万物互联时代的“算法”崇拜与资源配置变革
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摘要
随着万物互联时代的来临,人类资源配置将被各种人工智能"算法"(1)所取代。万物互联产生的数据将成为社会资源的重要形态,也是支撑人工智能"算法"的重要基础。数据资源的安全、所有权归属、开发利用效率以及保密等重要议题,将成为民族学、经济学、社会学和心理学等相关学科关注和研究的新热点。我国是一个统一的多民族国家,如何将丰富的民族多样化资源转化为支持万物互联资源网络协同优化配置人工智能"算法"的数据,需要从民族历史、文化、生物、信息处理技术等相关学科做深入的理论和实证研究。在万物互联时代,因资源配置方式与配置机制发生变革,经济学一般不再直接求解资源最优配置的策略集,更多是从理论和实证方面研究资源配置中人工智能"算法"的构造原理、构造条件与影响因素。万物互联时代,社会和谐秩序的构建,需要政府建立和维护万物互联网络的安全防护体系,并对资源配置中人工智能技术演变路径作规范和指引。
With the advent of the era of the Internet of Everything( or IoE),human resource allocation will be replaced by various"Algorithms"of artificial intelligence. The data generated by the IoE will become an important form of social resources,and also an important basis to support the"Algorithms"of artificial intelligence. The security,ownership, development and utilization efficiency,confidentiality and other important issues of data resources will become a new focus in the research of ethnology,economics,sociology,psychology and other related disciplines. China is a multi-ethnic country with abundant resources in the aspects of nature,history,linguistics,culture,religion,social customs,biological and genetic information,etc. How to transform the rich ethnic diversity resources into the data that support the collaborative optimization and allocation of artificial intelligence "algorithms"in the era of IoE requires in-depth theoretical and empirical research from related disciplines,such as ethno-history,culture,biology and information processing technology. Facing the future era of IoE,in which a huge flow of data will be created,the information needed for resource allocation will be huge and complex. The degree of information richness might be almost close to the complete information required for rational resource allocation. At that time,according to current methods of analysis,the average human brain will no longer be competent to calculate the equilibrium solution of reasonable and effective allocation of resources. Therefore,the behaviors anddecisions concerning the resource allocation of human beings will be arranged by artificial intelligence organized by various "algorithms". In general,economists will no longer directly study the strategy sets of optimal allocation of resources,but will study instead construction principles, construction conditions and influencing factors of artificial intelligence "algorithms " in resource allocation from theoretical and empirical perspectives.With the advent of the IoE era,the digital economy and the substantive economy will be deeply integrated. Cloud computing,big data and artificial intelligence will build a new infrastructure for the entire economy and society. At that time,no matter whether the main businesses belong to platformtype Internet enterprises or belong to enterprises in the Internet operating various specific industries,they will have to rely on the data generated by the IoE for their survival. As a result,both the way and mechanisms of the social resources allocation will also be completely changed. On the one hand,the mode of resource allocation will be transformed from a vertical configuration to a network cooperative configuration; on the other hand,resource allocation mechanisms will be transformed from price allocation mechanisms to network collaborative and dynamic optimization allocation mechanisms.Once human society enters the era of Io E,the data generated by IoE will become an important resource for social and economic development,and also an important link for the construction of social order. The industrial organization and behavior se-lections of human society will be based on processing and managing big data via artificial intelligence"algorithms". To some extent,the construction of the forms of human social organization will also depend on artificial intelligence "algorithms ". The government should play a guiding role in facing these important changes in the future allocation of resources. Firstly,the government should construct and improve related laws and regulations to ensure the data security of IoE. Secondly,the government should grasp the direction of the evolutionary path of artificial intelligence technology in the society of IoE,restrict the research and development of artificial intelligence technology that is destructive to human social order,encourage and support the innovation of artificial intelligence technology that is conducive to improving human social welfare and building a harmonious human social order.
