The proliferation of big data and rising computational power are currently giving artificial intelligence (AI) the tools it needs to be widely adopted and applied in a variety of fields. Current AI algorithms significantly hampered critical decision-making systems by failing to provide rationale for their decisions. For example, deep learning lacks reasoning and control on the processes that are internal or the outcomes. Additionally, there is a risk that attacks that are adversarial will taint the inference or learning processes of current black-box AI implementations. Explainable AI (XAI) is a new feature in algorithms of artificial intelligence, which offers justifications for the decisions they make. In this work, a framework is presented that makes use of smart contract, block chain, and storage (not centralized) features to create a XAI that is more reliable. We outline a framework for sophisticated artificial intelligence systems wherein consensuses of several predictors of artificial intelligence and XAI that are not centralized are used to determine decision outcomes. The paper presents use cases from the scenarios that are real for our suggested framework in important application areas.