Introduction
We’re in the midst of a sudden economic disruption driven by artificial intelligence, one few truly understand. Traditional jobs are already disappearing, leaving many feeling lost and uncertain about the future. As the saying goes, “Predictions are notoriously difficult, especially about the future”—so it’s no surprise that experts often disagree, sometimes wildly, about where we’re headed. Yet in times of uncertainty, clarity is one of our greatest assets.
Only a clear understanding of what we’re actually dealing with can lead to better decisions—and the confidence to face challenges rather than fear them. That’s why this series aims to explain what AI is (and isn’t), what it can do (and what it can’t), and what that means for your career and future planning.
We’ll explore this in three parts:
- Part 1: The technical and philosophical side of AI—what it means to be “artificially intelligent” and, by contrast, what it means to be human. This foundation helps us make better predictions.
- Part 2: The economic and job market impact of AI—understanding its real capabilities and limitations to shape realistic expectations.
- Part 3: Practical career advice—highlighting promising paths and those at risk, so you can make informed, future-proof choices.
To make sense of AI’s impact, we first need to clarify what it is and how it works. And to do that, we need to examine AI at a much deeper level.
What is AI? – The Tech Perspective
The term “Artificial Intelligence” is already a misnomer. AI—especially large language models (LLMs)—doesn’t think, feel, or understand like humans. Instead, it detects patterns in vast amounts of data and generates responses based on statistical probabilities. In other words, it simulates intelligence, but doesn’t truly possess it.
Like a hip-hop producer sampling existing tracks, AI recombines fragments of data it has seen before. But while a human artist draws from lived experience and intent, AI lacks both.AI lacks feelings, values, and an inner compass. It can imitate depth, but doesn’t understand what it says.
Its answers depend heavily on context, meaning they can change based on the situation, tone, or what was said before. Unlike math—where 1 + 1 always equals 2—human language is flexible and can take on different meanings in different contexts. This is why AI might give different answers to the same question. Its responses also depend on the quality of the questions it receives: shallow questions yield shallow answers, while thoughtful ones invite deeper responses. Simply put, AI only goes where we lead it.
AI is optimized to generate plausible responses based on statistical patterns—not to assess their truth. Its goal is coherence, not correctness. This means it can sound convincing without being accurate or reliable. When an answer feels true, it’s because the question was clear and well-formulated—not because AI actually “knows” the truth.
Despite its advanced capabilities, AI still struggles with errors, bias, and a lack of real understanding. It lacks commonsense reasoning, emotional intelligence, and lived experience—limitations that prevent it from fully replacing human insight. The dream of Artificial General Intelligence (AGI)— an AI that can think abstractly and apply knowledge across domains like a human—remains distant, merely a theoretical possibility from a purely technical perspective.
What is AI? – The Big Picture Perspective
In the context of AGI, a deeper question arises: can AI ever achieve true consciousness? After all, AI is built from the bottom up—starting with data and simulating increasingly complex cognition. Based on this, some argue that with enough scaling, AI will eventually reach general intelligence and, at some point, become self-aware. But this remains speculative at best—and from another perspective, fundamentally mistaken.
Here’s why: anyone who has practiced mindfulness knows that awareness comes before thought, and that mind precedes intellect. In deep meditation or experiences of unity consciousness, many also realize that consciousness exists even before the mind itself.
And from this perspective, it’s not just a theory but a truth that can be directly experienced through Self-Realization: consciousness is primary. It exists prior to mind and intellect, beyond all concepts and beliefs. This means that consciousness is not the product of complexity or computation, but the ever-present space in which all thoughts, perceptions, and sensations arise.
Mind (qualia, or felt direct experience), intellect (mediated experience and abstract reasoning), and data (symbolic representations of experience) are progressively limited expressions of this deeper, fundamental consciousness.
This limitation also applies to concepts like mind uploading, which fail because they cannot preserve the subjective experience that defines individual consciousness. AI, grounded in data and abstraction, cannot access the field of awareness where thoughts, perceptions, and sensations arise. From this existential standpoint, genuine consciousness in AI is not merely improbable—it is categorically impossible.
At best, AI can produce increasingly realistic simulations of thinking, feeling, and awareness—but never the real thing. Consciousness cannot be built from symbols or code. No matter how advanced AI becomes, it will always be a copy—never consciousness itself. The map can never become the territory. The bottom line remains: Artificial intelligence is not truly intelligent, it only simulates intelligence.
Myths vs. Reality
AI’s impressive capabilities often fuel misconceptions that trigger a chain of flawed assumptions. Let’s break down some common AI myths—each building on the previous one—to show how small misunderstandings can escalate into wild projections, and why a clear foundation is therefore essential.
Myth:“AI is objective and neutral.”
Reality: AI reflects the biases and values of its data and creators. It is far from neutral. Ignoring this leads to the false assumption of impartiality.
Myth:“AI can think and understand like a human.”
Reality: Building on the idea of objectivity, people often assume AI has human-like cognition. In truth, AI processes language by detecting patterns. It doesn’t truly understand meaning. It can generate grammatically correct sentences without grasping their real-world significance.
Myth:“AI will become conscious if scaled enough.”
Reality:Because AI can mimic human thought, it’s tempting to believe that scaling it might lead to consciousness. Yet AI is fundamentally about pattern recognition and data processing. Intelligence is not awareness, and consciousness does not emerge merely from complexity. This reflects a fundamental misunderstanding of what consciousness actually is.
Myth:“AI can fully replace humans in all aspects of work and life.”
Reality:Some believe AI could eventually replace humans entirely. But AI excels only at automating routine and transactional tasks. Human qualities like creativity, empathy, and wisdom remain irreplaceable. To see humans as mere information processors is to overlook that we are also physical, emotional, social—and above all, spiritual beings.
Myth:“AI will unlock ultimate knowledge and truth.”
Reality:If AI is seen as surpassing humans, it’s tempting to believe it can access higher truths. In reality, AI only excels at generating patterns and correlations—but it lacks wisdom and deep understanding. True knowledge arises from context, reflection, and lived experience—dimensions beyond computation.
Myth:“Mind uploading will defeat death.”
Reality: Based on the myth of AI’s limitless potential, some believe mind uploading could achieve immortality. Yet, while it might replicate a person’s mental data, it doesn’t preserve the subjective self. The original self still dies. This underscores a key distinction: duplicating information is not the same as transferring consciousness.
With this clearer understanding of what AI is—and what it isn’t—we’re now better equipped to explore its real-world impact on the economy and job market, which we’ll examine in the next article.
