人工智能为何需要知识社会学:第一和第二部分

IF 2.9 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Harry Collins
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引用次数: 0

摘要

基于神经网络的人工智能的最新发展——深度学习和大型语言模型,我将其统称为newai——已经在语言处理方面取得了惊人的进步,并且有可能通过向互联网学习来跟上不断变化的人类知识。然而,像ChatGPT这样的例子,这是一个“大型语言模型”,已经被证明没有道德指南针:他们用虚构的回答问题,和提供事实一样流利。我试图解释为什么会这样,基于知识社会学的论点,特别是科学的社会研究,特别是“专业知识和经验的研究”和社会的“分形模型”。从互联网上学习与社会化是不一样的:NEWAI没有提供人类道德理解基础的初级社会化。相反,大型语言模型通过人为干预进行回顾性社会化,试图使它们与社会接受的道德规范保持一致。也许,随着技术的进步,大型语言模型可以很好地理解语音和识别物体,从而获得相当于初级社交的能力。与此同时,我们必须警惕谁在与他们交往,并意识到他们与我们交往的危险,使我们与他们结盟,而不是相反,这种可能性将导致真假之间的区别进一步被侵蚀,从而进一步支持民粹主义和法西斯主义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Why artificial intelligence needs sociology of knowledge: parts I and II

Recent developments in artificial intelligence based on neural nets—deep learning and large language models which together I refer to as NEWAI—have resulted in startling improvements in language handling and the potential to keep up with changing human knowledge by learning from the internet. Nevertheless, examples such as ChatGPT, which is a ‘large language model’, have proved to have no moral compass: they answer queries with fabrications with the same fluency as they provide facts. I try to explain why this is, basing the argument on the sociology of knowledge, particularly social studies of science, notably ‘studies of expertise and experience’ and the ‘fractal model’ of society. Learning from the internet is not the same as socialisation: NEWAI has no primary socialisation such as provides the foundations of human moral understanding. Instead, large language models are retrospectively socialised by human intervention in an attempt to align them with societally accepted ethics. Perhaps, as technology advances, large language models could come to understand speech and recognise objects sufficiently well to acquire the equivalent of primary socialisation. In the meantime, we must be vigilant about who is socialising them and be aware of the danger of their socialising us to align with them rather than vice-versa, an eventuality that would lead to the further erosion of the distinction between the true and the false giving further support to populism and fascism.

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来源期刊
AI & Society
AI & Society COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
8.00
自引率
20.00%
发文量
257
期刊介绍: AI & Society: Knowledge, Culture and Communication, is an International Journal publishing refereed scholarly articles, position papers, debates, short communications, and reviews of books and other publications. Established in 1987, the Journal focuses on societal issues including the design, use, management, and policy of information, communications and new media technologies, with a particular emphasis on cultural, social, cognitive, economic, ethical, and philosophical implications. AI & Society has a broad scope and is strongly interdisciplinary. We welcome contributions and participation from researchers and practitioners in a variety of fields including information technologies, humanities, social sciences, arts and sciences. This includes broader societal and cultural impacts, for example on governance, security, sustainability, identity, inclusion, working life, corporate and community welfare, and well-being of people. Co-authored articles from diverse disciplines are encouraged. AI & Society seeks to promote an understanding of the potential, transformative impacts and critical consequences of pervasive technology for societies. Technological innovations, including new sciences such as biotech, nanotech and neuroscience, offer a great potential for societies, but also pose existential risk. Rooted in the human-centred tradition of science and technology, the Journal acts as a catalyst, promoter and facilitator of engagement with diversity of voices and over-the-horizon issues of arts, science, technology and society. AI & Society expects that, in keeping with the ethos of the journal, submissions should provide a substantial and explicit argument on the societal dimension of research, particularly the benefits, impacts and implications for society. This may include factors such as trust, biases, privacy, reliability, responsibility, and competence of AI systems. Such arguments should be validated by critical comment on current research in this area. Curmudgeon Corner will retain its opinionated ethos. The journal is in three parts: a) full length scholarly articles; b) strategic ideas, critical reviews and reflections; c) Student Forum is for emerging researchers and new voices to communicate their ongoing research to the wider academic community, mentored by the Journal Advisory Board; Book Reviews and News; Curmudgeon Corner for the opinionated. Papers in the Original Section may include original papers, which are underpinned by theoretical, methodological, conceptual or philosophical foundations. The Open Forum Section may include strategic ideas, critical reviews and potential implications for society of current research. Network Research Section papers make substantial contributions to theoretical and methodological foundations within societal domains. These will be multi-authored papers that include a summary of the contribution of each author to the paper. Original, Open Forum and Network papers are peer reviewed. The Student Forum Section may include theoretical, methodological, and application orientations of ongoing research including case studies, as well as, contextual action research experiences. Papers in this section are normally single-authored and are also formally reviewed. Curmudgeon Corner is a short opinionated column on trends in technology, arts, science and society, commenting emphatically on issues of concern to the research community and wider society. Normal word length: Original and Network Articles 10k, Open Forum 8k, Student Forum 6k, Curmudgeon 1k. The exception to the co-author limit of Original and Open Forum (4), Network (10), Student (3) and Curmudgeon (2) articles will be considered for their special contributions. Please do not send your submissions by email but use the "Submit manuscript" button. NOTE TO AUTHORS: The Journal expects its authors to include, in their submissions: a) An acknowledgement of the pre-accept/pre-publication versions of their manuscripts on non-commercial and academic sites. b) Images: obtain permissions from the copyright holder/original sources. c) Formal permission from their ethics committees when conducting studies with people.
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