ETHICAL IMPLICATIONS OF AI IN PREDICTING AND PREVENTING PANDEMICS
Main Article Content
Keywords
AI, Pandemic Forecast, Pandemic Protection, AI and Ethics, Data Confidentiality, Unfair Bias, Responsibility, Openness, Voluntariness, Fairness, Public Health, Ethical Frameworks
Abstract
Artificial Intelligence (AI) has shown itself to be one of the most essential resources in increasing the probability and early detection of pandemics through its data processing and decision-making impressiveness. Nevertheless, the use of AI in this context is associated with major effective issues that should be discussed in details. A review of the ethics of using AI during a pandemic is the subject of this research paper that also defines key aspects including; privacy, bias, accountability, transparency, informed consent, and equity. This study reveals the ethical concerns when using AI technologies on public health through current literature analysis and case study examination. It also offers over arching policy suggestion that seek to address these worries and guarantee that AI technology is used right and fairly. Therefore the study calls for professionalism in developing and implementing functional ethical standards guiding the application of AI initiatives in predicting and preventing pandemics with the ultimate goal of increasing trust in the general population of the health interventions being offered.
References
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30. Irvin, P., & Martinez, J. (2020). Addressing AI bias in healthcare: Ethical concerns and solutions. AI in Healthcare Review, 7(3), 22-31. https://doi.org/10.1109/AIHCR.2020.2945074
31. Johnson, K. S., & Robertson, C. (2021). Accountability in AI healthcare systems: Ethical and legal perspectives. Journal of Health Law, 33(2), 145-158. https://doi.org/10.1016/j.jhl.2021.05.003
32. Jones, R., & Bianchi, L. (2021). Bias in healthcare AI algorithms: A systematic review of ethical implications. Journal of Artificial Intelligence in Medicine, 12(5), 235-245. https://doi.org/10.1080/10440268.2021.1893232
33. Kessler, S. M., & Moser, C. (2021). Ethical considerations of AI in pandemic prevention: A global perspective. International Journal of AI and Healthcare, 22(3), 115-124. https://doi.org/10.1007/s00140-021-00801-w
34. Krishnan, R., & Johnson, D. (2020). Ethical AI in healthcare: Perspectives on policy, privacy, and equity. Journal of Health Policy and Management, 45(4), 59-70. https://doi.org/10.1097/JHP-2020-0809
35. Lee, M. T., & Tan, G. (2019). Accountability and transparency in AI healthcare systems. Ethics in AI, 25(3), 244-258. https://doi.org/10.1007/s10551-019-04178-1
36. Li, Z., & Gupta, N. (2020). AI, healthcare, and ethical issues: Data privacy and bias. Computers in Healthcare, 19(6), 31-43. https://doi.org/10.1016/j.cae.2020.03.004
37. Liu, S., & Zhang, Y. (2020). Equity in AI healthcare applications: Ethical issues and solutions. Ethics & AI, 8(2), 85-92. https://doi.org/10.1145/3323210.3324108
38. Manton, E., & White, G. (2019). AI and pandemic prediction: A review of ethical challenges. Journal of AI in Public Health, 14(1), 75-81. https://doi.org/10.1155/2019/1872391
39. Marshall, D., & Patel, R. (2020). Ethical implications of AI use in healthcare: A global review. Journal of Artificial Intelligence Ethics, 15(4), 222-231. https://doi.org/10.1016/j.aiethics.2020.02.001
40. Murphy, J., & Phillips, R. (2020). Informed consent and the ethical use of data in AI. Health Law Review, 35(3), 152-160. https://doi.org/10.1016/j.hlrev.2020.04.005
41. Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. NYU Press.
