The governance of artificial intelligence: Harnessing opportunities and mitigating challenges

The governance of artificial intelligence: Harnessing opportunities and mitigating challenges
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人工智能治理:利用机遇并应对挑战

DOI:
10.1016/j.respol.2023.104928
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发表时间:
2024
期刊:
影响因子:
7.2
通讯作者:
Goos M
Goos M
中科院分区:
管理学1区
文献类型:
--
作者:
Goos M

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经合组织将人工智能系统定义为“一种基于机器的系统,可以通过为给定的一组目标产生输出(预测,建议或决策)来影响环境。它使用基于机器和/或人类的数据和输入来(i)感知真实的和/或虚拟环境;(ii)通过自动方式(例如,使用机器学习)或手动分析将这些感知插入模型中;以及(iii)使用模型推理来制定结果选项。人工智能系统旨在以不同程度的自主性运行”(经合组织,2019年a)。这个定义将人工智能与最近围绕技术进步产生兴奋的技术类型联系起来:机器学习。机器学习是计算统计学的一个分支,它专注于设计算法来从新数据中进行预测,而无需显式编程解决方案。自2012年以来,机器学习作为预测技术的使用大幅增长。机器学习现在已经很普遍了:Pandora学会了如何根据用户的偏好做出更好的音乐推荐;谷歌学会了如何根据在线找到的翻译文档自动将内容翻译成不同的语言; Facebook学会了如何根据已知用户的数据库识别照片中的人。
The OECD defines an AI (Artificial Intelligence) system as “a machine-based system that can influence the environment by producing an output (predictions, recommendations, or decisions) for a given set of objectives. It uses machine and/or human-based data and inputs to (i) perceive real and/or virtual environments;(ii) insert these perceptions into models through analysis in an automated manner (eg, with machine learning), or manually; and (iii) use model inference to formulate options for outcomes. AI systems are designed to operate with varying levels of autonomy”(OECD, 2019a).This definition relates AI to the type of technology that has created the recent excitement around technological progress: machine learning. Machine learning is a branch of computational statistics that focuses on designing algorithms to make predictions from new data without explicitly programming the solution. Since 2012, the use of machine learning as a prediction technology has grown substantially. Machine learning is now commonplace: Pandora learns how to make better music recommendations based on its users' preferences; Google learns how to automatically translate content into different languages based on translated documents found online; and Facebook learns how to identify people in photos based on its database of known users.
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