We Can’t Expect our Institutions to Ensure Ethical AI

IF 1.7 4区 管理学 Q3 BUSINESS Research-Technology Management Pub Date : 2023-09-03 DOI:10.1080/08956308.2023.2236460
William J. Clancey
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Abstract

Overview:Artificial intelligence raises important ethical concerns, which are unlikely to be adequately addressed by either government or business. Every citizen must work to ensure AI technology is designed and used appropriately.Keywords:: Artificial intelligenceEthicsAI technology Additional informationNotes on contributorsWilliam J. ClanceyWilliam J. Clancey is a cognitive scientist specializing in the nature and applications of artificial intelligence. He is a senior research scientist emeritus at Florida Institute for Human and Machine Cognition. He earned a PhD in computer science from Stanford University and a Bachelor’s degree in mathematical sciences from Rice University. His work combines theory and methods from computer science, psychology, anthropology, and philosophy. wclancey@ihmc.org
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我们不能指望我们的机构确保人工智能的道德
概述:人工智能引发了重要的伦理问题,政府或企业都不太可能充分解决这些问题。每个公民都必须努力确保人工智能技术的设计和使用得当。关键词:人工智能;伦理学;人工智能技术;附加信息:作者说明威廉·j·克兰西威廉·j·克兰西是一位认知科学家,专门研究人工智能的性质和应用。他是佛罗里达人类与机器认知研究所的资深研究科学家。他在斯坦福大学获得计算机科学博士学位,在莱斯大学获得数学科学学士学位。他的工作结合了计算机科学、心理学、人类学和哲学的理论和方法。wclancey@ihmc.org
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来源期刊
Research-Technology Management
Research-Technology Management 管理科学-工程:工业
CiteScore
3.90
自引率
13.60%
发文量
63
审稿时长
>12 weeks
期刊介绍: RTM is the leading peer-reviewed journal focused on the practice of innovation. We publish articles that map the cutting edge in R&D management, illustrate how management theory can be applied to real-world challenges, and give R&D managers the tools to promote innovation throughout their organizations. RTM publishes both quantitative and rigorous qualitative work, including case studies, descriptions of new practical models, and paradigms for understanding and fostering innovation. We are interested in a wide range of topics in innovation and technology management, including: • Product development processes and strategy • R&D portfolio management • R&D performance metrics • Management of technical and creative people • Strategy and innovation • Global innovation • Innovation and design, including design thinking • Innovation and organizational culture • Innovation and sustainability across the triple bottom line • New modes of innovation, including business model innovation, corporate entrepreneuring/intrapreneuring, and various forms of open innovation • Intellectual asset management • Innovations of manufacturing, including Industry 4.0 • Security, ethical, and legal challenges associated with emerging technologies and innovation nodes • Emerging trends reshaping R&D and innovation into the future
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