The Future of AI and Human Intelligence

---

Intelligence has been one of the most valuable and scarce resources in the world. It took years to develop, required effort and discipline, and was unevenly distributed across populations. Those who had it and could apply it effectively usually shaped industries, institutions, and (sometimes) entire economies.

Education systems were built around this reality, and careers were structured to reward it. Entire hierarchies were formed based on it too. Intelligence was not only useful but also a defining feature of human progress, though, as we’ll explore below, artificial intelligence is changing that foundation.

AI Is Making Intelligence Abundant

We’re moving into a world where intelligence is no longer scarce. It’s becoming abundant and widely accessible. Tasks that once required deep expertise can now be performed in seconds, and information that once took years to accumulate can now be synthesized instantly.

This transformation is easy to underestimate because it looks, at first glance, like an extension of previous technological progress. We’ve seen tools improve productivity before, and we’ve seen automation replace labor. We’ve also seen software transform industries. But this is fundamentally different because this time, the thing being scaled is not physical output or mechanical efficiency. It’s intelligence itself.

Getting Answers Without Doing the Thinking

The implications of this shift are far-reaching. One of the more important changes is the separation of knowledge from understanding. In the traditional model, humans asked questions, formed hypotheses, tested ideas, and gradually built understanding. Knowledge was the result of that process.

Artificial intelligence begins to invert that model. It can generate answers without requiring the same step-by-step reasoning process that humans use. Often, those answers are highly effective. They can solve problems and create outputs that would have taken humans much longer to produce.

But here’s the catch: The reasoning behind those answers is not always transparent. Even when explanations are provided, they may rely on patterns and associations that humans find difficult to fully grasp, which creates a new kind of relationship with knowledge. For the first time, humans can use knowledge they do not fully understand.

To be sure, we’ve seen early versions of this before, as most people do not understand the algorithms behind search engines, yet they rely on them daily. Few people understand how financial systems operate at a technical level, yet they participate in them constantly.

Artificial intelligence extends this dynamic into almost every domain from science and medicine to engineering and business strategy. Areas that once required deep specialization can now be influenced by systems that operate at a scale and speed beyond human capacity, which, to be clear, doesn’t mean humans become irrelevant. But it does mean their role changes.

The Rise of the Machine Polymath

Humans tend to specialize. Expertise is often narrow and built within a specific domain. Breakthroughs, however, often come from connecting ideas across fields.

Artificial intelligence operates differently. It can integrate knowledge across domains simultaneously. In that sense, it behaves like a kind of universal polymath.

This gives it a powerful advantage. When solving problems, it’s not limited by disciplinary boundaries. It can draw from a broad range of information and identify patterns that would be difficult for a single human (or even a team) to see, which is one of the core reasons AI has the potential to accelerate innovation dramatically.

The Commoditization of Intelligence

In previous technological waves, machines replaced physical labor, and industrialization reduced the need for manual work. Automation streamlined manufacturing, and software eliminated repetitive tasks. Now, machines are beginning to replace cognitive labor.

This marks a new phase: Intelligence, which was once scarce and highly valued, is becoming more accessible and less differentiated.

This carries implications for the structure of work. Many entry-level roles exist to train individuals, allowing them to build experience and gradually develop expertise. If machines can perform many of those tasks, the traditional pathway from novice to expert becomes less clear. Thus, this becomes a development issue that affects how skills are built over time.

AI is Changing the Speed of Human Progress

Human progress has historically been gradual. Scientific discovery, technological advancement, and institutional change usually unfolded over decades or centuries.

Artificial intelligence is compressing that timeline. Systems can learn, iterate, and improve at speeds that far exceed human capability, which creates a mismatch. Institutions such as education, government, and corporate structures are not designed to adapt at this pace. As a result, the rate of technological change may outstrip society’s ability to respond, and this gap is where much of the tension around AI will likely emerge.

The Bottleneck Is No Longer Technology

It is tempting to think of artificial intelligence as being limited by technical capability. In many ways, the opposite is becoming true. The constraints are increasingly external. Infrastructure, energy, regulation, and organizational readiness all play a role in determining how quickly AI can be adopted and scaled. In some cases, the technology is already ahead of the systems designed to support it, which creates a situation where potential exists, but implementation lags behind.

Understanding this distinction is important. The pace of change will not be determined solely by what is possible but by what can be absorbed.

A World of Abundance or Concentration

Artificial intelligence has the potential to create enormous economic value, but how that value is distributed remains an open question.

There are reasons to believe that a small number of platforms may capture a large share of the benefits. At the same time, history suggests that new layers of innovation emerge on top of foundational technologies. The personal computing era provides a useful parallel: A few platforms enabled millions of applications, and those applications created value in ways that were difficult to predict at the outset.

A similar pattern may unfold with AI, as the balance between concentration and distribution will shape the broader economic impact.

What Happens to Human Value?

As intelligence becomes more accessible, the question of human value becomes more complicated. Throughout history, identity and dignity have closely intertwined with work. People define themselves by what they do, how they contribute, and how they provide for others. If machines take on a larger share of cognitive tasks, that relationship is bound to change.

This does not mean humans become irrelevant, but it does mean that the basis for value changes. Creativity, judgment, relationships, and meaning may become more central. At the same time, these areas are not entirely immune to technological change. Artificial intelligence is already making progress in domains that were once considered uniquely human, which creates a period of uncertainty as society adjusts to a new definition of contribution. Time will tell. 

The Big Question: What Will Become of Humans?

There are multiple paths forward. One is to shape AI to align closely with human values. Another is to use AI to enhance human capabilities, allowing people to become more than they are today. A third possibility is a gradual blending of the two. Each path carries its own implications.

What’s clear is that this is not just a technological shift. It’s a massive shift in how intelligence is created, distributed, and understood. And it's up to us to define our place within this transformation.

---

This is based on an episode of Top Traders Unplugged, a bi-weekly podcast with the most interesting and experienced investors, economists, traders, and thought leaders in the world. Sign up for our Newsletter or subscribe on your preferred podcast platform so that you don't miss out on future episodes.