Toward Trustworthy Artificial Intelligence (TAI) in the Context of Explainability and Robustness

Abstract

From the innovation, Artificial Intelligence (AI) materialized as one of the noticeable research areas in various technologies and has almost expanded into every aspect of modern human life. However, nowadays, the development of AI is unpredictable with the stated values of those developing them; hence, the risk of misbehaving AI increases continuously. Therefore, there are uncertainties about indorsing that the development and deploying AI are favorable and not unfavorable to humankind. In addition, AI holds a black-box pattern, which results in a lack of understanding of how systems can work based on the raised concerns. From the above discussion, trustworthy AI is vital for the extensive adoption of AI in many applications, with strong attention to humankind and the need to focus on AI systems developing into the system outline at the time of system design. In this survey, we discuss compound materials on trustworthy AI and present state-of-the-art of trustworthy AI technologies, revealing new perspectives, bridging knowledge gaps, and paving the way for potential advances of robustness, and explainability rules which play a proactive role in designing AI systems. Systems that are reliable and secure and mimic human behaviour significantly impact the technological AI ecosystem. We provided various contemporary technologies to build explainability and robustness for AI-based solutions, so AI works safer and more trustworthy. Finally, we conclude our survey paper with high-end opportunities, challenges, and future research directions for trustworthy AI to investigate in the future.