摘要
[目的/意义]如何使AI(Artificial Intelligence)智能体在内的AI生态系统能够“明物理、通事理和懂人理”是AI治理的核心命题。而AI训练,尤其是人在回路型AI训练为此问题提供了解决方案。[方法/过程]首先,采用流程分析方法,提出人在回路型AI训练的基本流程;其次,结合人在回路思想和AI训练流程,提出了AI训练的交互模型;接着,通过对Indeed、Linkedin、智联招聘、拉勾和百度百聘五家招聘网站上发布的AI训练师的招聘公告进行分析,探讨了AI训练师的岗位职责与能力要求。[结果/结论]AI训练不能停留于对AI智能体知识和技能维度的训练,而更应重视对其进行人文和社会维度的训练。为此,AI训练可分为预训练和再训练两种,分别侧重于使AI智能体具备“明物理、通事理”和“懂人理”的能力。人在回路型AI训练的基本流程和交互模型的提出为AI训练,尤其是基于人文和社会维度的AI再训练提供了理论参考。
[Purpose/significance] How to equip AI systems including AI agents with the knowledge and skills and make them behave in a more humanized way is the core proposition of AI governance. AI training, especially humanin-the-loop AI training, is a valuable solution to this problem. [Method/process] Firstly, based on the procedure analysis, the basic process of human-in-the-loop AI training is proposed. Secondly, the interaction models of AI training are proposed based on the human-in-the-loop idea and AI training process. Moreover, by analyzing hiring announcements of AI trainers posted on Indeed, Linkedin, Zhaopin, Lagou and Baidu Baipin,the job responsibilities and requirements of AI trainers are discussed. [Result/conclusion] AI training should not be limited to the training of knowledge and skills of AI, but should also focus on the training in humanistic and social dimensions. In addition, AI training can be divided into pre-training and retraining, which respectively focus on the training of cognitive ability and humanization of AI. The basic process and interaction models of human-in-the-loop AI training explored in this paper will provide theoretical references for the development of AI training, especially AI retraining.
作者
余欣
朝乐门
孟刚
Yu Xin;Chao Lemen;Meng Gang(Key Laboratory of Data Engineering and Knowledge Engineering(Renmin University of China),Beijing,100872;School of Information Resource Management,Renmin University of China,Beijing,100872;Institute of Finance and Economics,Zhengzhou University of Science and Technology,Zhengzhou,450064)
出处
《情报资料工作》
CSSCI
北大核心
2022年第5期34-41,共8页
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