International Journal of Science, Engineering and TechnologyAuthors: Sagar Gupta
Abstract: As Artificial Intelligence (AI) systems permeate critical sectors like healthcare, finance, and governance, deep-rooted limitations have begun to surface—often referred to metaphorically as "AI cancers." These include systemic issues such as algorithmic bias, hallucination, goal misalignment, data poisoning, overfitting, and lack of explainability. Like cancer in a biological organism, these flaws can spread undetected, undermining trust, accuracy, and societal safety. This paper explores the nature, origin, and consequences of these "AI cancers," while outlining the emerging strategies to detect, contain, and remediate them.
