Development of Artificial Intelligence Through the Prism of Dialectics

he article is devoted to the philosophical analysis of the evolution of artificial intelligence (AI) through the prism of dialectical methodology, where AI is considered as part of technological revolutions. The authors trace the development of AI since the 1950s, when its foundation was laid, based on logical rules, but which was characterized by limited flexibility. In the 1970s and 1980s, expert systems such as MYCIN formalized knowledge in narrow areas, but failed to cope with non-standard tasks. The breakthrough began in the 2000s and is associated with the transition to machine learning, as well as neural networks. All this allowed AI to process big data and solve problems such as image recognition. Despite all the positive trends, problems of algorithm opacity have also arisen. The dialectical method identifies the main contradictions: technological capabilities versus transparency, centralization of development versus decentralization, mass unemployment versus jobs, personalization versus privacy protection. These conflicts are analyzed to find constructive solutions that promote responsible AI development. The authors emphasize the degree of philosophical understanding to form clear boundaries that ensure the coexistence of humans and intelligent systems. In view of the large-scale involvement of AI in all areas of society, AI research involves an interdisciplinary approach that opens up new prospects for research into human society.