Izvestiya of Saratov University.

Philosophy. Psychology. Pedagogy

ISSN 1819-7671 (Print)
ISSN 2542-1948 (Online)


Full text:
(downloads: 17)
Language: 
Russian
Heading: 
Article type: 
Article
UDC: 
37.013.41
EDN: 
IJIVHU

Artificial intelligence: Mythologies of social studies

Autors: 
Dydrov Artur Alexandrovich, South Ural State University (National Research University)
Abstract: 

Introduction. The social integration of complex technologies is constantly accompanied by the mythologization of innovations and the creation of special discourses that function on the basis of secondary semiotic systems. Traditionally, the trend is associated with philistine (user) discursive practices. The hypothesis of the study is that mythologization is a complex process that takes place not only within the boundaries of non-professional communities, but also in the scientific world. Theoretical analysis. The technological mythology originated in the West in the context of the social sciences and has a predominantly empirical research background. Today several variations of the conceptualization of mythology in relation to technologies have been developed, which need to be significantly supplemented and refined. Empirical analysis. The general research method is the content analysis of the Scopus scientific database in the field of social sciences. The focus was on the topic of artificial intelligence as the main convergent technology. The reference base includes scientific papers for the decade (2010–2020), united by the theme, the subject and keywords. Conclusion. Research practices in the field of artificial intelligence have almost 60 years of history, which allows us to compare the results of analytics in the future, identify genetic patterns and features of scientific discourse, contrast the results of the analysis of Western content and Russian one, by identifying key discursive specifications.

Reference: 
  1. Davis E. Tekhnognozis: mif, magiya i mistitsizm v informatsionnuyu epokhu [Techgnosis: Myth, Magic and Mysticism in the Age of Information]. Moscow, AST, 2008. 408 p. (in Russian).
  2. Dery M. Skorost’ ubeganiya: kiberkul’tura na rubezhe vekov [Escape Velocity: Cyberculture at the End of the Century]. Moscow, AST MOSKVA, 2008. 478 p. (in Russian).
  3. Mosco V. The Digital Sublime. Myth, Power, and Cyberspace. Massachusetts, The MIT Press, 2005. 230 p.
  4. Singh S. Convergence of blockchain and artificial intelligence in IoT network for the sustainable smart city. Sustainable Cities and Society, 2020, no. 63, article no. 102364. https://doi.org/10.1016/j.scs.2020.102364
  5. Natale S., Ballatore A. Imagining the thinking machine: Technological myths and the rise of artificial intelligence. Convergence: The International Journal of Research into New Media Technologiesm, 2020, no. 1, pp. 3–18. https://doi.org/10.1177/1354856517715164
  6. Duan Y. Artifi cial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda. International Journal of Information Management, 2019, vol. 48, pp. 63–71. https://doi.org/10.1016/j.ijinfomgt.2019.01.021
  7. London A. J. Artifi cial Intelligence and Black-Box Medical Decisions: Accuracy versus Explainability. Hastings Center Republic, 2019, no. 49 (1), pp. 15–21. https://doi.org/10.1002/hast.973
  8. Reis J. Artifi cial Intelligence Research and Its Contributions to the European Union’s Political Governance: Comparative Study between Member States. Social Science, 2020, no. 9 (11), pp. 1–17. https://doi.org/10.3390/socsci9110207
  9. Goralski M. Artifi cial intelligence and sustainable development. International Journal of Management Education, 2020, vol. 18, I. 1, article no. 100330. https://doi.org/10.1016/j.ijme.2019.100330
  10. Timms M. Letting Artifi cial Intelligence in Education Out of the Box: Educational Cobots and Smart Classrooms. International Journal of Artifi cial Intelligence in Education, 2016, no. 26, pp. 701–712. https://doi.org/10.1007/s40593-016-0095-y
Received: 
26.03.2023
Accepted: 
09.06.2023
Published: 
29.09.2023