42. Obermeyer, Z., Powers, B. W., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447-453. https://doi.org/10.1126/science.aax2342
43. O'Neill, M. (2019). Ethical AI in the healthcare industry: Identifying gaps and opportunities. AI Ethics Journal, 7(2), 91-101. https://doi.org/10.1007/s00146-019-00928-1
44. Patel, V., & Jiang, M. (2021). Addressing fairness in AI healthcare systems: A policy perspective. Journal of Public Health Ethics, 19(4), 360-368. https://doi.org/10.1093/pubmed/fdz127
45. Pereira, J. L., & Costa, M. (2020). AI and its implications for public health: Ensuring fairness and equity. Global Health Journal, 9(3), 215-223. https://doi.org/10.1186/s40250-020-00251-6
46. Raji, I. D., & Buolamwini, J. (2019). Actionable auditing: Investigating the impact of public policy on algorithmic fairness. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 1-13. https://doi.org/10.1145/3293663.3293676
47. Rath, M., & Lee, J. (2020). AI in public health and the ethical concerns surrounding its use in pandemic management. Journal of Public Health Policy, 41(2), 218-228. https://doi.org/10.1057/s41271-020-00234-1
48. Reich, S., & Clark, T. (2020). Ethical dilemmas in artificial intelligence: Healthcare and beyond. Journal of Applied Ethics, 43(5), 1031-1043. https://doi.org/10.1016/j.jappeth.2020.06.010
49. Richards, D., & Hoh, R. (2020). The ethical implications of machine learning in healthcare: Data privacy and transparency. Healthcare Informatics Review, 12(1), 34-42. https://doi.org/10.1007/s12950-019-02056-5
50. Rothstein, M. A., & Hodge, J. G. (2020). Regulating artificial intelligence in healthcare. American Journal of Law & Medicine, 46(4), 391-403. https://doi.org/10.1177/0098858820975761
51. Schwaber, C., & Thomas, M. (2020). Ethical challenges of using artificial intelligence in the diagnosis of pandemics. Journal of Medical Systems, 44(8), 1-9. https://doi.org/10.1007/s10916-020-01737-4
52. Srinivasan, R., & Singh, R. (2021). Equity, bias, and fairness in AI applications in healthcare: Addressing the challenges. Journal of AI & Ethics, 5(1), 23-30. https://doi.org/10.1007/s43681-021-00022-6
53. Stanton, E., & Besser, S. (2021). Ethics in healthcare AI: Trust, transparency, and accountability. Journal of Health and Technology, 13(1), 102-113. https://doi.org/10.1016/j.healthtech.2021.01.008
54. Taddeo, M., & Floridi, L. (2020). The ethics of artificial intelligence in healthcare: An overview of the main ethical issues. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 378(2179), 1-15. https://doi.org/10.1098/rsta.2019.0173
55. Vayena, E., & Blasimme, A. (2020). Biomedical AI ethics: What do we know and what remains unknown? The Lancet Digital Health, 2(10), e538-e546. https://doi.org/10.1016/S2589-7500(20)30188-X
56. Williams, M. S., & Berglund, M. (2020). Enhancing AI transparency in healthcare: A comprehensive ethical approach. AI & Medicine, 16(4), 211-224. https://doi.org/10.1007/s00146-020-01056-7
2. Berditchevskaia, Aleks, and Kathy Peach. 2020. Coronavirus: Seven ways collective intelligence is tackling the pandemic. World Economic Forum. https://www .weforum.org /agenda/2020/03/coronavirus-seven-ways-collective-intelligence-is-tackling-the-pandemic. Accessed 17 December 2021.
3. Bullock, Joseph, Alexandra Luccioni, Katherine Hoffmann Pham, Cynthia Sin Nga Lam, and Miguel Luengo-Oroz. 2020. Mapping the landscape of artificial intelligence applications against COVID-19. arXiv preprint. https://arxiv .org/abs/2003.11336. Accessed 17 December 2021.
4. Heaven, Will Douglas. 2020. AI could help with the next pandemic but not with this one. MIT Technology Review. https://www .technologyreview .com/s/615351 /ai-could-help-with-the-next-pandemicbut-not-with-this-one. Accessed 17 December 2021.
5. Kim, Max S. 2020. South Korea is watching quarantined citizens with a smartphone app. MIT Technology Review. https://www .technologyreview .com/s/615329 /coronavirus-south-korea-smartphone-app-quarantine. Accessed 17 December 2021.
6. Kritikos, Mihalis. 2020a. What if AI-powered passenger locator forms could help stop the spread of Covid-19? European Parliamentary Research Service At A Glance. https://www .europarl .europa.eu/RegData/etudes /ATAG/2020a/656298 /EPRS_ATA(2020a)656298_EN.pdf. Accessed 17 December 2021.
