scholarly journals The impact of new relationship learning on artificial intelligence technology innovation

2021 ◽  
Vol 5 (1) ◽  
pp. 2-8
Author(s):  
Ying Xue ◽  
Chao Fang ◽  
Ying Dong
Keyword(s):  
Artificial Intelligence ◽  
Technology Innovation ◽  
Artificial Intelligence Technology ◽  
The Impact

scholarly journals Research on the Evaluation and Optimization Method of the Impact of Chorus Education on University Culture Based on Coevolution Model in the Background of Artificial Intelligence

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Qingna Lin ◽  
Lizheng Zhuo
Keyword(s):  
Artificial Intelligence ◽  
Evaluation System ◽  
Quantitative Methods ◽  
Comprehensive Evaluation ◽  
Colleges And Universities ◽  
Practical Significance ◽  
University Culture ◽  
Research Perspectives ◽  
Artificial Intelligence Technology ◽  
The Impact

The development of artificial intelligence technology is a field where all walks of life need to carry out in-depth research in the future, and the introduction of artificial intelligence technology in the field of university evaluation has become an inevitable trend. Through the collection and collation of the literature at home and abroad, the influence of chorus education on college culture in China has long remained in qualitative and experiential judgment and the significance and value of chorus education to colleges and universities are relatively single. Therefore, it is of great innovative value and practical significance to establish a scientific, systematic, and comprehensive evaluation mechanism for the impact of chorus education on university culture and to scientifically analyze key issues, establish evaluation criteria, and inject new research perspectives into the promotion of chorus education in colleges and universities in China, combining with the mature coevolution theoretical model of management science. It is of great innovative value and significance to combine the DEMATEL research method with the current practice of promoting chorus education in China’s colleges and universities and to systematically and comprehensively construct the evaluation system and research paradigm in line with chorus education by using the qualitative and quantitative methods.

scholarly journals Empirical model for analysis of the dynamics of algorithmization (artificial intelligence technology) in the field of security by the example of the USA

2021 ◽  
Author(s):  
A.M. Turobov ◽  
M.G. Mironyuk
Keyword(s):  
Artificial Intelligence ◽  
Empirical Model ◽  
Digital Technologies ◽  
The State ◽  
Security System ◽  
State Security ◽  
The Usa ◽  
Artificial Intelligence Technology ◽  
Definition Of ◽  
The Impact

How does the state security system evolve under the influence of the artificial intelligence technology? To answer this question, an empirical model is proposed. The model evaluates the state security system (by the example of the USA) using the security consistency parameter, which estimates how the state perceives threats (indicator of threats) and whether the state has the necessary capabilities to counter them (indicator of capabilities) in relation to the artificial intelligence technology. The model (as well as the conceptualization of the artificial intelligence technology in the context of the security domain) provides evidence of how security transformations occur. It serves as a tool for studying the corresponding changes and assessing the state security system. It is necessary to indicate the limitation of the study: we do not consider direct military applications in the field of automation and algorithms (artificial intelligence technology). The validation of the empirical model has been undertaken using the case of the USA (eight-time intervals are subject to analysis, namely: 1999, 2002, 2006, 2010, 2012, 2015, 2017, 2019). With the development of the technology itself, the “interest” of the state and the definition of threats, as well as the rapid growth of the capabilities of the artificial intelligence technology (coincides with the years of maximum progress in computing power and the introduction of new algorithms) are growing, and since 2012, the dynamic has been linear, since more new “discoveries” have contributed to evolutionary rather than “revolutionary” growth trajectory. The developed model is scalable. This feature may be useful in the empirical security studies: the artificial intelligence technology within the model can be replaced with other types of digital technologies (for example, big data, cloud computing or 5 g connection technologies, etc.); thus, empirical models of security consistency under the impact of other technologies can be developed. The approach proposed allows to under take cross-country comparisons with respect to specific types of digital technologies and their interactions with the security domain.

