<p>This book review discusses Artificial Misinformation: Exploring Human–Algorithm Interaction Online by Donghee Shin (PalgraveMacmillan, 2024), which offers a critical and interdisciplinary analysis of how misinformation emerges and circulates in algorithmicallymediated environments. Shin reframes misinformation not as isolated falsehoods but as a systemic phenomenon arising from the intersection of human cognitive biases and algorithmic design. Drawing from theories of bounded rationality and cognitive heuristics, the book highlights how vulnerabilities such as noise, overconfidence, and heuristic shortcuts interact with recommender systems toreinforce echo chambers and ideological silos. Through case studies of platforms such as TikTok, Shin demonstrates how algorithmic amplification shapes user behavior and contributes to polarization, while also noting the contextual limits of findings from U.S. and South Korean settings. The review emphasizes Shin’s normative interventions, including the Misinformation Processing Model, nudging strategies, anddiversity-aware recommender systems, which go beyond traditional fact-checking to address structural and cognitive vulnerabilities. These proposals are connected to broader policy frameworks, such as the EU’s Digital Services Act, OECD principles for trustworthyAI, and UNESCO guidelines, underscoring their global relevance. The book also interrogates interface design, inoculation strategies,and the ethical accountability of platforms, framing algorithmic diversity and transparency as democratic responsibilities rather than optional features. While recognizing limitations in geographical scope and generalizability, the review concludes that Shin’s book makes a landmark contribution to misinformation studies and AI ethics by integrating cognitive psychology, media studies, and normative frameworks for governance. It provides valuable insights for scholars, developers, and policymakers concerned with safeguarding knowledge, democracy, and truth in the digital age.</p>