Formation of Motivated Adaptive Artificial Intelligence for Digital Generation of Information and Technological Actions

Motivated artificial intelligence plays a relevant role in digital generation of information. Motivated artificial intelligence activates the generation of meanings and technological action. Its motivational functionality and motivation goals are determined by developers and users of technologies, which in turn helps to form AI motivation in the context of digital transformation. Formation of artificial intelligence motivation in digital generation of information is complex and multifaceted task that includes both theoretical and practical aspects of AI motivation in technological thinking and actions. Artificial motivated intelligence must have clearly defined goals that it must achieve. The goal of motivation can be set in the form of functionality (ontology, erudition, reflection, usefulness, preference), which will guide the motivation of AI. The use of reinforcement learning methods will allow AI to independently find optimal strategies for achieving its goals. It receives positive or negative reinforcement depending on how successfully it performs information transformation tasks. To form motivation of AI, it is necessary to ensure its ability to adapt to changing conditions and tasks. This includes learning from new data, knowledge and experiences. In some cases, it is useful to implement elements of emotional intelligence so that AI can better understand and respond to human emotions and actions. This improves the digital generation of information. It is important to consider ethical aspects and security. It is necessary to ensure that the digital generation of information does not lead to undesirable consequences or harm. Artificial intelligence must be able to effectively interact with users and other systems to receive feedback and adjust its actions in accordance with changing conditions. Research and implementation of motivation models, such as the hierarchy of needs or self-determination, can be useful in international digital generation of information. Formation of AI motivation requires an interdisciplinary approach that includes psychology, computer science and ethics. Motivation of AI to advance scientific and technological achievements is relevant in digital generation of information in various fields of activity. The motivation of hybrid intelligent systems is realized on the basis of knowledge engineering through synergetic communication.