With the advent of the era of the Internet of Everything( or IoE),human resource allocation will be replaced by various"Algorithms"of artificial intelligence. The data generated by the IoE will become an important form of social resources,and also an important basis to support the"Algorithms"of artificial intelligence. The security,ownership, development and utilization efficiency,confidentiality and other important issues of data resources will become a new focus in the research of ethnology,economics,sociology,psychology and other related disciplines. China is a multi-ethnic country with abundant resources in the aspects of nature,history,linguistics,culture,religion,social customs,biological and genetic information,etc. How to transform the rich ethnic diversity resources into the data that support the collaborative optimization and allocation of artificial intelligence "algorithms"in the era of IoE requires in-depth theoretical and empirical research from related disciplines,such as ethno-history,culture,biology and information processing technology. Facing the future era of IoE,in which a huge flow of data will be created,the information needed for resource allocation will be huge and complex. The degree of information richness might be almost close to the complete information required for rational resource allocation. At that time,according to current methods of analysis,the average human brain will no longer be competent to calculate the equilibrium solution of reasonable and effective allocation of resources. Therefore,the behaviors anddecisions concerning the resource allocation of human beings will be arranged by artificial intelligence organized by various "algorithms". In general,economists will no longer directly study the strategy sets of optimal allocation of resources,but will study instead construction principles, construction conditions and influencing factors of artificial intelligence "algorithms " in resource allocation from theoretical and empirical perspectives.With the advent of the IoE era,the digital economy and the substantive economy will be deeply integrated. Cloud computing,big data and artificial intelligence will build a new infrastructure for the entire economy and society. At that time,no matter whether the main businesses belong to platformtype Internet enterprises or belong to enterprises in the Internet operating various specific industries,they will have to rely on the data generated by the IoE for their survival. As a result,both the way and mechanisms of the social resources allocation will also be completely changed. On the one hand,the mode of resource allocation will be transformed from a vertical configuration to a network cooperative configuration; on the other hand,resource allocation mechanisms will be transformed from price allocation mechanisms to network collaborative and dynamic optimization allocation mechanisms.Once human society enters the era of Io E,the data generated by IoE will become an important resource for social and economic development,and also an important link for the construction of social order. The industrial organization and behavior se-lections of human society will be based on processing and managing big data via artificial intelligence"algorithms". To some extent,the construction of the forms of human social organization will also depend on artificial intelligence "algorithms ". The government should play a guiding role in facing these important changes in the future allocation of resources. Firstly,the government should construct and improve related laws and regulations to ensure the data security of IoE. Secondly,the government should grasp the direction of the evolutionary path of artificial intelligence technology in the society of IoE,restrict the research and development of artificial intelligence technology that is destructive to human social order,encourage and support the innovation of artificial intelligence technology that is conducive to improving human social welfare and building a harmonious human social order.
引文
[1][以色列]尤瓦尔·赫拉利.人类简史:从动物到上帝[M].林俊宏,译.北京:中信出版集团,2017.
[2][以色列]尤瓦尔·赫拉利.未来简史:从智人到智神[M].林俊宏,译.北京:中信出版集团,2017.
[3]何大安.互联网应用扩张与微观经济学基础[J].经济研究,2018(8):177-191.
[4]江小涓.高度联通社会中的资源重组与服务增长[J].经济研究,2017(3):4-17.
[5]张永林.网络、信息池与时间复制---网络复制经济模型[J].经济研究,2014(2):171-182.
[6]张永林.互联网、信息元与屏幕化市场---现代网络经济理论模型和应用[J].经济研究,2016(9):147-161.
[7][美]凯文·凯利.必然[M].周峰,等,译.北京:电子工业出版社,2016.
[8]自由在高处.未来已来,只是尚未流行[EB/OL].(2016-05-31)[2018-05-16].http://www.she.vc/article/18-106717-0.html.
[9]高通CEO史蒂夫.莫伦科夫:5G是一种创新的链接结构,新机遇远超3G、4G[EB/OL].(2018-11-07)[2018-11-08].http://www.tmtpost.com/nictation/3575419.html.
[10][以色列]尤瓦尔.赫拉利.今日简史[M].林俊宏,译.北京:中信出版集团,2018.
[11]叶航.人是理性、自利的吗?行为经济学对主流经济学的挑战[N].南方周末,2018-10-18.
[12]颜鹏飞.西方经济学研究大纲[J].经济学动态,1996(9):53-57.
[13]北邮老土.从第五次信息革命到第六次信息革命[EB/OL].(2017-03-28)[2018-03-20].https://www.jianshu.com/p/16e7af566cab.
He Da'an. hulianwang yingyong kuozhang yu weiguan jingjixue jichu(The Expansion of Internet Application and Fundamentals of Microeconomics).In Economic Research Journal,2018(8):177-191.
Jiang Xiaojuan. gaodu liantong shehui zhong de ziyuan chongzu yu fuwu zengzhang(Resource Regrouping and Service growth in Highly Connected Society). In Economic Research Journal,2017(3):4-17.
