Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Lapina, Maria; Mary Anita, E.A.; Bagautdinova, Alina; Gordova, Marina Title A name given to the resource Research of Prospects and Challenges in Artificial Intelligence Technology Teaching and Learning Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems;Volume;1616 LNNS;pp.266-276 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-032-04365-8_27" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-032-04365-8_27</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105019522955?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105019522955?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Lapina M., North-Caucasus Federal University, Stavropol, 3550017, Russian Federation; Mary Anita E.A., Christ University, Bangalore, India; Bagautdinova A., North-Caucasus Federal University, Stavropol, 3550017, Russian Federation; Gordova M., Financial University Under the Government of the Russian Federation, Moscow, 125993, Russian Federation Description An account of the resource Recently, knowledge in the field of artificial intelligence in order to modernize various aspects of human activity has played a significant role. The exploration of the opportunities and difficulties associated with the development of artificial intelligence technologies is becoming an important area of research, as it profoundly affects our perception of work, education, medicine and other spheres of existence. New methods of machine learning, deep learning and reinforcement learning are being developed. These technologies are changing our understanding of how machines can learn and adapt to the world around them. The application of artificial intelligence covers many areas, including healthcare, finance, education and industry. In medicine, for example, AI can improve diagnostic accuracy and develop customized treatments. In education, it is possible to create personalized learning plans for each student. While in industry, artificial intelligence technologies are able to optimize production processes and increase business efficiency. However, despite the potential benefits associated with learning artificial intelligence technologies, there are serious challenges that require careful analysis. These challenges include ethical dilemmas, such as issues of algorithm transparency and responsibility for making principled decisions. Data security and privacy are also among the key aspects that require innovative approaches to AI technology training. The main purpose of the research is to deeply analyze the prospects and challenges in the field of artificial intelligence technology training, provide a comprehensive understanding of the current state of this field, identify key areas of development and propose practical strategies for effectively overcoming challenges. Taking into account both positive and negative aspects, it is necessary to have a meaningful look at the future of artificial intelligence technology education, taking into account social, ethical and technical aspects. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. Subject The topic of the resource AI ethics; algorithm transparency; Artificial intelligence technologies; challenges; data security; deep learning; education; efficiency; finance; industry; innovation; learning; machine learning; medicine; perspectives; reinforcement learning; socio-cultural aspects Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-303204364-1; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online