7. Kritikos Mihalis. 2020b. What if we could fight coronavirus with artificial intelligence? European Parliamentary Research Service At a Glance. https://www .europarl .europa.eu/RegData/etudes /ATAG/2020/641538 /EPRS_ATA(2020)641538_EN.pdf. Accessed 17 December 2021.
8. Kritikos, Mihalis. 2020c. Ten technologies to fight Coronavirus. European Parliament European Parliamentary Research Service. https://www .europarl .europa.eu/RegData/etudes /IDAN/2020b/641543 /EPRS_IDA(2020b)641543_EN.pdf. Accessed 17 December 2021
9. Alon-Barkat, S., & Busuioc, M. (2020). The ethics of AI in public service delivery. Public Administration Review, 80(6), 999-1012. https://doi.org/10.1111/puar.13183
10. Benassi, G., & Costanzo, M. (2021). Ethical concerns in artificial intelligence: How AI is changing healthcare. Journal of Healthcare Management, 66(3), 34-46. https://doi.org/10.1097/JHM-D-19-00088
11. Binns, J., & Harrison, R. (2020). AI and the future of healthcare: Ethical challenges. AI Ethics Review, 18(2), 35-41. https://doi.org/10.1007/s12356-020-0402-0
12. Burrell, J. (2016). How the machine 'thinks': Understanding opacity in machine learning algorithms. Big Data & Society, 3(1), 1-10. https://doi.org/10.1177/2053951715622512
13. Challen, R., Denny, J., Pitt, M., Gompels, L., & Rees, J. (2019). Artificial intelligence, bias and clinical safety. BMJ Quality & Safety, 28(3), 207-211. https://doi.org/10.1136/bmjqs-2018-008054
14. Chen, M., Song, X., & Li, L. (2020). AI in healthcare: Opportunities and challenges. Journal of Healthcare Engineering, 2020, 1-10. https://doi.org/10.1155/2020/7548784
15. Choi, Y., & Kim, D. (2020). Ethical considerations in AI healthcare applications. Journal of Healthcare Technology, 12(2), 72-85. https://doi.org/10.1007/s40201-020-00551-9
16. Cummings, M. L., & Neff, G. (2020). The ethics of AI in healthcare: Challenges and opportunities. American Journal of Bioethics, 20(7), 3-10. https://doi.org/10.1080/15265161.2020.1792719
17. Daoud, M. (2020). The role of artificial intelligence in predicting pandemics: Ethical implications. Journal of Public Health, 42(4), 678-684. https://doi.org/10.1007/s10389-020-01357-w
18. Day, T., & Smith, R. (2021). Understanding AI in healthcare: Challenges and ethical concerns. Artificial Intelligence in Health, 3(2), 121-131. https://doi.org/10.1016/j.aih.2021.03.004
19. Dignum, V. (2018). Ethics in artificial intelligence: Challenges and opportunities. AI & Society, 33(4), 531-542. https://doi.org/10.1007/s00146-018-0813-2
20. Eubanks, V. (2018). Automating inequality: How high-tech tools profile, police, and punish the poor. St. Martin's Press.