Kevin Kelly. biran(The Inevitable:Understanding the 12 Technological Forces That Will Shape Our Future),Zhou Feng Transl. Beijing:dianzi gongye chubanshe,2016.
Yan Pengfei. xifang jingjixue yanjiu dagang(Outline of Western Economics Research). In Economic Perspectives,1996(9):53-57.
Ye Han. renshi lixing,zili de ma? Xingwei jingjixue dui zhuliu jingjixue de tiaozhan(Are People Rational and Self-interested? Behavioral Economics Challenges Mainstream Economics). In Southern Weekend,2018-10-18.
Yuval Noah Haravi. jinri jianshi(21 Lessons fro the 21stCentury). Beijing:zhongxin chuban jituan,2018.
Yuval Noah Haravi. weilai jianshi:cong zhiren dao zhisheng(Homo Deus:A Brief History of Tomorrow). Beijing:zhongxin chuban jituan,2017.
Yuval Noah Haravi. renlei jianshi:cong dongwu dao shangdi(Sapiens:A Brief History of Humankind). Lin Junhong transl. Beijing:zhongxin chuban jituan,2017.
Zhang Yonglin. wangluo,xinxichi yu shijian fuzhi—wangluo fuzhi jingji moxing(Network,Information Pool and Time Replication:Economic Model of Network Replication). In Economic Research Journal,2014(2):171-182.
Zhang Yonglin. hulianwan,xinxiyuan yu pingmuhua shichang—xiandai wangluo jingji lilun moxin he yingyong(Internet,Information Element and Screen Market:Theoretical Model and Application of Modern Network Economy). In Economic Research Journal,2016(9):147-161
(1)根据百度百科的解释,“算法”(Algorithm)意指对解题方案作准确完整的描述,是一系列解决问题的清晰指令,显示用系统的方法描述解决问题的策略机制。一个算法的优劣可以用空间复杂度与时间复杂度来衡量。算法具有“有穷性、确切性、输入项、输出项、可行性”等几个基本特征。算法一般体现为计算机一系列运算指令和操作(如:算术运算、逻辑运算、关系运算以及数据传输)的结果。算法可大致分为:基本算法、数据结构算法、数论与代数算法、计算几何算法、图论算法、动态规划与数值分析、加密算法(如区块链中的哈希算法等)、排序算法、检索算法、随机化算法、并行算法,厄米变形模型,随机森林算法等(参见https://baike.baidu. com/item/算法/209025? fr=aladdin)。本文中的“算法”,是指对万物互联时代产生的庞大数据流,经由各种人工智能给出的解决问题的策略机制和清晰指令。
(2)认知革命(7万年前)、农业革命(1. 2万年前)、科学革命(500年前)、工业革命(200年前)、现代信息革命(72年前)(参见[以色列]尤瓦尔·赫拉利著,林俊宏译.人类简史:从动物到上帝[M].北京:中信出版集团,2017:397-398),其中,现代信息革命是以1946年计算机和互联网诞生开始计算。
(3)从广义来说,信息时代是从语言和文字诞生时就开始了,基于此我们可以把信息革命分为不同的阶段。第一次信息革命:语言的产生,大约公元前4万;第二次信息革命:文字的创造和出现,如距今约5-6千年前新石器时代中后期古中国出现的象形文字,以及公元前1600年殷商时期出现的甲骨文等;第三次信息革命:造纸和印刷术的发明,如公元105年蔡伦发明了造纸术,公元1041-1048年毕昇发明了活字印刷术,造纸和印刷术的发明推动了人类信息大量生产、规模复制、加速交流和广泛传播;第四次信息革命:电报电话和电视的发明,1837年美英两国人几乎同时发明了电报,1876年贝尔发明了电话,1923年美国人日瓦金发明了光电摄像管和电视摄像机,第四次信息革命的成果使信息传递速度加快了成千上万倍;第五次信息革命:计算机和互联网的诞生,1946年美国发明了第一台电子数字计算机,1969年美国人又发明了互联网,1971年第一次微处理芯片发明成功,通过计算机的数据处理技术与新一代通信技术的有机结合,使人类进入了数字计算和数字化时代;第六次信息革命:云计算、大数据、移动互联网、智慧城市、人工智能,目前而言,人类已进入第六次信息革命的初期,初级人工智能借助大数据不仅已在机械和装备制造、航拍、智能家居、疾病诊断等靠人类经验和简单劳动等进行工作的领域出现,甚至通过机器深度学习已开始向挑战人类智能的围棋、德州扑克、写诗、谱曲等领域进发(参见https://www. jianshu. com/p/16e7af566cab)。
(4)本文中的“万物互联”,在其他学者的文中有近似的称谓,如“高度互联”(江小涓,2017)或“互联网应用扩张”(何大安,2018)。
(5)针对数据与信息的关系,有学者指出,虽然主流观点把数据归为信息范畴,但从信息获取途径来看,也可把信息归为数据范畴,不同的信息本质上是不同的数据表现形态。因为无论什么信息都是对数据进行挖掘、加工、处理后的结果(参见何大安.互联网应用扩张与微观经济学基础[J].经济研究,2018(8):182)。本文也认为,信息就是不同的数据表现,特别是在万物互联时代,人工智能“算法”完全是建立在对各种信息加工处理后形成的数据基础上的。
(6)例如帕累托(Pareto,1909)在瓦尔拉斯等基于“理性”“自利”等假设下建立的一般均衡分析基础上,根据市场交易中需求函数满足齐次条件的预算约束均衡,提出了帕累托最优配置模型;哈耶克(1945)还分析了信息约束条件对价格机制有效配置资源的作用等(参见何大安.互联网应用扩张与微观经济学基础[J].经济研究,2018(8):186)。
[2][以色列]尤瓦尔·赫拉利.未来简史:从智人到智神[M].林俊宏,译.北京:中信出版集团,2017.
