Artificial Intelligence raises concerns, especially in areas where human beings are affected by its decisions. Trust, explainability, and accountability are therefore crucial for legal compliance and to increase end-user confidence. This is particularly relevant when Intelligent Controls are employed in Swarm Robotic systems, which consist of numerous independent units functioning as a collective. Here, the complexity of trustworthy Artificial Intelligence solutions may escalate rapidly, necessitating the development of swarm intelligence paradigms that differ from conventional methods, used for single intelligent agents. Interactions between humans and Artificial Intelligence raise critical questions: at the internal system level, where human-in-the-loop control is often required, and at the external level, where intelligent agents’ actions may impact humans, potentially leading to ethical dilemmas. This paper proposes a new extension to Human Swarm Teaming-3 architecture adding explainability and accountability through Distributed Autonomous Organization and Distributed Ledger Technologies. Finally, an implementation of this new Human Swarm Teaming-4 architecture is proposed using a Robot simulator software and Distributed Ledger testnet.