  In the last years, the raise of Artificial Intelligence (AI), and its
pervasiveness in our lives, has sparked a flourishing debate about the ethical
principles that should lead its implementation and use in society. Driven by
these concerns, we conduct a rapid review of several frameworks providing
principles, guidelines, and/or tools to help practitioners in the development
and deployment of Responsible AI (RAI) applications. We map each framework
w.r.t. the different Software Development Life Cycle (SDLC) phases discovering
that most of these frameworks fall just in the Requirements Elicitation phase,
leaving the other phases uncovered. Very few of these frameworks offer
supporting tools for practitioners, and they are mainly provided by private
companies. Our results reveal that there is not a "catching-all" framework
supporting both technical and non-technical stakeholders in the implementation
of real-world projects. Our findings highlight the lack of a comprehensive
framework encompassing all RAI principles and all (SDLC) phases that could be
navigated by users with different skill sets and with different goals.