[3]何大安.互联网应用扩张与微观经济学基础[J].经济研究,2018(8):177-191.
[4]江小涓.高度联通社会中的资源重组与服务增长[J].经济研究,2017(3):4-17.
[5]张永林.网络、信息池与时间复制---网络复制经济模型[J].经济研究,2014(2):171-182.
[6]张永林.互联网、信息元与屏幕化市场---现代网络经济理论模型和应用[J].经济研究,2016(9):147-161.
[7][美]凯文·凯利.必然[M].周峰,等,译.北京:电子工业出版社,2016.
[8]自由在高处.未来已来,只是尚未流行[EB/OL].(2016-05-31)[2018-05-16].http://www.she.vc/article/18-106717-0.html.
[9]高通CEO史蒂夫.莫伦科夫:5G是一种创新的链接结构,新机遇远超3G、4G[EB/OL].(2018-11-07)[2018-11-08].http://www.tmtpost.com/nictation/3575419.html.
[10][以色列]尤瓦尔.赫拉利.今日简史[M].林俊宏,译.北京:中信出版集团,2018.
[11]叶航.人是理性、自利的吗?行为经济学对主流经济学的挑战[N].南方周末,2018-10-18.
[12]颜鹏飞.西方经济学研究大纲[J].经济学动态,1996(9):53-57.
[13]北邮老土.从第五次信息革命到第六次信息革命[EB/OL].(2017-03-28)[2018-03-20].https://www.jianshu.com/p/16e7af566cab.
He Da'an. hulianwang yingyong kuozhang yu weiguan jingjixue jichu(The Expansion of Internet Application and Fundamentals of Microeconomics).In Economic Research Journal,2018(8):177-191.
Jiang Xiaojuan. gaodu liantong shehui zhong de ziyuan chongzu yu fuwu zengzhang(Resource Regrouping and Service growth in Highly Connected Society). In Economic Research Journal,2017(3):4-17.
Kevin Kelly. biran(The Inevitable:Understanding the 12 Technological Forces That Will Shape Our Future),Zhou Feng Transl. Beijing:dianzi gongye chubanshe,2016.
Yan Pengfei. xifang jingjixue yanjiu dagang(Outline of Western Economics Research). In Economic Perspectives,1996(9):53-57.
Ye Han. renshi lixing,zili de ma? Xingwei jingjixue dui zhuliu jingjixue de tiaozhan(Are People Rational and Self-interested? Behavioral Economics Challenges Mainstream Economics). In Southern Weekend,2018-10-18.
Yuval Noah Haravi. jinri jianshi(21 Lessons fro the 21stCentury). Beijing:zhongxin chuban jituan,2018.
Yuval Noah Haravi. weilai jianshi:cong zhiren dao zhisheng(Homo Deus:A Brief History of Tomorrow). Beijing:zhongxin chuban jituan,2017.
Yuval Noah Haravi. renlei jianshi:cong dongwu dao shangdi(Sapiens:A Brief History of Humankind). Lin Junhong transl. Beijing:zhongxin chuban jituan,2017.
Zhang Yonglin. wangluo,xinxichi yu shijian fuzhi—wangluo fuzhi jingji moxing(Network,Information Pool and Time Replication:Economic Model of Network Replication). In Economic Research Journal,2014(2):171-182.
