Artificial Intelligence and Artificial Stupidity: The Inseparables

Abstract

Artificial intelligence (AI) has long been heralded for its ability to simulate human intelligence, enabling machines to perform complex tasks such as decision-making, problem-solving, and data analysis. However, alongside the advancements in AI, the concept of artificial stupidity (AS) has gained attention. AS refers to the limitations and errors made by AI systems, often resulting from incomplete data, biased algorithms, or the inherent restrictions placed on AI to simulate more human-like decision-making. These instances of "stupidity" can lead to nonsensical or harmful outcomes, especially when AI is applied to critical areas such as healthcare, autonomous systems, and legal decision-making. This narrative review explores the duality between AI's potential and its flaws, emphasizing the importance of understanding both AI and AS in developing robust, safe, and ethical AI applications. By addressing the causes of artificial stupidity, such as algorithmic limitations and poor data quality, researchers and developers can improve the reliability and decision-making capabilities of AI systems. There is also the need for human oversight and ethical considerations to mitigate the negative impacts of artificial stupidity, especially in high-stakes environments.