  Artificial intelligence is transforming our lives, and technological progress
and transfer from the academic and theoretical sphere to the real world are
accelerating yearly. But during that progress and transition, several open
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 AI (CEAI), are questionable, with other directions also being
widely explored, such as decentralized artificial intelligence (DEAI), to solve
some of the most reaching problems. This paper provides a systematic literature
review (SLR) of existing work in the field of DEAI, presenting 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. In the end, future directions of research and open problems
are proposed.
