In 1956, a small group of scientists imagined machines that could think—now 70 years later, we’re still asking what that really means.
From what I’ve read so far, Artificial Intelligence (AI) doesn’t seem to have a single, universally accepted definition—and that alone makes the topic fascinating. At the 1956 Dartmouth Workshop, where John McCarthy first coined the term, AI was described as “the science and engineering of making intelligent machines, especially intelligent computer programs… to simulate aspects of human intelligence.” This early vision focused on mimicking human cognitive functions like learning, problem-solving, and understanding.
Since then, AI has evolved in ways I’m only beginning to grasp—from symbolic reasoning to machine learning and now generative models.
Reflecting this complexity, the OECD (2024) defined an AI system as “a machine-based system that, for explicit or implicit objectives, infers from the input it receives how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment.”
It’s interesting to see how the focus seems to have shifted—from building smart machines to thinking about their role in our lives.
Most recently, the EU AI Act (2025) offered a detailed definition: an AI system is (1) machine-based; (2) designed to operate with varying levels of autonomy; (3) capable of adaptiveness after deployment; (4) working toward explicit or implicit objectives; (5) inferring from input how to generate outputs; (6) such as predictions, content, recommendations, or decisions; (7) that can influence physical or virtual environments.
What strikes me is how these definitions highlight characteristics that echo human capabilities —autonomy, adaptability, and the ability to shape the environment. Like humans, AI systems can act independently to different degrees. AI systems can be adaptive and learn similar to the way we do. AI systems don’t just passively process input but influence their surroundings.
Decades later, the question persists: what makes intelligence—artificial or natural—truly unique? And does it matter which is which? Is one of greater value than the other?
I don’t have the answer yet, but exploring these definitions feels like opening a door to deeper questions.
Published on Linkedin.com
