A review on building blocks of decentralized artificial intelligence

Artificial intelligence (AI) is one of the key technologies transforming our lives, while the transfer of knowledge and competencies from the academic sphere to the industry and real-world use cases are accelerating yearly. However, during that transition, several significant problems and questions need to be addressed for the field to develop ethically, such as digital privacy, ownership, and control. These are some of the reasons why the currently most popular approaches of artificial intelligence, i.e., centralized artificial intelligence (CEAI), are questionable, with other directions also being explored widely, such as decentralized artificial intelligence (DEAI), which aim to solve some of the most far-reaching problems. This paper aims to review and organize the knowledge in the field of DEAI, focusing solely on studies that fall within this category. A systematic literature review (SLR) was conducted using six scientific databases and additional gray literature to analyze and present the findings of 71 identified studies. The paper's primary focus is identifying the building blocks of DEAI solutions and networks, tackling the DEAI analysis from a bottom-up approach. Future research directions and open problems are presented and proposed at the end.