scholarly journals Legal forms and ways of application of artificial intelligence technology in making corporate decisions by the board of directors: problems and prospects

2021 ◽  
Vol 106 ◽  
pp. 02012
Author(s):  
Olga Sushkova
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Corporate Governance ◽  
Board Of Directors ◽  
Three Dimensions ◽  
Corporate Decisions ◽  
The Board Of Directors ◽  
Artificial Intelligence Technology ◽  
Legal Forms ◽  
The Impact

This study investigates the impact of scientific and technological advances and adaptation of artificial intelligence on corporate governance practices. It applies or can be applied in three dimensions - business, technology, and society. Therefore, to assess the necessity, feasibility, effectiveness, and responsibility of decision-making automation at the Board of Directors (supervisory body of a legal entity) to ensure effective corporate governance, it is necessary to consider all normative regulators in the field of corporate law. Based on an assessment of the potential and limitations of human and machine learning for effective decision-making at the level of the collegial governance body, the Board of Directors, the paper proposes five AI-based governance scenarios, i.e., supportive, augmented, enhanced, autonomous, and autopoietic, that can shape the governance of organizations today, tomorrow, and in the future. It is important to understand the implications of such AI-enabled governance in the areas where the Board is empowered to make certain corporate decisions.

Artificial Intelligence in Accounting and Finance: Meta-Analysis

2021 ◽  
Vol 3 (1) ◽  
pp. 56-79
Author(s):  
Oguljan Berdiyeva ◽  
Muhammad Umar Islam ◽  
Mitra Saeedi
Keyword(s):  
Artificial Intelligence ◽  
Customer Service ◽  
Intelligent Agents ◽  
Meta Analysis ◽  
Traditional System ◽  
Finance Industry ◽  
Key Points ◽  
Artificial Intelligence Technology ◽  
The Impact ◽  
Artificial Intelligence Systems

The use of the traditional system is declined greatly and with a modernization of the accounting and finance process there have been a great deal of change, and these improvements are beneficial to the accounting and finance industry. Adopting Artificial Intelligence applications such as Expert systems for audit and tax, Intelligent Agents for customer service, Machine Learning for decision making, etc. can lead a great benefit by reducing errors and increasing the efficiency of the accounting and finance processes. To keep ensuring a transparent and replicable process, we have conducted a meta-analysis. The database search was between the years 1989-2020 and reviewed 150 research papers. As meta-analysis results show, the majority of researches illustrate a positive effect of the impact of AI systems in the accounting and finance process. Key points:  Meta-Analysis has been applied for emphasizing positive results of the impact of Artificial Intelligence systems in the Accounting and Finance process.  Implementing Artificial Intelligence systems in Accounting and Finance process can increase the efficiency of the process.  Artificial Intelligence technology has been influential in all the areas of accounting, which are especially concerned with knowledge

scholarly journals Analyzing Sentiments of German Job References

2020 ◽  
Vol 1 (1) ◽  
pp. 1-22
Keyword(s):  
Artificial Intelligence ◽  
Imbalanced Data ◽  
Machine Learning Algorithms ◽  
The Other ◽  
Training Data ◽  
Data Sets ◽  
Artificial Intelligence Technology ◽  
Research Questions ◽  
The One ◽  
The Impact

Filling a vacancy takes a lot of (costly) time. Automated preprocessing of applications using artificial intelligence technology can help to save time, e.g., by analyzing applications using machine learning algorithms. We investigate whether such systems are potentially biased in terms of gender, origin, and nobility. Using a corpus of common German reference letter sentences, we investigate two research questions. First, we test sentiment analysis systems offered by Amazon, Google, IBM and Microsoft. All tested services rate the sentiment of the same template sentences very inconsistently and biased at least with regard to gender. Second, we examine the impact of (im-)balanced training data sets on classifiers, which are trained to estimate the sentiment of sentences from our corpus. This experiment shows that imbalanced data, on the one hand, lead to biased results, but on the other hand, under certain conditions, can lead to fair results.

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