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A review of Robots Won’t Save Japan: An Ethnography of Eldercare Automation by James Wright 詹姆斯·赖特(James Wright)的《机器人不会拯救日本:老年护理自动化的人种志》
Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2023-11-08 DOI: 10.1007/s00146-023-01800-3
Ngoc-Thang B. Le, Manh-Tung Ho
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引用次数: 0
Correction: Artificial intelligence as the new fire and its geopolitics 更正:人工智能作为新火及其地缘政治
Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2023-11-06 DOI: 10.1007/s00146-023-01784-0
Manh-Tung Ho, Hong-Kong T. Nguyen
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引用次数: 0
Artificial intelligence and the law from a Japanese perspective: a book review 日本视角下的人工智能与法律:书评
Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2023-11-04 DOI: 10.1007/s00146-023-01801-2
Manh-Tung Ho
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引用次数: 0
Correction: Bowling alone in the autonomous vehicle: the ethics of well-being in the driverless car 更正:在自动驾驶汽车中独自打保龄球:无人驾驶汽车中的幸福伦理
Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2023-11-02 DOI: 10.1007/s00146-023-01781-3
Avigail Ferdman
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引用次数: 0
Review of “AI assurance: towards trustworthy, explainable, safe, and ethical AI” by Feras A. Batarseh and Laura J. Freeman, Academic Press, 2023 Feras A. Batarseh和Laura J. Freeman合著的《人工智能保证:走向可信赖、可解释、安全和合乎道德的人工智能》,学术出版社,2023年
Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2023-11-01 DOI: 10.1007/s00146-023-01802-1
Jialei Wang, Li Fu
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引用次数: 0
Mind who’s testing: Turing tests and the post-colonial imposition of their implicit conceptions of intelligence 注意谁在测试:图灵测试和后殖民时期对智力的隐性概念的强加
Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2023-10-31 DOI: 10.1007/s00146-023-01796-w
Fabian Fischbach, Tijs Vandemeulebroucke, Aimee van Wynsberghe
Abstract This paper aims to show that dominant conceptions of intelligence used in artificial intelligence (AI) are biased by normative assumptions that originate from the Global North, making it questionable if AI can be uncritically applied elsewhere without risking serious harm to vulnerable people. After the introduction in Sect. 1 we shortly present the history of IQ testing in Sect. 2, focusing on its multiple discriminatory biases. To determine how these biases came into existence, we define intelligence ontologically and underline its constructed and culturally variable character. Turning to AI, specifically the Turing Test (TT), in Sect. 3, we critically examine its underlying intelligence conceptions. The test has been of central influence in AI research and remains an important point of orientation. We argue that both the test itself and how it is used in practice risk promoting a limited conception of intelligence which solely originated in the Global North. Hence, this conception should be critically assessed in relation to the different global contexts in which AI technologies are and will be used. In Sect. 4, we highlight how unequal power relations in AI research are a real threat, rather than just philosophical sophistry while considering the history of IQ testing and the TT’s practical biases. In the last section, we examine the limits of our account and identify fields for further investigation. Tracing colonial continuities in AI intelligence research, this paper points to a more diverse and historically aware approach to the design, development, and use of AI.
