Trust in Humans versus Trust in Machines/Systems: A Systematic Literature Review (SLR) and Roadmap for Future Research

Intelligent machines are set to become an integral part of society in the autonomous age (specifically in the AI era), but tensions remain between human liberties and machine controls. Little research has explored the dynamic trust relationship between humans and artificial intelligence (AI) systems. We conducted a PRISMA-style systematic literature review (SLR) supplemented by a machine learning (ML) approach on studies published between 2010 and 2023, investigating emergent themes, research gaps, and potential directions. Our analysis reveals increasing emphasis on trust in AI, especially as automation spreads across healthcare, finance, e-commerce, and other sectors. Ensuring users feel confident and secure when interacting with AI is vital. We propose a four-phase roadmap focusing on trust across AI's evolving capabilities, from narrow AI to futuristic super-intelligence AI. This guideline helps conceptualize, enhance, and institutionalize trust, making AI more user-friendly and reliable. Moreover, it underscores trust as essential for responsible AI adoption and governance, forming a foundation for future academic research.