Take a sentence and convert its words into numbers so the computer can process them, then organize them so it understands the order. Next, look at the sentence as a whole to capture the overall meaning, while also letting each word relate to others to identify what matters most. At the same time, process the sentence in multiple ways to refine the understanding without losing context. Then begin forming the response one word at a time, without looking ahead, while continuously checking back with the original sentence to stay aligned. At last, choose the most likely next word at each step to build a clear and meaningful answer.

AI gives us “wow” content in seconds, and we often mistake it for meaning and clarity. We open a tool, ask a question, and within seconds information comes back that does feel magical. This magic appears to have solved our problem. The solution reads well (we might not read it completely). It sounds right (we might not have the knowledge to evaluate). It feels like intelligence (until we try to use it). But what exactly is that “wow”? That wow is only a first impression and like most first impressions, it is also incomplete.

I am talking about the time when purchases happened face-to-face. Oh wait, they still do happen. A product hunt today has become easy. Purchases can now happen online. Reviews, recommendations, and price comparisons have always been there. AI today is helping to take the next leap. That already gives us enough information to decide what has stayed and what has changed. Did the markets disappear? No. The way we make decisions has changed. As we can see, markets have stayed, products have stayed, and human needs have stayed. The speed, scale and the way we access the information has changed and that leading to how we take the decisions.

We all live with two dimensions of meaning in how we understand things. One meaning is given by the world in the form of standard definitions, while the other is internalized through our thoughts and lived experiences. The ability to recognize both and reflect on how we interpret them, when to use what, may be is what we call consciousness. Let’s take a pause here.

Quick question for you: Do you hallucinate? (Hallucinate - to see or hear something that's not really there)

If you said “no,” then you need to take some time to consider the questions below and rethink your answer. You can also still do it even if your answer was “yes.”

Have you ever relied on information that did sound reasonable and later turned out to be fictional? Do you sometimes create facts the way people create imaginary arguments in the shower? Have you ever answered like someone in love, like the way they are confident even when they are imagining things? Do you remember how you accept the “I read the terms and conditions” section?
How many times have you trusted and forwarded that WhatsApp forward?

Vast amounts of data: collected, structured, measured, evaluated and optimized. That is how AI and machine learning are traditionally introduced to us. When we approach it from a technical standpoint, this perspective is, of course, valid. But, I know there is always a ‘but’. This perspective shifts our attention away from a more fundamental truth that “we humans have always made decisions without waiting for perfect data”. Long before spreadsheets, dashboards, or machine learning models entered our lives, decisions were made by memory, experience, and intuition. This leads to a simple but important thought that if we want to use AI wisely, we must first acknowledge that intelligence did not begin with numbers.