Simon T. Powers;Olena Linnyk;Michael Guckert;Jennifer Hannig;Jeremy Pitt;Neil Urquhart;Aniko Ekárt;Nils Gumpfer;The Anh Han;Peter R. Lewis;Stephen Marsh;Tim Weber
{"title":"The Stuff We Swim in: Regulation Alone Will Not Lead to Justifiable Trust in AI","authors":"Simon T. Powers;Olena Linnyk;Michael Guckert;Jennifer Hannig;Jeremy Pitt;Neil Urquhart;Aniko Ekárt;Nils Gumpfer;The Anh Han;Peter R. Lewis;Stephen Marsh;Tim Weber","doi":"10.1109/MTS.2023.3341463","DOIUrl":null,"url":null,"abstract":"Recent activity in the field of artificial intelligence (AI) has given rise to large language models (LLMs) such as GPT-4 and Bard. These are undoubtedly impressive achievements, but they raise serious questions about appropriation, accuracy, explainability, accessibility, responsibility, and more. There have been pusillanimous and self-exculpating calls for a halt in development by senior researchers in the field and largely self-serving comments by industry leaders around the potential of AI systems, good or bad. Many of these commentaries leverage misguided conceptions, in the popular imagination, of the competence of machine intelligence, based on some sort of Frankenstein or Terminator-like fiction: however, this leaves it entirely unclear what exactly the relationship between human(ity) and AI, as represented by LLMs or what comes after, is or could be.","PeriodicalId":55016,"journal":{"name":"IEEE Technology and Society Magazine","volume":"42 4","pages":"95-106"},"PeriodicalIF":2.1000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Technology and Society Magazine","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10410106/","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Recent activity in the field of artificial intelligence (AI) has given rise to large language models (LLMs) such as GPT-4 and Bard. These are undoubtedly impressive achievements, but they raise serious questions about appropriation, accuracy, explainability, accessibility, responsibility, and more. There have been pusillanimous and self-exculpating calls for a halt in development by senior researchers in the field and largely self-serving comments by industry leaders around the potential of AI systems, good or bad. Many of these commentaries leverage misguided conceptions, in the popular imagination, of the competence of machine intelligence, based on some sort of Frankenstein or Terminator-like fiction: however, this leaves it entirely unclear what exactly the relationship between human(ity) and AI, as represented by LLMs or what comes after, is or could be.
期刊介绍:
IEEE Technology and Society Magazine invites feature articles (refereed), special articles, and commentaries on topics within the scope of the IEEE Society on Social Implications of Technology, in the broad areas of social implications of electrotechnology, history of electrotechnology, and engineering ethics.