人工智能视阈下教育治理的技术功用与困境突破
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摘要
人工智能是历经多次产业革命和长期技术积累的共同成果,具有技术优势与社会属性高度融合的典型特征。通过分析人工智能的意涵与技术进路,得出借助于机器学习、专家系统和人机交互等关键技术,能够实现教育治理信息筛选与情境再现、系统识别应答复杂教育情境、神经网络模拟辅助教育治理决策行为。但因与传统的教育治理体制机制不相适应,使得教育治理面临着多元主体"功能性"缺位、垂直单向的组织结构"能动性"不足、治理思维认知与行动方式的"阻滞性"、治理制度"规制性"和伦理道德"规范性"缺失等现实困境。为破解这些难题,提出明辨多元治理主体权限,优化治理组织架构,推进治理理念与行为建设,尤其关注重构监督机制及伦理道德等因应策略,为实现教育治理智能化和现代化提供支撑。
Artificial intelligence is a common achievement based on many industrial revolutions and long-term technology accumulation, which characterizes high integration of technological advantages and social attributes. By analyzing the implication and technical approach of artificial intelligence, it is concluded that with the help of key technologies such as machine learning, expert system and human-computer interaction, the information screening and situation representation of educational governance, system's identification and response of the complex educational situation, the decision-making behavior of auxiliary education governance simulated by neural network can be realized. However, because of the inappropriate traditional institutional mechanism, educational governance is faced with such practical dilemmas as the absence of the function of multiple subjects, the lack of the initiative of vertical and one-way organizational structure, the retardation of governance thinking and action mode, the regulation of governance system and the lack of ethical and moral standardization. In order to solve those problems, this paper puts forward some countermeasures, such as distinguishing the authority of multiple governance subjects, optimizing the organizational structure of governance, promoting the construction of governance concepts and behaviors, paying special attention to the reconstruction of supervision mechanism and ethics,etc., so as to provide support for realizing the intellectualization and modernization of educational governance.
Artificial intelligence is a common achievement based on many industrial revolutions and long-term technology accumulation, which characterizes high integration of technological advantages and social attributes. By analyzing the implication and technical approach of artificial intelligence, it is concluded that with the help of key technologies such as machine learning, expert system and human-computer interaction, the information screening and situation representation of educational governance, system's identification and response of the complex educational situation, the decision-making behavior of auxiliary education governance simulated by neural network can be realized. However, because of the inappropriate traditional institutional mechanism, educational governance is faced with such practical dilemmas as the absence of the function of multiple subjects, the lack of the initiative of vertical and one-way organizational structure, the retardation of governance thinking and action mode, the regulation of governance system and the lack of ethical and moral standardization. In order to solve those problems, this paper puts forward some countermeasures, such as distinguishing the authority of multiple governance subjects, optimizing the organizational structure of governance, promoting the construction of governance concepts and behaviors, paying special attention to the reconstruction of supervision mechanism and ethics,etc., so as to provide support for realizing the intellectualization and modernization of educational governance.
引文
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[3]雷·库兹韦尔.奇点来临[M].李庆诚,等译.北京:机械工业出版社,2011:160.
[4]詹姆斯·罗西瑙.没有政府的治理[M].张胜军,译.南昌:江西人民出版社,2001:55.
[5]俞可平.治理和善治:一种新的政治分析框架[J].南京社会科学,2001(9):40-44.
[6] WILLIAMSON B. Digital education governance:data visualization, predictive analytics, and “real-time” policy instruments[J].Journal of education policy, 2016, 31(2):1-19.
[7]陈金芳,万作芳.教育治理体系与治理能力现代化的几点思考[J].教育研究, 2016(10):25-31.
[8] ZHU B, WANG Y, HE C L. Global social event extraction and analysis by processing online news[C]//International Conference on Information System and Artificial Intelligence. New York:IEEE, 2017:73-76.
[9] SOMERS M J, CASAL J. Introducing neural computing in governance research:applying self-organizing maps to configurational studies[J]. Corporate governance:an international review, 2017, 25(6):440-453.
[10]褚宏启.教育治理:以共治求善治[J].教育研究,2014(10):4-11.
[11]鲍勃·杰索普,漆蕪.治理的兴起及其失败的风险:以经济发展为例的论述[J].国际社会科学杂志,1999(1):31-48.
[12]王战军,肖红缨.大数据背景下的院系治理现代化[J].高等教育研究,2016(3):21-27.
[13]刘金松.大数据应用于教育决策的可行性与潜在问题研究[J].电化教育研究, 2017(11):37-41,73.
[14] O'LEARY D E. Artificial intelligence and big data[J].IEEE intelligent systems, 2013,28(2):96-99.
[15]俞宪忠.制度现代化解构[J].天津社会科学,2002(5):78-83.
[16] HALL P A, TAYLOR R C R. Political science and the three new institutionalisms[J]. Political studies,1996,44(5):936-957.
[17] CRNKOVIC G D,覶譈R譈KL譈B. Robots:ethical by design[J].Ethics and information technology,2012,14(1):61-71.
[18]钟绍春,唐烨伟.人工智能时代教育创新发展的方向与路径研究[J].电化教育研究, 2018(10):15-20,40.
[19]袁振国.人工智能的时代,依然会有诗和远方[J].华东师范大学学报(教育科学版), 2017(5):27-29.
[20]乌尔里希·贝克,安东尼·吉登斯,斯科特·拉什,等.自反性现代化[M].赵文书,译.北京:商务印书馆,2001:74.
[21]何俊志,任军锋,朱德米.新制度主义政治学译文精选[M].天津:天津人民出版社, 2007:77.
[22]袁曾.人工智能有限法律人格审视[J].东方法学,2017(5):50-57.