The Stuff We Swim in: Regulation Alone Will Not Lead to Justifiable Trust in AI

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2023-12-01 DOI:10.1109/MTS.2023.3341463
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
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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.
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我们在其中游泳仅靠监管无法实现对人工智能的合理信任
最近,人工智能(AI)领域出现了一些大型语言模型(LLM),如 GPT-4 和 Bard。这些无疑是令人印象深刻的成就,但它们也引发了关于挪用、准确性、可解释性、可访问性、责任等方面的严重问题。该领域的资深研究人员曾惺惺作态、自贬身价地呼吁停止开发,而行业领导者也曾围绕人工智能系统的潜力(无论好坏)发表过自以为是的评论。其中许多评论利用了大众想象中对机器智能能力的错误概念,这些概念建立在某种弗兰肯斯坦或终结者式的虚构之上:然而,这使得人们完全不清楚以 LLM 为代表的人类与人工智能之间的关系到底是什么或可能是什么。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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