Ethical Perspective on AI Hazards to Humans: A Review

Overview

Journal Medicine (Baltimore)

Specialty General Medicine

Date 2023 Dec 5

PMID 38050218

Authors

Changye Chen

Ziyu Chen

Wenyu Luo

Ying Xu

Sixia Yang

Guozhao Yang

Xuhong Chen

Xiaoxia Chi

Ni Xie

Zhuoying Zeng

Affiliations

Soon will be listed here.

Abstract

This article explores the potential ethical hazards of artificial intelligence (AI) on society from an ethical perspective. We introduce the development and application of AI, emphasizing its potential benefits and possible negative impacts. We particularly examine the application of AI in the medical field and related ethical and legal issues, and analyze potential hazards that may exist in other areas of application, such as autonomous driving, finance, and security. Finally, we offer recommendations to help policymakers, technology companies, and society as a whole address the potential hazards of AI. These recommendations include strengthening regulation and supervision of AI, increasing public understanding and awareness of AI, and actively exploring how to use the advantages of AI to achieve a more just, equal, and sustainable social development. Only by actively exploring the advantages of AI while avoiding its negative impacts can we better respond to future challenges.

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References

Drukker K, Chen W, Gichoya J, Gruszauskas N, Kalpathy-Cramer J, Koyejo S . Toward fairness in artificial intelligence for medical image analysis: identification and mitigation of potential biases in the roadmap from data collection to model deployment. J Med Imaging (Bellingham). 2023; 10(6):061104. PMC: 10129875. DOI: 10.1117/1.JMI.10.6.061104. View

Dedeloudi A, Weaver E, Lamprou D . Machine learning in additive manufacturing & Microfluidics for smarter and safer drug delivery systems. Int J Pharm. 2023; 636:122818. DOI: 10.1016/j.ijpharm.2023.122818. View

Filippi L, Urso L, Bianconi F, Palumbo B, Marzola M, Evangelista L . Radiomics and theranostics with molecular and metabolic probes in prostate cancer: toward a personalized approach. Expert Rev Mol Diagn. 2023; 23(3):243-255. DOI: 10.1080/14737159.2023.2192351. View

Cortis K, Davis B . Over a decade of social opinion mining: a systematic review. Artif Intell Rev. 2021; 54(7):4873-4965. PMC: 8227369. DOI: 10.1007/s10462-021-10030-2. View

Murphy K, Di Ruggiero E, Upshur R, Willison D, Malhotra N, Cai J . Artificial intelligence for good health: a scoping review of the ethics literature. BMC Med Ethics. 2021; 22(1):14. PMC: 7885243. DOI: 10.1186/s12910-021-00577-8. View

Li C, Bian S, Wu T, Donovan R, Li B . Affordable Artificial Intelligence-Assisted Machine Supervision System for the Small and Medium-Sized Manufacturers. Sensors (Basel). 2022; 22(16). PMC: 9414792. DOI: 10.3390/s22166246. View

Buchanan B, Wright D . The impact of machine learning on UK financial services. Oxf Rev Econ Policy. 2021; 37(3):537-563. PMC: 8500123. DOI: 10.1093/oxrep/grab016. View

Pande S, Nattarkannan K, Rama Bai M, Kapila D, Anandan P, Mishra N . Lightweight Artificial Intelligence for Secure Data Communication in Energy-Constrained Healthcare Devices. Comput Intell Neurosci. 2022; 2022:7934582. PMC: 9451988. DOI: 10.1155/2022/7934582. View

Lee P, Bubeck S, Petro J . Benefits, Limits, and Risks of GPT-4 as an AI Chatbot for Medicine. N Engl J Med. 2023; 388(13):1233-1239. DOI: 10.1056/NEJMsr2214184. View

10.

Lorenz E, Zaniletti I, Johnson B, Petterson T, Kremers W, Schinstock C . Physiological Age by Artificial Intelligence-Enhanced Electrocardiograms as a Novel Risk Factor of Mortality in Kidney Transplant Candidates. Transplantation. 2023; 107(6):1365-1372. PMC: 10205652. DOI: 10.1097/TP.0000000000004504. View

11.

Dalton-Brown S . The Ethics of Medical AI and the Physician-Patient Relationship. Camb Q Healthc Ethics. 2019; 29(1):115-121. DOI: 10.1017/S0963180119000847. View

12.

Kim H, Shon T . Industrial network-based behavioral anomaly detection in AI-enabled smart manufacturing. J Supercomput. 2022; 78(11):13554-13563. PMC: 8935250. DOI: 10.1007/s11227-022-04408-4. View

13.

Liuzzi P, Campagnini S, Fanciullacci C, Arienti C, Patrini M, Carrozza M . Predicting SARS-CoV-2 infection duration at hospital admission:a deep learning solution. Med Biol Eng Comput. 2022; 60(2):459-470. PMC: 8739354. DOI: 10.1007/s11517-021-02479-8. View

14.

Li N, Fan L, Xu H, Zhang X, Bai Z, Li M . An AI-Aided Diagnostic Framework for Hematologic Neoplasms Based on Morphologic Features and Medical Expertise. Lab Invest. 2023; 103(4):100055. DOI: 10.1016/j.labinv.2022.100055. View

15.

Keskinbora K . Medical ethics considerations on artificial intelligence. J Clin Neurosci. 2019; 64:277-282. DOI: 10.1016/j.jocn.2019.03.001. View

16.

van de Sande D, Van Bommel J, Chung E, Gommers D, van Genderen M . Algorithmic fairness audits in intensive care medicine: artificial intelligence for all?. Crit Care. 2022; 26(1):315. PMC: 9578232. DOI: 10.1186/s13054-022-04197-5. View

17.

Sun M, Kentley J, Wilson B, Soyer H, Curiel-Lewandrowski C, Rotemberg V . Digital skin imaging applications, part II: a comprehensive survey of post-acquisition image utilization features and technology standards. Skin Res Technol. 2022; 28(6):771-779. PMC: 9907633. DOI: 10.1111/srt.13195. View

18.

Fraser A, Biasin E, Bijnens B, Bruining N, Caiani E, Cobbaert K . Artificial intelligence in medical device software and high-risk medical devices - a review of definitions, expert recommendations and regulatory initiatives. Expert Rev Med Devices. 2023; 20(6):467-491. DOI: 10.1080/17434440.2023.2184685. View