The intelligence illusion: why AI isn’t as smart as it is made out to be
The AI Illusion: Why Machines Aren’t Creative Luc Julia Wiley (2026)French-American computer scientist Luc Julia has worked at the interface of artificial intelligence and consumer technologies for more than three decades. Currently chief scientific officer at the car maker Renault Group, he has previously worked at Samsung Electronics, Apple and Hewlett-Packard. He did early work on the natural-language-processing tools that underlie current generative AI models. In his book, The AI Illusion, translated from French, he argues that the hype and fear surrounding the intelligence and creative abilities of AI models are overblown.What is the ‘AI Illusion’?The term aims to address a fundamental misunderstanding about AI that has persisted for nearly 70 years, dating back to 1956 when AI research formally began. The term ‘intelligence’ is widely misunderstood, often leading people to anthropomorphize AI tools, attributing human-like qualities to machines. This illusion has been perpetuated by science fiction and media portrayals, which depict AI systems as potentially dangerous or capable of developing human-like emotions and decision-making skills.Does AI already have human-level intelligence? The evidence is clearIn reality, the systems that we call AI are more about processing information than showing intelligence similar to human smartness. The illusion lies in our tendency to overestimate AI’s capabilities and potential threats, rather than understanding it as a collection of sophisticated but narrow tools designed for specific tasks.Just as a magician uses sleight of hand to create the illusion of magic, the terminology around AI creates the illusion of human-like intelligence. This stems from the dual meaning of the word intelligence, which can refer to both information processing and cognitive smartness. The latter is often projected onto AI, leading to exaggerated expectations and fears. AI, in its current form, operates on algorithms and data, performing tasks with precision but lacking the consciousness and creativity that is inherent in human intelligence. This distinction is essential for understanding the true capabilities and limitations of AI.Who is being deceived?The general public, by the technology companies and organizations that benefit from the hype around AI. These companies are in a race to develop the technology and are incentivized to promote the idea of human-like artificial general intelligence to secure funding and market dominance. Members of the scientific community, particularly those who are not directly involved in the race for AI funding, acknowledge the reality that AI is a set of specialized tools, rather than a unified intelligent entity. This distinction is crucial, but it is blurred by commercial interests that amplify the illusion for monetary gain.How close is AI to human-level intelligence?The narrative of AI as an impending replacement for human intelligence fuels both fascination and apprehension. It generates excitement and investment, driving technological advancements and economic growth. But it also creates unrealistic expectations and fears, influencing public perception and policy decisions. It is important to recognize that, although AI can augment human capabilities, it is not a sentient entity poised to overtake human roles. Understanding this dynamic is essential for fostering informed discussions about the role of AI in society.What is intelligence in the context of AI?Intelligence is a contentious term because it lacks a single, universally accepted definition. In the context of AI, ‘intelligence’ often refers to information processing rather than genuine cognitive ability. A calculator performs calculations faster than a human, which might seem intelligent, but it is merely executing predefined operations. Similarly, AI systems are designed to excel at specific tasks, outperforming humans in those areas, but they lack the creativity and adaptability that is inherent to human intelligence. Philosophers and psychologists offer various perspectives on intelligence, but AI, as it stands, does not have the innate creativity or consciousness that is associated with true intelligence.The debate over AI’s intelligence highlights the complexity of defining intelligence itself. Human intelligence encompasses a range of cognitive abilities, including reasoning, problem solving and emotional understanding. AI operates in the confines of algorithms and the data on which it is trained, lacking the experiential learning and emotional depth of human cognition.Yet AI systems are powerful?Absolutely, AI systems are impressive in their designated functions. The power of AI lies in its ability to process vast amounts of data quickly and accurately. This capability has transformed industries such as health care, finance and transportation.However, with great power comes great responsibility. The effectiveness of AI models depends on the quality of the data they are trained on and the context in which they are applied. Misuse or misunderstanding of AI can lead to errors, biases and ethical concerns, highlighting the importance of human oversight and regulation. The key to harnessing AI’s potential lies in recognizing it as a tool that complements human abilities rather than as a replacement for human intelligence.AI can be used to support medical applications including robotic surgery.Credit: Costfoto/NurPhoto/GettyWhat would a truly intelligent AI look like to you?It would need to have a form of general intelligence similar to that of humans, capable of continuous and creative thought across various domains. This means the system would need to reflect and act on any subject, innovate spontaneously and create new concepts or solutions independently. AI currently lacks the biological and creative aspects of human intelligence. A system designed to play chess, for example, can defeat human grandmasters but is incapable of understanding or writing a poem.Why do you argue that AI and machine learning are different?This distinction is important for understanding the various components and capabilities of modern AI systems.