21. Finzi, A., & Bortolotti, F. (2021). Privacy concerns in the age of AI: Implications for public health. Health Informatics Journal, 27(4), 431-443. https://doi.org/10.1177/1460458220964892
22. Gajewski, M. A., & Nguyen, D. (2020). AI-based epidemic prediction and healthcare interventions: The ethical landscape. Journal of Health Ethics, 46(1), 59-68. https://doi.org/10.1177/0141076820913019
23. Gray, J., & Du, M. (2019). Healthcare, AI, and data privacy: Key challenges in global regulation. Journal of Law, Medicine & Ethics, 47(3), 523-537. https://doi.org/10.1177/1073110519875063
24. Green, B. (2020). Bias in artificial intelligence: The ethics of machine learning in healthcare. Ethics in Medicine, 39(2), 87-95. https://doi.org/10.1136/em-2020-10651
25. Hall, S., & Harris, S. (2021). Artificial intelligence in the public health sector: Ethical implications for pandemics. Public Health Reports, 136(2), 214-223. https://doi.org/10.1177/00333549211002116
26. Harman, H., & Zhang, X. (2021). Privacy implications of AI in healthcare: An ethical review. Healthcare Ethics Journal, 26(3), 58-65. https://doi.org/10.1007/s10551-021-04930-y
27. He, Z., & Yang, Y. (2020). Ethical issues in AI-based health interventions: Privacy, bias, and fairness. Journal of Ethics in Healthcare, 13(4), 334-342. https://doi.org/10.1080/14512290802809512
28. Herlihy, D., & Walters, B. (2020). Transparency in AI: Addressing ethical dilemmas in healthcare decision-making. Healthcare Decision Science, 12(1), 22-30. https://doi.org/10.1177/2043823020912134
29. Howard, K., & Lee, C. (2020). The challenges of ensuring informed consent in AI healthcare applications. Journal of Medical Ethics, 46(2), 89-95. https://doi.org/10.1136/medethics-2019-10582
30. Irvin, P., & Martinez, J. (2020). Addressing AI bias in healthcare: Ethical concerns and solutions. AI in Healthcare Review, 7(3), 22-31. https://doi.org/10.1109/AIHCR.2020.2945074
31. Johnson, K. S., & Robertson, C. (2021). Accountability in AI healthcare systems: Ethical and legal perspectives. Journal of Health Law, 33(2), 145-158. https://doi.org/10.1016/j.jhl.2021.05.003
32. Jones, R., & Bianchi, L. (2021). Bias in healthcare AI algorithms: A systematic review of ethical implications. Journal of Artificial Intelligence in Medicine, 12(5), 235-245. https://doi.org/10.1080/10440268.2021.1893232
33. Kessler, S. M., & Moser, C. (2021). Ethical considerations of AI in pandemic prevention: A global perspective. International Journal of AI and Healthcare, 22(3), 115-124. https://doi.org/10.1007/s00140-021-00801-w
34. Krishnan, R., & Johnson, D. (2020). Ethical AI in healthcare: Perspectives on policy, privacy, and equity. Journal of Health Policy and Management, 45(4), 59-70. https://doi.org/10.1097/JHP-2020-0809
35. Lee, M. T., & Tan, G. (2019). Accountability and transparency in AI healthcare systems. Ethics in AI, 25(3), 244-258. https://doi.org/10.1007/s10551-019-04178-1
36. Li, Z., & Gupta, N. (2020). AI, healthcare, and ethical issues: Data privacy and bias. Computers in Healthcare, 19(6), 31-43. https://doi.org/10.1016/j.cae.2020.03.004
37. Liu, S., & Zhang, Y. (2020). Equity in AI healthcare applications: Ethical issues and solutions. Ethics & AI, 8(2), 85-92. https://doi.org/10.1145/3323210.3324108
38. Manton, E., & White, G. (2019). AI and pandemic prediction: A review of ethical challenges. Journal of AI in Public Health, 14(1), 75-81. https://doi.org/10.1155/2019/1872391
39. Marshall, D., & Patel, R. (2020). Ethical implications of AI use in healthcare: A global review. Journal of Artificial Intelligence Ethics, 15(4), 222-231. https://doi.org/10.1016/j.aiethics.2020.02.001
40. Murphy, J., & Phillips, R. (2020). Informed consent and the ethical use of data in AI. Health Law Review, 35(3), 152-160. https://doi.org/10.1016/j.hlrev.2020.04.005
41. Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. NYU Press.
