Aryeshwar Dayal, International Journal of Computer Science and Mobile Computing, Vol.13 Issue.10, October- 2024, pg. 54-57 © 2024, IJCSMC All Rights Reserved, ZAIN Publications, Fridhemsgatan 62, 112 46, Stockholm, Sweden 54 Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology ISSN 2320–088X IMPACT FACTOR: 7.056 IJCSMC, Vol. 13, Issue. 10, October 2024, pg.54 – 57 Artificial Intelligence and Artificial Stupidity: The Inseparables Aryeshwar Dayal House no 503, Hermitage, GH Society 2, Sector 28, Gurugram, Haryana, India aryeshwar@gmail.com DOI: https://doi.org/10.47760/ijcsmc.2024.v13i10.006 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. Keywords— Artificial Intelligence, Artificial Stupidity, Machine Learning, Neural Networks I. INTRODUCTION Artificial intelligence (AI) refers to the simulation of human intelligence by machines, particularly computer systems. AI enables machines to perform tasks that typically require human intelligence, such as learning, problem-solving, decision-making, and understanding natural language. AI systems can adapt to new data, recognize patterns, and automate processes like image analysis and speech recognition, making them highly versatile across various fields, including robotics, healthcare, and finance. Artificial stupidity (AS) refers to the limitations, flaws, or intentional "dumbing down" of artificial intelligence (AI) systems. It is a term used to describe the behaviours or outcomes produced by AI that appear unintelligent or nonsensical, often due to errors, misapplication of technology, or limited capabilities. In some cases, artificial stupidity arises when AI is deliberately constrained to simulate more human-like or imperfect behaviour in areas like gaming or human- computer interactions. It highlights the contrast between AI's potential for intelligence and its frequent, seemingly "stupid" errors. Understanding both AI and AS is critical for successful AI application development. AI represents systems that simulate human intelligence, solving complex tasks with high precision. However, these systems also exhibit artificial stupidity i.e. failures and errors due to poor data, flawed algorithms, or misapplications. Recognizing