Zhang Yonglin. hulianwan,xinxiyuan yu pingmuhua shichang—xiandai wangluo jingji lilun moxin he yingyong(Internet,Information Element and Screen Market:Theoretical Model and Application of Modern Network Economy). In Economic Research Journal,2016(9):147-161
(1)根据百度百科的解释,“算法”(Algorithm)意指对解题方案作准确完整的描述,是一系列解决问题的清晰指令,显示用系统的方法描述解决问题的策略机制。一个算法的优劣可以用空间复杂度与时间复杂度来衡量。算法具有“有穷性、确切性、输入项、输出项、可行性”等几个基本特征。算法一般体现为计算机一系列运算指令和操作(如:算术运算、逻辑运算、关系运算以及数据传输)的结果。算法可大致分为:基本算法、数据结构算法、数论与代数算法、计算几何算法、图论算法、动态规划与数值分析、加密算法(如区块链中的哈希算法等)、排序算法、检索算法、随机化算法、并行算法,厄米变形模型,随机森林算法等(参见https://baike.baidu. com/item/算法/209025? fr=aladdin)。本文中的“算法”,是指对万物互联时代产生的庞大数据流,经由各种人工智能给出的解决问题的策略机制和清晰指令。
(2)认知革命(7万年前)、农业革命(1. 2万年前)、科学革命(500年前)、工业革命(200年前)、现代信息革命(72年前)(参见[以色列]尤瓦尔·赫拉利著,林俊宏译.人类简史:从动物到上帝[M].北京:中信出版集团,2017:397-398),其中,现代信息革命是以1946年计算机和互联网诞生开始计算。
(3)从广义来说,信息时代是从语言和文字诞生时就开始了,基于此我们可以把信息革命分为不同的阶段。第一次信息革命:语言的产生,大约公元前4万;第二次信息革命:文字的创造和出现,如距今约5-6千年前新石器时代中后期古中国出现的象形文字,以及公元前1600年殷商时期出现的甲骨文等;第三次信息革命:造纸和印刷术的发明,如公元105年蔡伦发明了造纸术,公元1041-1048年毕昇发明了活字印刷术,造纸和印刷术的发明推动了人类信息大量生产、规模复制、加速交流和广泛传播;第四次信息革命:电报电话和电视的发明,1837年美英两国人几乎同时发明了电报,1876年贝尔发明了电话,1923年美国人日瓦金发明了光电摄像管和电视摄像机,第四次信息革命的成果使信息传递速度加快了成千上万倍;第五次信息革命:计算机和互联网的诞生,1946年美国发明了第一台电子数字计算机,1969年美国人又发明了互联网,1971年第一次微处理芯片发明成功,通过计算机的数据处理技术与新一代通信技术的有机结合,使人类进入了数字计算和数字化时代;第六次信息革命:云计算、大数据、移动互联网、智慧城市、人工智能,目前而言,人类已进入第六次信息革命的初期,初级人工智能借助大数据不仅已在机械和装备制造、航拍、智能家居、疾病诊断等靠人类经验和简单劳动等进行工作的领域出现,甚至通过机器深度学习已开始向挑战人类智能的围棋、德州扑克、写诗、谱曲等领域进发(参见https://www. jianshu. com/p/16e7af566cab)。
(4)本文中的“万物互联”,在其他学者的文中有近似的称谓,如“高度互联”(江小涓,2017)或“互联网应用扩张”(何大安,2018)。
(5)针对数据与信息的关系,有学者指出,虽然主流观点把数据归为信息范畴,但从信息获取途径来看,也可把信息归为数据范畴,不同的信息本质上是不同的数据表现形态。因为无论什么信息都是对数据进行挖掘、加工、处理后的结果(参见何大安.互联网应用扩张与微观经济学基础[J].经济研究,2018(8):182)。本文也认为,信息就是不同的数据表现,特别是在万物互联时代,人工智能“算法”完全是建立在对各种信息加工处理后形成的数据基础上的。
(6)例如帕累托(Pareto,1909)在瓦尔拉斯等基于“理性”“自利”等假设下建立的一般均衡分析基础上,根据市场交易中需求函数满足齐次条件的预算约束均衡,提出了帕累托最优配置模型;哈耶克(1945)还分析了信息约束条件对价格机制有效配置资源的作用等(参见何大安.互联网应用扩张与微观经济学基础[J].经济研究,2018(8):186)。