Editor’s note: Besides tracking technological advancements and innovations, our author is a Juilliard-trained musical composer. He has created a musical piece titled “Appearance of Understanding” for you to enjoy while reading this column.
I know we all like to think that we are conscious and rational, and that we completely understand what is going on, including why we make the decisions we do. I also know that a great deal of my understanding is based on intuition, rather than rational, analytical, or pedagogical learning. For me, physics was far easier than spelling correctly. Somehow, I was able to recognize patterns, and physics just made sense to me. You might think it impossible to apply a word like ‘intuition’ to science, but I can assure you that some of the best scientists and engineers I know are tremendously intuitive.
My professional career began as a researcher. Research always felt like walking down the hallway with a very large number of doors, none of which had windows large enough to see anything but a small glimmer of the topic, and you had to intuit which door to open and go through to find a field in which you could make progress. I mean, how could you know without information? But somehow you could. And, in fact, I knew people who could examine very complicated electrical circuits and intuitively understand that if they changed the value of a single component, it would alter the circuit’s operation and by how much. I was able to walk into a laboratory while teaching electrical engineering classes and simply turn a knob on the right piece of equipment to the right amount to make the experiment work. I cannot explain this, but it is not uncommon among people who are skilled at experiments.
Human Intuition: Deeply Embodied
Intuition can be like a quiet nudge from within that knows something before you know why. It is an internal compass, subtle, swift, and amazingly accurate. I have been fascinated by this ever since noticing that my father and I could understand mathematics that we had never been taught, read about, or learned. It was a kind of whispered truth. After decades of technical experience, I still find that some people seem to possess an innate understanding of things.
We can directly apprehend concepts before our intellect kicks in, and this has something to do with the brain’s ability to recognize patterns unconsciously. It is not only true in artistic and traditionally creative realms. It is also true in science, and it is true in relationships between not only people but also subjects and topics that are seemingly unrelated. It is at the intersections where many of the great breakthroughs occur. And I do not believe these breakthroughs are usually based on linear, rational thinking. There is usually a leap involved, which often relies on intuition because you never have enough information to be certain of what you know.
Traditional AI is built around logic, rules, and step-by-step reasoning, but artificial intuition leans into pattern recognition, experience-based learning, generalization, and fast, subconscious-like responses, which is what people do.
Artificial Intuition: Simulated Gut?
Artificial intuition is about more than fast computation. It’s about making what appears to be an intuitive leap, a judgment made with incomplete information, without relying on exhaustive analysis. Like humans sensing the shape of a solution without knowing all the details, AI systems are beginning to perform similar feats. This capability often shows up in large language models (LLMs) and neural-symbolic hybrids. LLMs can answer novel questions, generate analogies, or write code with minimal prompting.
One example is an artificial intelligence system called AlphaFold. This program predicts the 3D structures of proteins based solely on their amino acid sequences, which is a significant achievement because proteins are the molecular machines of life. Their shape determines how they function; figuring out how that shape is used takes scientists months or years. AlphaFold can achieve this in hours with remarkable accuracy, yielding groundbreaking predictions and accelerating research in drug discovery and disease understanding. In his 2024 Nobel Prize banquet speech, Jeffrey Hinton spoke directly about artificial intelligence. At its heart, artificial intuition is about giving AI systems the ability to make leaps of insight, to recognize patterns, anticipate outcomes, and make decisions in situations where explicit rules or complete information aren’t available.
This will be necessary for self-driving cars that must make split-second decisions to function properly or to flag subtle medical anomalies that human doctors might miss. Therefore, this connection of artificial intuition represents a move beyond calculation to something more fluid and faster. Something that mimics the uncanny speed and insight of human feeling.
The Integration Challenge
Current research suggests that the future lies not in choosing between AI and artificial intuition, but in combining them. Hybrid systems can integrate the computational power of AI with intuitive processes.
This approach recognizes that systematic analysis and gut feelings serve different, yet complementary, roles in decision-making.
Intuition matters in the AI world. AI has transformed industries, but it struggles in situations that humans navigate effortlessly, such as facing a completely novel scenario, ambiguous information, or time-critical decisions with incomplete data. Traditional AI systems often falter, although human intuition, developed through millions of years of evolution, allows us to make surprisingly accurate snap judgments in these situations. Entrepreneurs sensing market opportunities, doctors diagnosing unusual cases, military commanders making split-second tactical decisions are all scenarios that require something beyond algorithmic processing. They demand the kind of rapid, holistic assessment that we call intuition.
I think we are moving into a new paradigm and machine cognition that doesn’t just compute answers but somehow feels some, and this evolution could transform everything from vehicles capable of navigating unpredictable situations to AI assistance that understands context and nuance in ways that feel more genuinely intelligent. My personal feeling is that the integration challenge is not between artificial intelligence and artificial intuition, but between human intuition and artificial intelligence. I am already using AI to design a new kind of musical ensemble where I can perform alongside artificially intelligent accompanists. It can be hard to tell who is leading because I have a greater ability to adapt to the AI than the AI has to adapt to me, but the net result is that I can sound like more than one musician.
