Application of systemic-structural activity theory to the design of BOTs and AI software

Today, artificial intelligence (AI) and BOTs (build–operate–transfer) transform our individual lives and businesses. Some authors even claim that this is the era of intelligence in machines. AI and BOTs are developed to mimic various human behaviors. The Systemic-Structural Activity Theory (SSAT) is the framework that offers numerous methods of analyzing and optimizing human performance and reducing the number of errors. This paper focuses on how the SSAT methodology can be utilized to develop AI and BOTs. The SSAT analysis of the tasks, their design, and testing can be improved via building a human algorithm of the task performance. Such analysis allows users to choose the most efficient method of task performance that can then be applied to the development of an AI or a BOT. This paper discusses the examples of BOT development and demonstrates the capabilities, utilization, and future applications of the SSAT framework.