: https://doi.org/10.3390/bioengineering11010057
32. Ji Z, Lee N, Frieske R, et al. Survey of hallucination in natural language generation. ACM Comput. Surv. 2023,55, 1–38.
33. Mutti A. Hey James, Write an Editorial for “La Medicina del Lavoro”. Med Lav. 2023;114(2):e2023014. Doi: 10.23749/mdl.v114i2.14451. Epub 2023 Apr 13. PMCID: PMC10133773
34. Menz BD, Modi ND, Sorich MJ, Hopkins AM. Health Disinformation Use Case Highlighting the Urgent Need for Artificial Intelligence Vigilance: Weapons of Mass Disinformation. JAMA Intern Med. 2024;184(1):92–96. Doi: 10.1001/jamainternmed.2023.5947
35. EU-OSHA (European Agency for Safety and Health at Work), 2024. Worker management through AI. From technology development to the impacts on workers and their safety and health. Discussion paper. (Available online: https://osha.europa.eu/en/highlights/ai-worker-management-worker-safety-and-health-considered) [Last Accessed 19-03-2024].
36. Meskó B, Topol EJ. The imperative for regulatory oversight of large language models (or generative AI) in healthcare. NPJ Digit Med. 2023;6(1). Doi: 10.1038/s41746-023-00873-0)
37. Council Directive 89/391/EEC of 12 June 1989 on the introduction of measures to encourage improvements in the safety and health of workers at work (https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:31989L0391) [Last Accessed 6-02-2024].
38. Friedland J, Balkin DB. When gig workers become essential: Leveraging customer moral self-awareness be-yond COVID-19. Bus Horiz. 2023 Mar-Apr;66(2):181-190. Doi: 10.1016/j.bushor.2022.05.003. Epub 2022 May 15. PMID: 35601275; PMCID: PMC9107384
39. Gmyrek P, Berg J, Bescond D. 2023. Generative AI and jobs: A global analysis of potential effects on job quan-tity and quality, ILO Working Paper 96 (Geneva, ILO). https://doi.org/10.54394/ FHEM8239
40. Regulatory considerations on artificial intelligence for health. Geneva: World Health Organization; 2023. Li-cense: CC BY-NC-SA 3.0 IGO
41. Ethics and governance of artificial intelligence for health. Guidance on large multi-modal models. Geneva: World Health Organization; 2024. License: CC BY-NC-SA 3.0 IGO).
42. Ethics & Governance of Artificial Intelligence for Health”. Geneva: World Health Organization; 2021 (https://www.who.int/publications/i/item/9789240029200, accessed 30 January 2024).
43. International Commission on Occupational Health (ICOH). International code of ethics for occupational health professionals. ICOH, Third edition, 2014
44. The ICOH International Code of Ethics for Occupational Medicine Practitioners: Historical Fortunes and Fu-ture Perspectives in Italy. Med Lav 2016; 107, 6: 485-489)
45. INAIL. Il codice internazionale di etica per gli operatori di medicina del lavoro. 2016 ISBN-978-88-7484-511-8
2. McCarthy J, Minsky ML, Rochester N, Shannon C E (2006). A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence, August 31, 1955. AI Magazine, 27(4),12. Doi: https://doi.org/10.1609/aimag.v27i4.1904
3. Haug, Charlotte J, Drazen JM. Artificial Intelligence and Machine Learning in Clinical Medicine, 2023. New Eng J Med vol. 388,13 (2023): 1201-1208. Doi: 10.1056/NEJMra2302038)
4. Bhattad PB, Jain V. Artificial Intelligence in Modern Medicine – The Evolving Necessity of the Present and Role in Transforming the Future of Medical Care. Cureus. Published online 2020. Doi: 10.7759/cureus.8041
5. Leso V, Fontana L, Iavicoli I. The occupational health and safety dimension of Industry 4.0. Med Lav. 2018 Oct 29;110(5):327-338. Doi: 10.23749/mdl.v110i5.7282. PMID: 30378585; PMCID: PMC7682172
6. EU-OSHA (European Agency for Safety and Health at Work), 2019,OSH and the Future of Work: benefits and risks of artificial intelligence tools in (Available online: https://osha.europa.eu/en/publications/osh-and-future-work-benefits-and-risks-artificial-intelligence-tools-workplaces, accessed 05 February 2024)
7. Collins L, Fineman DR, Tsuchida A. 2017. People Analytics: Recalculating the Route. In Walsch, L. and Volini, E.’s Rewriting the rules for digital age. Deloitte University press. 97-106 (Available online: https://www2.deloitte.com/content/dam/Deloitte/global/Documents/About-Deloitte/central-europe/ce-global-human-capital-trends.pdf, accessed 15 February 2024)
8. Mokhtari F, Cheng Z, Wang CH, Foroughi J. Advances in Wearable Piezoelectric Sensors for Hazardous Work-place Environments. Global Challenges. 2023;7(6). Doi: 10.1002/gch2.202300019
9. Baldassarre A, Mucci N, Padovan M, et al. The role of electrocardiography in Occupational Medicine, from Einthoven’s invention to the digital era of wearable devices. Int J Environ Res Public Health. 2020;17(14). Doi: 10.3390/ijerph17144975
10. Prince SA, Elliott CG, Scott K, Visintini S, Reed JL. Device-measured physical activity, sedentary behaviour and cardiometabolic health and fitness across occupational groups: A systematic review and meta- analysis. Inter-national Journal of Behavioral Nutrition and Physical Activity. 2019;16(1). Doi: 10.1186/s12966-019-0790-9
11. Piwek L, Ellis DA, Andrews S, Joinson A. The Rise of Consumer Health Wearables: Promises and Barriers. PLoS Med. 2016;13(2). Doi: 10.1371/journal.pmed.1001953
12. Horizon 2020 Mental Health promotion of cobot Workers in Industry 4.0 https://cordis.europa.eu/project/id/847926, Doi: 10.3030/847926 [Last Accessed 06-02-2024].
