| 通用模型的伦理与治理：挑战及对策 |
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| 引用本文： | 滕妍,王国豫,王迎春.通用模型的伦理与治理：挑战及对策[J].中国科学院院刊,2022,37(9):1290-1299. |
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| 作者姓名： | 滕妍 王国豫 王迎春 |
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| 作者单位： | 上海人工智能实验室 治理研究中心 上海 200232;复旦大学 哲学学院 上海 200433;1. 上海人工智能实验室 治理研究中心 上海 200232 |
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| 基金项目： | 上海人工智能实验室,上海市科学技术委员会项目（21511104503、21511104502）,国家自然科学基金（L2124040） |
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| 摘 要： | 通用模型是近年来人工智能发展的重要方向之一。随着模型研发应用的增多,模型的社会和伦理影响受到广泛关注。文章从通用模型的特性出发、分析了模型在算法、数据和算力3个层面潜在的伦理挑战,包括不确定性、真实性、可靠性,偏见、毒性、公平、隐私及环境问题。进一步从技术哲学的视角分析了数据驱动的模型在人与世界关系中的中介性作用及所产生的“镜像”效应问题和透明性问题,提出了人与世界关系的新形态是以模型（数据）为中介的,即“人-模型（数据）-世界”关系。最后,从治理技术和治理机制两方面反思了当前的应对措施及局限性。建议建立开放式、全流程、价值嵌入的伦理规约机制,保障通用模型在合规、合伦理的框架下发展。
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| 关 键 词： | 人工智能 通用模型 风险 治理 科技伦理 |
| 收稿时间： | 2022/8/31 0:00:00 |
Ethics and Governance of General Models:Challenges and Countermeasures |
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| TENG Yan,WANG Guoyu,WANG Yingchun.Ethics and Governance of General Models:Challenges and Countermeasures[J].Bulletin of the Chinese Academy of Sciences,2022,37(9):1290-1299. |
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| Authors: | TENG Yan WANG Guoyu WANG Yingchun |
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| Institution: | Governance Research Center, Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China;School of Philosophy, Fudan University, Shanghai 200433, China;1. Governance Research Center, Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China |
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| Abstract: | In recent years, the general model is one of the most important development trends of artificial intelligence. With the rapidly increasing research and deployment of general models, the social and ethical effects of general models have received extensive attention. Grounded in the characteristics of general models, this article analyzes the potential ethical challenges of the models at three levels:algorithm, data, and computing power. The detailed challenges include uncertainty, truthfulness, reliability, bias, toxicity, fairness, privacy, and environmental issues. Also, through the lens of philosophy of technology, it elaborates the important reasons for the ethical challenges:the "mirroring" effect and transparency problem caused by the data-driven general models'' mediation between human and the world. This relation can be depicted as "human-model (data)-world". Finally, from the perspectives of governance tools and governance mechanisms, this article reviews the current countermeasures and reflects on their limitations. It is recommended to establish an open, full-process, value-embedded ethical restraint mechanism to ensure that the general model develops in accordance with legal and ethical requirements. |
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| Keywords: | artificial intelligence general model risk governance ethics of technology |
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