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2019冠状病毒病、人工智能、伦理挑战及政策影响

COVID-19, artificial intelligence, ethical challenges and policy implications.

作者信息

Anshari Muhammad, Hamdan Mahani, Ahmad Norainie, Ali Emil, Haidi Hamizah

机构信息

Universiti Brunei Darussalam, Brunei, Brunei Darussalam.

出版信息

AI Soc. 2023;38(2):707-720. doi: 10.1007/s00146-022-01471-6. Epub 2022 May 19.

DOI:10.1007/s00146-022-01471-6
PMID:35607368
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9117835/
Abstract

As the COVID-19 outbreak remains an ongoing issue, there are concerns about its disruption, the level of its disruption, how long this pandemic is going to last, and how innovative technological solutions like Artificial Intelligence (AI) and expert systems can assist to deal with this pandemic. AI has the potential to provide extremely accurate insights for an organization to make better decisions based on collected data. Despite the numerous advantages that may be achieved by AI, the use of AI can be perceived differently by society, where moral and ethical issues may be raised, especially in regards to accessing and exploiting public data gathered from social media platforms. To better comprehend the concerns and ethical challenges, utilitarianism and deontology were used as business ethics frameworks to explore the aforementioned challenges of AI in society. The framework assists in determining whether the AI's deployment is ethically acceptable or not. The paper lays forth policy recommendations for public and private organizations to embrace AI-based decision-making processes to avoid data privacy violations and maintain public trust.

摘要

由于新冠疫情仍是一个持续存在的问题,人们担心其造成的破坏、破坏程度、这场大流行将持续多久,以及人工智能(AI)和专家系统等创新技术解决方案如何有助于应对这场大流行。人工智能有潜力为组织提供极其准确的见解,以便基于收集到的数据做出更好的决策。尽管人工智能可能带来诸多优势,但社会对其使用的看法可能不同,可能会引发道德和伦理问题,尤其是在获取和利用从社交媒体平台收集的公共数据方面。为了更好地理解这些担忧和伦理挑战,功利主义和道义论被用作商业伦理框架,以探讨人工智能在社会中面临的上述挑战。该框架有助于确定人工智能的部署在伦理上是否可接受。本文为公共和私营组织提出了政策建议,以采用基于人工智能的决策过程,避免侵犯数据隐私并维持公众信任。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fe9/9117835/748e97de9ad7/146_2022_1471_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fe9/9117835/8771d1459304/146_2022_1471_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fe9/9117835/8699c1e799d7/146_2022_1471_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fe9/9117835/20c56ea986ed/146_2022_1471_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fe9/9117835/748e97de9ad7/146_2022_1471_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fe9/9117835/8771d1459304/146_2022_1471_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fe9/9117835/8699c1e799d7/146_2022_1471_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fe9/9117835/20c56ea986ed/146_2022_1471_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fe9/9117835/748e97de9ad7/146_2022_1471_Fig4_HTML.jpg

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