A measurement framework of crowd intelligence

被引:1
作者
Feng Y. [1 ]
Qiu L. [2 ]
Sun B. [2 ]
机构
[1] School of Information, Central University of Finance and Economics, Beijing
[2] China Center for Internet Economy Research, Central University of Finance and Economics, Beijing
基金
中国国家自然科学基金;
关键词
Crowd cyber; Crowd intelligence; Crowd science; Intelligence measurement;
D O I
10.1108/IJCS-09-2020-0015
中图分类号
学科分类号
摘要
Purpose: The originality of the crowd cyber system lies in the fact that it possesses the intelligence of multiple groups including intelligence of people, intelligence of objects and intelligence of machines. However, quantitative analysis of the level of intelligence is not sufficient, due to many limitations, such as the unclear definition of intelligence and the inconformity of human intelligence quotient (IQ) test and artificial intelligence assessment methods. This paper aims to propose a new crowd intelligence measurement framework from the harmony of adaption and practice to measure intelligence in crowd network. Design/methodology/approach: The authors draw on the ideas of traditional Confucianism, which sees intelligence from the dimensions of IQ and effectiveness. First, they clarify the related concepts of intelligence and give a new definition of crowd intelligence in the form of a set. Second, they propose four stages of the evolution of intelligence from low to high, and sort out the dilemma of intelligence measurement at the present stage. Third, they propose a framework for measuring crowd intelligence based on two dimensions. Findings: The generalized IQ operator model is optimized, and a new IQ algorithm is proposed. Individuals with different IQs can have different relationships, such as cooperative, competitive, antagonistic and so on. The authors point out four representative forms of intelligence as well as its evolution stages. Research limitations/implications: The authors, will use more rigorous mathematical symbols to represent the logical relationships between different individuals, and consider applying the measurement framework to a real-life situation to enrich the research on crowd intelligence in the further study. Originality/value: Intelligence measurement is one of foundations of crowd science. This research lays the foundation for studying the interaction among human, machine and things from the perspective of crowd intelligence, which owns significant scientific value. © 2020, Yiqiang Feng, Leiju Qiu and Baowen Sun.
引用
收藏
页码:81 / 91
页数:10
相关论文
共 21 条
[11]  
Kaplan A., Haenlein M., Siri, Siri, in my hand: who's the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence, Business Horizons, 62, 1, pp. 15-25, (2019)
[12]  
Lee T., Nam J., Han D., Kim S., In H.P., Developer micro interaction metrics for software defect prediction, IEEE Transactions on Software Engineering, 42, 11, pp. 1015-1035, (2016)
[13]  
Li W., Wu W.J., Wang H.M., Cheng X.Q., Chen H.J., Zhou Z.H., Ding R., Crowd intelligence in AI 2.0 era, Frontiers of Information Technology and Electronic Engineering, 18, 1, pp. 15-43, (2017)
[14]  
Liu D., A study on the generalized intelligence assessment, 2009 International Forum on Computer Science-Technology and Applications, pp. 78-81, (2009)
[15]  
Malone T.W., Bernstein M.S., Introduction, Collective Intelligence Handbook, (2015)
[16]  
Malone T.W., Laubacher R., Dellarocas C.N., Harnessing crowds: mapping the genome of collective intelligence, (2009)
[17]  
Poole D., Mackworth A., Goebel R., Computational Intelligence: A Logical Approach, (1998)
[18]  
Qiu L., Zhao Y., Liu Q., Sun B., Wu X., Transaction modes and rules in the perspective of crowd science, Proceedings of the 3rd International Conference on Crowd Science and Engineering (ICCSE’18), Article 14, pp. 1-5, (2018)
[19]  
Woolley A.W., Kim Y., Malone T.W., Measuring collective intelligence in groups: a reply to credé and howardson, (2018)
[20]  
Woolley A.W., Chabris C.F., Pentland A., Hashmi N., Malone T.W., Evidence for a collective intelligence factor in the performance of human groups, Science, 330, 6004, pp. 686-688, (2010)