通过重新评估公众认知建立对人工智能生态系统的信任

Christian Flores
{"title":"通过重新评估公众认知建立对人工智能生态系统的信任","authors":"Christian Flores","doi":"10.5070/cr37224","DOIUrl":null,"url":null,"abstract":"Artificial intelligence systems leverage large datasets with iterative processing algorithms that identify patterns to create an additional layer of expertise. This transformational power operates in tandem with ethical risks. The dominant narrative behind AI is simultaneously stigmatized and misunderstood: with exponential growth of the ubiquitous technology leaving public awareness in the dust, it's becoming increasingly important to balance enthusiasm for AI's enormous promise with a sober understanding of its moral risks. This study seeks to characterize the public opinion of AI in high-risk, domain-specific applications. To that end, a poll was administered to American adults. The results of the study reveal that the great majority of survey respondents have a neutral or optimistic perspective on AI in particular high-risk domains. The study concludes by presenting a standard heuristic for understanding public perception where ethics may fail to preserve a human factors' approach. In this way, researchers and developers can undertake coordinated efforts to mitigate the harm caused by AI while promoting rational optimism in vulnerable populations.","PeriodicalId":517860,"journal":{"name":"Challenger Research Journal","volume":"16 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Building Trust in the AI Ecosystem by Re-Evaluating Public Perception\",\"authors\":\"Christian Flores\",\"doi\":\"10.5070/cr37224\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Artificial intelligence systems leverage large datasets with iterative processing algorithms that identify patterns to create an additional layer of expertise. This transformational power operates in tandem with ethical risks. The dominant narrative behind AI is simultaneously stigmatized and misunderstood: with exponential growth of the ubiquitous technology leaving public awareness in the dust, it's becoming increasingly important to balance enthusiasm for AI's enormous promise with a sober understanding of its moral risks. This study seeks to characterize the public opinion of AI in high-risk, domain-specific applications. To that end, a poll was administered to American adults. The results of the study reveal that the great majority of survey respondents have a neutral or optimistic perspective on AI in particular high-risk domains. The study concludes by presenting a standard heuristic for understanding public perception where ethics may fail to preserve a human factors' approach. In this way, researchers and developers can undertake coordinated efforts to mitigate the harm caused by AI while promoting rational optimism in vulnerable populations.\",\"PeriodicalId\":517860,\"journal\":{\"name\":\"Challenger Research Journal\",\"volume\":\"16 3\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Challenger Research Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5070/cr37224\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Challenger Research Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5070/cr37224","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

人工智能系统利用大型数据集和迭代处理算法来识别模式,从而创造出更多层次的专业知识。这种变革的力量与道德风险并存。人工智能背后的主流叙事同时被污名化和误解:随着这种无处不在的技术的指数级增长,公众的认识被抛到九霄云外,平衡对人工智能巨大前景的热情和对其道德风险的清醒认识变得越来越重要。本研究旨在了解公众对人工智能在高风险、特定领域应用的看法。为此,我们对美国成年人进行了民意调查。研究结果显示,绝大多数受访者对人工智能在特定高风险领域的应用持中立或乐观态度。研究最后提出了一种标准的启发式方法,用于理解公众对伦理道德可能无法维护人因方法的看法。这样,研究人员和开发人员就可以协调努力,减轻人工智能造成的伤害,同时促进弱势群体的理性乐观。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Building Trust in the AI Ecosystem by Re-Evaluating Public Perception
Artificial intelligence systems leverage large datasets with iterative processing algorithms that identify patterns to create an additional layer of expertise. This transformational power operates in tandem with ethical risks. The dominant narrative behind AI is simultaneously stigmatized and misunderstood: with exponential growth of the ubiquitous technology leaving public awareness in the dust, it's becoming increasingly important to balance enthusiasm for AI's enormous promise with a sober understanding of its moral risks. This study seeks to characterize the public opinion of AI in high-risk, domain-specific applications. To that end, a poll was administered to American adults. The results of the study reveal that the great majority of survey respondents have a neutral or optimistic perspective on AI in particular high-risk domains. The study concludes by presenting a standard heuristic for understanding public perception where ethics may fail to preserve a human factors' approach. In this way, researchers and developers can undertake coordinated efforts to mitigate the harm caused by AI while promoting rational optimism in vulnerable populations.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Use of CRISPR/Cas9 Gene Editing Methods to Investigate the Mechanism of Trem2-Dependent Gene Expression in Macrophages Treading on the Tiger’s Tail: Chinese Wuxia and Japanese Jidaigeki Action Films Reacting to State Censorship in the 1930s and 1940s Building Trust in the AI Ecosystem by Re-Evaluating Public Perception Challenger Research Journal Volume 4
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1