本文旨在表明,人工智能(AI)中使用的主流智能概念受到来自全球北方的规范性假设的偏见,这使得人工智能是否可以不加批判地应用于其他地方而不会对弱势群体造成严重伤害成为问题。在第1节的介绍之后,我们将在第2节简要介绍智商测试的历史,重点关注其多重歧视性偏见。为了确定这些偏见是如何形成的,我们从本体论上定义了智力,并强调了智力的构建和文化变化特征。转向人工智能,特别是图灵测试(TT),在第3节中,我们批判性地检查其潜在的智能概念。该测试在人工智能研究中具有核心影响,并且仍然是一个重要的方向。我们认为,无论是测试本身,还是在实践中如何使用它,都有可能促进一种仅仅起源于全球北方的有限的智力概念。因此,应该根据人工智能技术正在使用和将要使用的不同全球背景,对这一概念进行批判性评估。在第4节中,我们强调了人工智能研究中的不平等权力关系是一个真正的威胁,而不仅仅是哲学上的诡辩,同时考虑到智商测试的历史和TT的实际偏见。在最后一节中,我们检查了我们的帐户的限制,并确定了进一步调查的领域。本文追溯了人工智能研究中的殖民连续性,指出了一种更加多样化和历史意识的方法来设计、开发和使用人工智能。
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引用次数: 0
Grasping AI: experiential exercises for designers 掌握AI:设计师的体验练习
Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2023-10-30 DOI: 10.1007/s00146-023-01794-y
Dave Murray-Rust, Maria Luce Lupetti, Iohanna Nicenboim, Wouter van der Hoog
Abstract Artificial intelligence (AI) and machine learning (ML) are increasingly integrated into the functioning of physical and digital products, creating unprecedented opportunities for interaction and functionality. However, there is a challenge for designers to ideate within this creative landscape, balancing the possibilities of technology with human interactional concerns. We investigate techniques for exploring and reflecting on the interactional affordances, the unique relational possibilities, and the wider social implications of AI systems. We introduced into an interaction design course ( n = 100) nine ‘AI exercises’ that draw on more than human design, responsible AI, and speculative enactment to create experiential engagements around AI interaction design. We find that exercises around metaphors and enactments make questions of training and learning, privacy and consent, autonomy and agency more tangible, and thereby help students be more reflective and responsible on how to design with AI and its complex properties in both their design process and outcomes.
人工智能(AI)和机器学习(ML)越来越多地集成到物理和数字产品的功能中,为交互和功能创造了前所未有的机会。然而,对于设计师来说,在这种创造性的环境中进行构思是一个挑战,平衡技术的可能性和人类的互动问题。我们研究了探索和反思人工智能系统的交互能力、独特的关系可能性和更广泛的社会影响的技术。我们在交互设计课程(n = 100)中引入了9个“人工智能练习”,这些练习不仅利用了人类设计、负责任的人工智能和推测性的制定,还围绕人工智能交互设计创造了体验性的参与。我们发现,围绕隐喻和制定的练习使培训和学习、隐私和同意、自主和代理等问题更加切实,从而帮助学生在设计过程和结果中对如何使用人工智能及其复杂属性进行设计进行反思和负责。
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引用次数: 0
Automated inauthenticity 自动化的不真实
Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2023-10-29 DOI: 10.1007/s00146-023-01795-x
Mark Ressler
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引用次数: 0
Friend or foe? Exploring the implications of large language models on the science system 是敌是友?探索大型语言模型对科学系统的影响
Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2023-10-26 DOI: 10.1007/s00146-023-01791-1
Benedikt Fecher, Marcel Hebing, Melissa Laufer, Jörg Pohle, Fabian Sofsky
Abstract The advent of ChatGPT by OpenAI has prompted extensive discourse on its potential implications for science and higher education. While the impact on education has been a primary focus, there is limited empirical research on the effects of large language models (LLMs) and LLM-based chatbots on science and scientific practice. To investigate this further, we conducted a Delphi study involving 72 researchers specializing in AI and digitization. The study focused on applications and limitations of LLMs, their effects on the science system, ethical and legal considerations, and the required competencies for their effective use. Our findings highlight the transformative potential of LLMs in science, particularly in administrative, creative, and analytical tasks. However, risks related to bias, misinformation, and quality assurance need to be addressed through proactive regulation and science education. This research contributes to informed discussions on the impact of generative AI in science and helps identify areas for future action.
OpenAI的ChatGPT的出现引发了关于其对科学和高等教育潜在影响的广泛讨论。虽然对教育的影响一直是主要关注的焦点,但关于大型语言模型(llm)和基于llm的聊天机器人对科学和科学实践的影响的实证研究有限。为了进一步调查这一点,我们进行了一项德尔福研究,涉及72名专门从事人工智能和数字化的研究人员。该研究的重点是法学硕士的应用和局限性,它们对科学系统的影响,伦理和法律方面的考虑,以及有效使用法学硕士所需的能力。我们的研究结果突出了法学硕士在科学领域的变革潜力,特别是在行政、创造性和分析任务方面。然而,与偏见、错误信息和质量保证相关的风险需要通过积极的监管和科学教育来解决。这项研究有助于就生成式人工智能在科学中的影响进行知情讨论,并有助于确定未来行动的领域。
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引用次数: 0
Towards a decolonial I in AI & Society 走向人工智能的非殖民化社会
Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2023-10-21 DOI: 10.1007/s00146-023-01770-6
Victoria Vesna
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引用次数: 0
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