Beyond Privacy: Protecting Data Interests in the Age of Artificial Intelligence

Bartlett, Matt

doi:10.5204/lthj.1595

Cited by 6 publications

(3 citation statements)

References 5 publications

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“…Bartlett found that the way tech companies collect and process user data creates serious challenges for data processing. Companies in the modern data economy use sophisticated algorithms to mine vast amounts of data to produce valuable behavioral predictions [9]. Based on the era of artificial intelligence, scholars have proposed various intelligent classification algorithms and decision-making algorithms.…”

Section: Related Workmentioning

confidence: 99%

Defining the Environmental Public Interest Litigation in the Era of Artificial Intelligence

Wei

Li²

2022

Mobile Information Systems

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Environmental public interest litigation is a category of modern litigation that aims to protect the rights and welfares of the public environment. In China, environmental public interest litigation is a common mean to protect the environment and has a vital role in protecting the environment. This paper aims to study how to use the advantages of the artificial intelligence era to study the definition of environmental public interest litigation. This paper proposes how to define environmental public interest litigation and proposes a data mining classification algorithm based on the era of artificial intelligence to analyze the definition of public interest litigation. The experimental results of this paper show that with the promulgation and implementation of the new environmental protection law in 2016, the number of environmental public interest litigation cases nationwide has increased significantly compared with previous years. There are 43,589 environmental public interest litigation cases nationwide, and the difficulty of work is 38%. It can be seen that public interest litigation has become one of the judicial channels generally accepted by the public. It has become a powerful weapon for safeguarding the interests of the public environment. The use of the data mining classification algorithm based on the era of artificial intelligence can make the case definition of environmental public interest litigation easier, thus improving work efficiency.

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Section: Related Workmentioning

confidence: 99%

Defining the Environmental Public Interest Litigation in the Era of Artificial Intelligence

Wei

Li²

2022

Mobile Information Systems

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“…There may be inappropriate training methods. Although coaches with short teaching years do not have more teaching experience and lack practical experience, who will spend more time with students when teaching, they are often just retired as athletes or just graduated from colleges, and have more knowledge about the latest and most scientific training content and methods [23]. The reason why the overall teaching years of coaches in the X club is not long is because the age of the coaches is younger.…”

Section: Results Of Football Training and Physical Educationmentioning

confidence: 99%

Practice of Artificial Intelligence Technology Based on Big Data in Football Training and Physical Education

2024

FSR

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Soccer is a sport in which the feet are mainly used to control the ball. Football today generally refers to modern football, which originated in China's "Cuju". It is an official event of the Olympic Games and a national sport that the public loves more. This paper aims to research and analyze the practice of football training and physical education through the football and related information obtained by big data artificial intelligence technology, so as to obtain practical conclusions. This paper gives a general introduction to the big data artificial intelligence technology, analyzes the relevant information of athletes in football training and actual physical education, and combines big data artificial intelligence technology with practical research in football training and physical education. Based on the experiments in this paper, it can be seen that the training intensity of the coaches arranged twice a week in the X football club was 85%. The coaches who arranged 3 times a week had a moderate to high exercise intensity of 65%. For coaches who arranged 4 or more times a week, the moderate exercise intensity was 50%. The results of this paper showed that the analysis of practical research in football training and physical education based on big data artificial intelligence technology was more abundant and scientific than the data obtained using traditional analysis methods.

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“…Artificial intelligence in banking uses data from customer bank accounts and other financial service providers. Banks' mobile applications (Mhlanga, 2020) and social media (Bartlett, 2021) are a source of much valuable customer data. Consumers, while agreeing to share a lot of data about Pobrane z czasopisma Annales H -Oeconomia http://oeconomia.annales.umcs.pl Data: 09/01/2023 06:19:44 U M C S themselves, expect in return the protection of their privacy, i.e.…”

Section: Literature Review and Hypotheses Developmentmentioning

confidence: 99%

Demographic and Socio-Economic Factors as Barriers to Robo-Advisory Acceptance in Poland

Piotrowski

2022

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Theoretical background: One manifestation of the use of artificial intelligence technology in financial services is robo-advisory. Automated assistants are used in the area of communication with consumers and the sale of financial products. The development of robo-advisory services may contribute to increasing the availability of financial services and the cost efficiency of banks' operations. So far, however, robo-advisory has not been widely used in bank services, and the reasons for this can be seen in the lack of wide acceptance of robo-advisory by bank customers, among other things. Purpose of the article:The aim of this paper is to identify barriers to the acceptance of robo-advisory in the services of banks operating in Poland. Variables relating to the demographic and socio-economic characteristics of consumers were analysed. Knowledge in this area can provide banks with a practical guideline for activities aimed at increasing acceptance of artificial intelligence technology and wider use of robo-advisory in financial services. Research methods: The paper uses the results of a survey conducted in October 2020 regarding the application of artificial intelligence technology in the banking sector in Poland. The survey included a representative Pobrane z czasopisma Annales H -Oeconomia http://oeconomia.annales.umcs.pl Data: 09/01/2023 06:19:44 U M C S 110 DARIUSZ PIOTROWSKIsample of 911 Polish citizens aged 18-65. A multinomial logit model was employed to identify variables that represent significant barriers to robo-advisory acceptance in financial services. Main findings: The conducted research helped identify the barriers to acceptance of robo-advisory among consumers in Poland. A low propensity to use robo-advisory in bank services is characteristic of respondents from older age groups, as well as those who do not show a predilection for testing new technological solutions. Lack of experience in using investment advisory services and customer concerns about the misuse of personal data by banks are also significant barriers.

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Beyond Privacy: Protecting Data Interests in the Age of Artificial Intelligence

Cited by 6 publications

References 5 publications

Defining the Environmental Public Interest Litigation in the Era of Artificial Intelligence

Defining the Environmental Public Interest Litigation in the Era of Artificial Intelligence

Practice of Artificial Intelligence Technology Based on Big Data in Football Training and Physical Education

Demographic and Socio-Economic Factors as Barriers to Robo-Advisory Acceptance in Poland

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