13. Murashov V, Hearl F, Howard J. Working safely with robot workers: Recommendations for the new workplace. J Occup Environ Hyg. 2016;13(3). Doi: 10.1080/15459624.2015.1116700
14. Paliga M. The Relationships of Human-Cobot Interaction Fluency with Job Performance and Job Satisfaction among Cobot Operators—The Moderating Role of Workload. Int J Environ Res Public Health. 2023;20(6). Doi: 10.3390/ijerph20065111
15. EU-OSHA (European Agency for Safety and Health at Work), 2018. “Foresight on new and emerging occupa-tional safety and health risks associated with digitalisation by 2025” European Risk Observatory Report. (Available online: https://osha.europa.eu/en/publications/foresight-new-and-emerging-occupational-safety-and-health-risks-associated) [Last Accessed 20-02-2024].
16. Berg J, Hilal A, El S, Horne R. (2021). World employment and social outlook: Trends 2021. International La-bour Organization.
17. Wu, D., & Huang, J. L. (2024). Gig work and gig workers: An integrative review and agenda for future re-search. J Organizat Behav, 45(2), 183–208. Doi: https://doi.org/10.1002/job.2775
18. Adel, A. Future of industry 5.0 in society: human-centric solutions, challenges and prospective research are-as. J Cloud Comp. 11, 40 (2022). Doi: https://doi.org/10.1186/s13677-022-00314-5
19. Topol Review (2019) Preparing the healthcare workforce to deliver the digital future. Final Report February 2019 – A Call For Evidence. A Middleton invited to contribute. Health Education England. (Available online: https://topol.hee.nhs.uk)
20. Boffetta P, Collatuzzo G. Application of P4 (Predictive, Preventive, Personalized, Participatory) Approach to Occupational Medicine. Med Lav. 2022 Feb 22;113(1):e2022009. Doi: 10.23749/mdl.v113i1.12622. PMID: 35226650; PMCID: PMC8902745
21. Blobel B, Kalra D. Editorial: Managing healthcare transformation towards P5 medicine. Front Med (Lau-sanne). 2023 Aug 25;10:1244100. Doi: 10.3389/fmed.2023.1244100. PMID: 37692783; PMCID: PMC10485846
22. Kamel Boulos MN, Zhang P. Digital Twins: From Personalised Medicine to Precision Public Health. J Pers Med 2021; 11(8):745. Doi: https://doi.org/10.3390/jpm11080745
23. Armeni P, Polat I, Maria De Rossi L. (2023). Digital Twins for Health: Opportunities, Barriers and a Path For-ward. IntechOpen. Doi: 10.5772/intechopen.112490
24. Shoja MM, Van de Ridder JMM, Rajput V. The Emerging Role of Generative Artificial Intelligence in Medical Education, Research, and Practice. Cureus. 2023 Jun 24;15(6):e40883. Doi: 10.7759/cureus.40883. PMID: 37492829; PMCID: PMC10363933).
25. Wayne Xin Zhao. A Survey of Large Language Models. Arxiv. Doi: 10.48550/arXiv.2303.18223
26. Lee, Peter et al. “Benefits, Limits, and Risks of GPT-4 as an AI Chatbot for Medicine. Reply.” New Eng J Med vol. 388,25 (2023): 2400. Doi: 10.1056/NEJMc2305286)
27. Thirunavukarasu AJ, Ting DSJ, Elangovan K, Gutierrez L, Tan TF, Ting DSW. Large language models in medi-cine. Nat Med. 2023;29(8). Doi: 10.1038/s41591-023-02448-8).