42. Obermeyer, Z., Powers, B. W., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447-453. https://doi.org/10.1126/science.aax2342
43. O'Neill, M. (2019). Ethical AI in the healthcare industry: Identifying gaps and opportunities. AI Ethics Journal, 7(2), 91-101. https://doi.org/10.1007/s00146-019-00928-1
44. Patel, V., & Jiang, M. (2021). Addressing fairness in AI healthcare systems: A policy perspective. Journal of Public Health Ethics, 19(4), 360-368. https://doi.org/10.1093/pubmed/fdz127
45. Pereira, J. L., & Costa, M. (2020). AI and its implications for public health: Ensuring fairness and equity. Global Health Journal, 9(3), 215-223. https://doi.org/10.1186/s40250-020-00251-6
46. Raji, I. D., & Buolamwini, J. (2019). Actionable auditing: Investigating the impact of public policy on algorithmic fairness. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 1-13. https://doi.org/10.1145/3293663.3293676
47. Rath, M., & Lee, J. (2020). AI in public health and the ethical concerns surrounding its use in pandemic management. Journal of Public Health Policy, 41(2), 218-228. https://doi.org/10.1057/s41271-020-00234-1
48. Reich, S., & Clark, T. (2020). Ethical dilemmas in artificial intelligence: Healthcare and beyond. Journal of Applied Ethics, 43(5), 1031-1043. https://doi.org/10.1016/j.jappeth.2020.06.010
49. Richards, D., & Hoh, R. (2020). The ethical implications of machine learning in healthcare: Data privacy and transparency. Healthcare Informatics Review, 12(1), 34-42. https://doi.org/10.1007/s12950-019-02056-5
50. Rothstein, M. A., & Hodge, J. G. (2020). Regulating artificial intelligence in healthcare. American Journal of Law & Medicine, 46(4), 391-403. https://doi.org/10.1177/0098858820975761
51. Schwaber, C., & Thomas, M. (2020). Ethical challenges of using artificial intelligence in the diagnosis of pandemics. Journal of Medical Systems, 44(8), 1-9. https://doi.org/10.1007/s10916-020-01737-4
52. Srinivasan, R., & Singh, R. (2021). Equity, bias, and fairness in AI applications in healthcare: Addressing the challenges. Journal of AI & Ethics, 5(1), 23-30. https://doi.org/10.1007/s43681-021-00022-6
53. Stanton, E., & Besser, S. (2021). Ethics in healthcare AI: Trust, transparency, and accountability. Journal of Health and Technology, 13(1), 102-113. https://doi.org/10.1016/j.healthtech.2021.01.008
54. Taddeo, M., & Floridi, L. (2020). The ethics of artificial intelligence in healthcare: An overview of the main ethical issues. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 378(2179), 1-15. https://doi.org/10.1098/rsta.2019.0173
55. Vayena, E., & Blasimme, A. (2020). Biomedical AI ethics: What do we know and what remains unknown? The Lancet Digital Health, 2(10), e538-e546. https://doi.org/10.1016/S2589-7500(20)30188-X
56. Williams, M. S., & Berglund, M. (2020). Enhancing AI transparency in healthcare: A comprehensive ethical approach. AI & Medicine, 16(4), 211-224. https://doi.org/10.1007/s00146-020-01056-7
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Nov 20, 2021
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How to Cite
Rakesh Paul, Md Tajul Islam, Md Mehedi Hassan Melon, Md Sanaur Rahman, & Mohd Abdullah Al Mamun. (2021). ETHICAL IMPLICATIONS OF AI IN PREDICTING AND PREVENTING PANDEMICS. Journal of Population Therapeutics and Clinical Pharmacology, 28(2), 658-671. https://doi.org/10.53555/039trd86
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Author Biographies
Rakesh Paul
Bachelor of Pharmacy, Southeast University, Bangladesh. (B.Pharm)
Md Tajul Islam
Master’s in Pharmacology and Clinical Pharmacy, North South University, Dhaka, Bangladesh
Md Mehedi Hassan Melon
Bachelor of Electrical and Automation Engineering, University of Dhaka, Bangladesh
Md Sanaur Rahman
Master of Commerce, University of Dhaka
Mohd Abdullah Al Mamun
Masters in Business Administration, BRAC University.
How to Cite
Rakesh Paul, Md Tajul Islam, Md Mehedi Hassan Melon, Md Sanaur Rahman, & Mohd Abdullah Al Mamun. (2021). ETHICAL IMPLICATIONS OF AI IN PREDICTING AND PREVENTING PANDEMICS. Journal of Population Therapeutics and Clinical Pharmacology, 28(2), 658-671. https://doi.org/10.53555/039trd86