Using Automated Digital Systems to Thoroughly Regulate Social Governance: Monitoring and Behavior Modification through Data-driven Algorithmic Decision-Making

2019 ◽  
Vol 11 (1) ◽  
pp. 63
2013 ◽  
Vol 344 ◽  
pp. 242-245
Author(s):  
Hai Tao Yang ◽  
Peng Wei Li ◽  
Hong Li Zhao

This paper studies how to use the cognitive model to model the behavioral decision-making for the tactical level simulation. The decision making process includes initial behavior planning and behavior modification. This method has the advantages of accuracy and real-time, this makes the behaviors of the simulation entity more realistic and improves the credibility of simulation.


2005 ◽  
Vol 10 (1) ◽  
pp. 25-38 ◽  
Author(s):  
Hilde Iversen ◽  
Torbjørn Rundmo ◽  
Hroar Klempe

Abstract. The core aim of the present study is to compare the effects of a safety campaign and a behavior modification program on traffic safety. As is the case in community-based health promotion, the present study's approach of the attitude campaign was based on active participation of the group of recipients. One of the reasons why many attitude campaigns conducted previously have failed may be that they have been society-based public health programs. Both the interventions were carried out simultaneously among students aged 18-19 years in two Norwegian high schools (n = 342). At the first high school the intervention was behavior modification, at the second school a community-based attitude campaign was carried out. Baseline and posttest data on attitudes toward traffic safety and self-reported risk behavior were collected. The results showed that there was a significant total effect of the interventions although the effect depended on the type of intervention. There were significant differences in attitude and behavior only in the sample where the attitude campaign was carried out and no significant changes were found in the group of recipients of behavior modification.


2020 ◽  
Vol 48 (7) ◽  
pp. 1-12
Author(s):  
Ran Xiong ◽  
Ping Wei

Confucian culture has had a deep-rooted influence on Chinese thinking and behavior for more than 2,000 years. With a manually created Confucian culture database and the 2017 China floating population survey, we used empirical analysis to test the relationship between Confucian culture and individual entrepreneurial choice using data obtained from China's floating population. After using the presence and number of Confucian schools and temples, and of chaste women as instrumental variables to counteract problems of endogeneity, we found that Confucian culture had a significant role in promoting individuals' entrepreneurial decision making among China's floating population. The results showed that, compared with those from areas of China not strongly influenced by Confucian culture, individuals from areas that are strongly influenced by Confucian culture were more likely to choose entrepreneurship as their occupation choice. Our findings reveal cultural factors that affect individual entrepreneurial behavior, and also illustrate the positive role of Confucianism as a representative of the typical cultures of the Chinese nation in the 21st century.


This book explores the intertwining domains of artificial intelligence (AI) and ethics—two highly divergent fields which at first seem to have nothing to do with one another. AI is a collection of computational methods for studying human knowledge, learning, and behavior, including by building agents able to know, learn, and behave. Ethics is a body of human knowledge—far from completely understood—that helps agents (humans today, but perhaps eventually robots and other AIs) decide how they and others should behave. Despite these differences, however, the rapid development in AI technology today has led to a growing number of ethical issues in a multitude of fields, ranging from disciplines as far-reaching as international human rights law to issues as intimate as personal identity and sexuality. In fact, the number and variety of topics in this volume illustrate the width, diversity of content, and at times exasperating vagueness of the boundaries of “AI Ethics” as a domain of inquiry. Within this discourse, the book points to the capacity of sociotechnical systems that utilize data-driven algorithms to classify, to make decisions, and to control complex systems. Given the wide-reaching and often intimate impact these AI systems have on daily human lives, this volume attempts to address the increasingly complicated relations between humanity and artificial intelligence. It considers not only how humanity must conduct themselves toward AI but also how AI must behave toward humanity.


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