28. Naveed H, Khan AU, Qiu, S, et al. A Comprehensive Overview of Large Language Models. arXiv 2023, arXiv:2307.06435
29. Chakraborty, Chiranjib et al. “Overview of Chatbots with special emphasis on artificial intelligence-enabled ChatGPT in medical science.” Front Artif Intell vol. 6 1237704. 31 Oct. 2023, Doi: 10.3389/frai.2023.1237704
30. Sridi C, Brigui S. The use of ChatGPT in Occupational Medicine: opportunities and threats. Ann Occup Environ Med. 2023 Oct 23;35:e42. Doi: 10.35371/aoem.2023.35.e42. PMID: 38029273; PMCID: PMC10654530)
31. Padovan M, Cosci B, Petillo A, et al. ChatGPT in Occupational Medicine: A Comparative Study with Human Experts. Bioengineering. 2024; 11(1):57.Doi: https://doi.org/10.3390/bioengineering11010057
32. Ji Z, Lee N, Frieske R, et al. Survey of hallucination in natural language generation. ACM Comput. Surv. 2023,55, 1–38.
33. Mutti A. Hey James, Write an Editorial for “La Medicina del Lavoro”. Med Lav. 2023;114(2):e2023014. Doi: 10.23749/mdl.v114i2.14451. Epub 2023 Apr 13. PMCID: PMC10133773
34. Menz BD, Modi ND, Sorich MJ, Hopkins AM. Health Disinformation Use Case Highlighting the Urgent Need for Artificial Intelligence Vigilance: Weapons of Mass Disinformation. JAMA Intern Med. 2024;184(1):92–96. Doi: 10.1001/jamainternmed.2023.5947
35. EU-OSHA (European Agency for Safety and Health at Work), 2024. Worker management through AI. From technology development to the impacts on workers and their safety and health. Discussion paper. (Available online: https://osha.europa.eu/en/highlights/ai-worker-management-worker-safety-and-health-considered) [Last Accessed 19-03-2024].
36. Meskó B, Topol EJ. The imperative for regulatory oversight of large language models (or generative AI) in healthcare. NPJ Digit Med. 2023;6(1). Doi: 10.1038/s41746-023-00873-0)
37. Council Directive 89/391/EEC of 12 June 1989 on the introduction of measures to encourage improvements in the safety and health of workers at work (https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:31989L0391) [Last Accessed 6-02-2024].
38. Friedland J, Balkin DB. When gig workers become essential: Leveraging customer moral self-awareness be-yond COVID-19. Bus Horiz. 2023 Mar-Apr;66(2):181-190. Doi: 10.1016/j.bushor.2022.05.003. Epub 2022 May 15. PMID: 35601275; PMCID: PMC9107384
39. Gmyrek P, Berg J, Bescond D. 2023. Generative AI and jobs: A global analysis of potential effects on job quan-tity and quality, ILO Working Paper 96 (Geneva, ILO). https://doi.org/10.54394/ FHEM8239
40. Regulatory considerations on artificial intelligence for health. Geneva: World Health Organization; 2023. Li-cense: CC BY-NC-SA 3.0 IGO
41. Ethics and governance of artificial intelligence for health. Guidance on large multi-modal models. Geneva: World Health Organization; 2024. License: CC BY-NC-SA 3.0 IGO).
42. Ethics & Governance of Artificial Intelligence for Health”. Geneva: World Health Organization; 2021 (https://www.who.int/publications/i/item/9789240029200, accessed 30 January 2024).
43. International Commission on Occupational Health (ICOH). International code of ethics for occupational health professionals. ICOH, Third edition, 2014
44. The ICOH International Code of Ethics for Occupational Medicine Practitioners: Historical Fortunes and Fu-ture Perspectives in Italy. Med Lav 2016; 107, 6: 485-489)
45. INAIL. Il codice internazionale di etica per gli operatori di medicina del lavoro. 2016 ISBN-978-88-7484-511-8
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Apr 24, 2024
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Come citare
1.
Baldassarre A, Padovan M. Regulatory and Ethical Considerations on Artificial Intelligence for Occupational Medicine. Med Lav [Internet]. 2024 Apr. 24 [cited 2024 Jul. 18];115(2):e2024013. Available from: https://mattioli1885journals.com/index.php/lamedicinadellavoro/article/view/15881
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Come citare
1.
Baldassarre A, Padovan M. Regulatory and Ethical Considerations on Artificial Intelligence for Occupational Medicine. Med Lav [Internet]. 2024 Apr. 24 [cited 2024 Jul. 18];115(2):e2024013. Available from: https://mattioli1885journals.com/index.php/lamedicinadellavoro/article/view/15881
