“Smart” outsourcing in support of the humanization of entrepreneurship in the artificial intelligence economy

Matytsin, Denis E.; Dzedik, Valentin A.; Makeeva, Galina A.; Boldyreva, Saglar B.

doi:10.1057/s41599-022-01493-x

Cited by 9 publications

(4 citation statements)

References 55 publications

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“…This item captures individuals’ overall evaluation of the impact of AI technology on society and humanity as a whole. The item is grounded in the literature on the social implications of AI ( Brynjolfsson and McAfee, 2014 ) and reflects the belief that AI can contribute to societal progress and well-being by addressing complex global challenges, improving healthcare ( Loh et al, 2022 ), enhancing education ( Xia et al, 2022 ; Yang, 2022 ), and fostering economic growth ( Jones, 2022 ; Matytsin et al, 2023 ).…”

Section: Methodsmentioning

confidence: 99%

Development and validation of the AI attitude scale (AIAS-4): a brief measure of general attitude toward artificial intelligence

Grassini

2023

Front. Psychol.

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The rapid advancement of artificial intelligence (AI) has generated an increasing demand for tools that can assess public attitudes toward AI. This study proposes the development and the validation of the AI Attitude Scale (AIAS), a concise self-report instrument designed to evaluate public perceptions of AI technology. The first version of the AIAS that the present manuscript proposes comprises five items, including one reverse-scored item, which aims to gauge individuals’ beliefs about AI’s influence on their lives, careers, and humanity overall. The scale is designed to capture attitudes toward AI, focusing on the perceived utility and potential impact of technology on society and humanity. The psychometric properties of the scale were investigated using diverse samples in two separate studies. An exploratory factor analysis was initially conducted on a preliminary 5-item version of the scale. Such exploratory validation study revealed the need to divide the scale into two factors. While the results demonstrated satisfactory internal consistency for the overall scale and its correlation with related psychometric measures, separate analyses for each factor showed robust internal consistency for Factor 1 but insufficient internal consistency for Factor 2. As a result, a second version of the scale is developed and validated, omitting the item that displayed weak correlation with the remaining items in the questionnaire. The refined final 1-factor, 4-item AIAS demonstrated superior overall internal consistency compared to the initial 5-item scale and the proposed factors. Further confirmatory factor analyses, performed on a different sample of participants, confirmed that the 1-factor model (4-items) of the AIAS exhibited an adequate fit to the data, providing additional evidence for the scale’s structural validity and generalizability across diverse populations. In conclusion, the analyses reported in this article suggest that the developed and validated 4-items AIAS can be a valuable instrument for researchers and professionals working on AI development who seek to understand and study users’ general attitudes toward AI.

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Section: Methodsmentioning

confidence: 99%

Development and validation of the AI attitude scale (AIAS-4): a brief measure of general attitude toward artificial intelligence

Grassini

2023

Front. Psychol.

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“…Unlike Hong and Xiao (2024), the AI economy does not influence the environmental costs of economic growth. Confirming Matytsin et al (2023), the AI economy creates advantages for the quality of life.…”

Section: Discussionmentioning

confidence: 97%

“…The existing literature determines the expected advantages (implications) of the development of the AI economy, which are manifested to a different extent in different countries. These advantages include the following:  Improvement of labour productivity due to automatization (Tokunova et al, 2023);  Support for knowledge-intensive employment due to the increased technical complexity of labour with the use of AI and the necessity for manifesting innovative activity (Zhang, 2023);  Technological complications of the manufactured and exported products (Lu et al, 2024);  Improvement of product quality due to high-precision smart production and automatized quality control (Woźniak et al, 2022;Zimon et al, 2022);  Raising the quality of life due to the growth of affordability of goods and services and intellectual support for their selection (Matytsin et al, 2023). A potential drawback of the AI economy is the risk of an increase in the environmental costs of economic growth (Hong and Xiao, 2024).…”

Section: Literature Reviewmentioning

confidence: 99%

Untitled

2024

J. Tr., Chal. Art. Intell.

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This paper is devoted to determining the trends of the AI economy in Russia. The method of trend analysis was used to find the dynamics of change in the values of the indicators of development of the AI economy in Russia. As a result, we revealed the specific features of its Russian model. The first feature is that in Russia, the key participant of the AI economy is the government, and the role of business, despite its being a secondary player, constantly grows. The second feature is that Russia successfully strengthens technological sovereignty in the sphere of the AI economy. The main conclusion is that in the Russian model, the advantages of the AI economy are connected with the growth of the share of knowledge-intensive employment and an increase in the quality of life, and its risks consist in a possible slowdown of the growth rate of labour productivity and reduction of the quality of products. The managerial significance of the paper is that the compiled econometric model generalised the leading experience of the top 30 AI economies in the world in 2023 and disclosed the cause-and-effect relationships of its development. The practical significance is that the authors' forecast outlined the perspective of the development of the AI economy in Russia in the Decade of Science and Technologies until 2031.

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“…Currently, there are a number of academic articles that describe the use of AI for business applications (Janiesch et al, 2021; Matytsin et al, 2023; Minkkinen et al, 2022; Mullins et al, 2021; Pai & Chandra, 2022; Raisch & Krakowski, 2021). Most of them have even outlined their strengths and weaknesses (Dauvergne, 2022; Huang & Rust, 2022).…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence governance: Ethical considerations and implications for social responsibility

Camilleri

2023

Expert Systems

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A number of articles are increasingly raising awareness on the different uses of artificial intelligence (AI) technologies for customers and businesses. Many authors discuss about their benefits and possible challenges. However, for the time being, there is still limited research focused on AI principles and regulatory guidelines for the developers of expert systems like machine learning (ML) and/or deep learning (DL) technologies. This research addresses this knowledge gap in the academic literature. The objectives of this contribution are threefold: (i) It describes AI governance frameworks that were put forward by technology conglomerates, policy makers and by intergovernmental organizations, (ii) It sheds light on the extant literature on ‘AI governance’ as well as on the intersection of ‘AI’ and ‘corporate social responsibility’ (CSR), (iii) It identifies key dimensions of AI governance, and elaborates about the promotion of accountability and transparency; explainability, interpretability and reproducibility; fairness and inclusiveness; privacy and safety of end users, as well as on the prevention of risks and of cyber security issues from AI systems. This research implies that all those who are involved in the research, development and maintenance of AI systems, have social and ethical responsibilities to bear toward their consumers as well as to other stakeholders in society.

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“Smart” outsourcing in support of the humanization of entrepreneurship in the artificial intelligence economy

Cited by 9 publications

References 55 publications

Development and validation of the AI attitude scale (AIAS-4): a brief measure of general attitude toward artificial intelligence

Development and validation of the AI attitude scale (AIAS-4): a brief measure of general attitude toward artificial intelligence

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Artificial intelligence governance: Ethical considerations and implications for social responsibility

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