BrazilWhy humans still have the edge on artificial intelligence
The rapid rise of AI is reshaping industries. Companies see enormous opportunities, but at the same time there is a growing fear that AI will displace jobs. According to Parichay Mazumdar from CGI, that fear is overhyped. “AI can become a champion of the game, but we as humans have the capacity to rewrite the rules or create a whole new game.”
A few weeks ago, I finally took the time to properly read about the AlphaFold breakthrough, and it filled me with immense hope. For days, I felt an unexpected excitement – but why? What made this story so special? It was only last week that it hit me.
I was of course amazed that AI basically solved the protein folding problem, one of biology’s largest mysteries. But it was not the AI – it was the human brains who designed it that sparked that joy. It resonated with something I strongly believe in: AI on its own is quite useless – but in the right hands, it is the amplifier of human genius.
AlphaFold didn’t decide to solve protein folding – we did. It didn’t define the problem or interpret its findings. Human curiosity, intuition, and expertise led to its creation. AI was the tool – powerful, but still just a tool.
The wrong question
This distinction is crucial because every time AI achieves something remarkable, the same debate resurfaces: Will AI replace human experts? Is human intelligence becoming obsolete?
AlphaFold is the perfect example of why that’s the wrong question to ask. The most exciting future isn’t one where AI replaces experts but one where AI and human intelligence work together, each enhancing the other.
This realization is what I want to explore. AI is undoubtedly changing the nature of expertise, but it is not making it irrelevant. Instead, it’s pushing us to redefine what expertise means in an AI-powered world. So, where do humans still hold the edge? Where does AI struggle? And how can we use AI not as a competitor, but as an ally in solving the biggest problems of our time?
To figure some of these things out, we need to think about how AI ‘thinks’ and how we humans think.
Fundamentally different
At first glance, AI and human intelligence might seem similar. Both recognize patterns, both reason through problems, and both improve over time. Yet, the way they do this is fundamentally different.
AI learns by analyzing massive amounts of data, detecting statistical relationships, and optimizing for specific objectives. It operates within a defined problem space, following the logic embedded in its training data. Humans, however, don’t just recognize patterns – we interpret them, challenge them, and even break them when necessary. Our reasoning is shaped by context, experience, and an ability to imagine beyond the given data.
Take AlphaFold as an example. Its ability to predict protein structures was nothing short of revolutionary. Decoding the shape of proteins used to take scientists years of painstaking research, and suddenly, AI could do it in hours with remarkable accuracy. But while AlphaFold could predict protein structures, it didn’t explain why they folded the way they did, nor did it propose what new, unseen structures might be possible.
The reasoning behind protein folding – the fundamental physics, the underlying biological implications – still required human expertise. Scientists had to interpret AlphaFold’s results, verify them through experimentation, and determine their broader significance for medicine and drug discovery.
The game and the rules
This highlights the fundamental difference between AI and human reasoning. AI, like AlphaFold, excels at recognizing complex patterns and predicting outcomes with superhuman accuracy. But it doesn’t generate new scientific hypotheses, rethink its own assumptions, or redefine problems. Even when AI produces novel solutions by combining existing data in unexpected ways, it remains bound by the constraints we define.
Humans, on the other hand, have the unique ability to challenge those constraints, reframe questions, and rethink the very foundations of a problem – a skill that remains essential in turning AI-generated knowledge into real-world breakthroughs.
This distinction isn’t just abstract. It plays out in critical fields like medicine, law, finance, and art, where AI assists but doesn’t replace expertise. In medicine, AI can detect tumors in scans, but only doctors can interpret the results in the context of a patient’s full health history.
In law, AI can analyze thousands of legal cases, but only human judges and lawyers can weigh ethics, intent, and justice. In finance, AI can predict market trends, but only human investors can navigate the uncertainty of global events and shifting economies. In art, AI can generate paintings and music, but only humans create with meaning, purpose, and emotional depth.
AI can become a champion of the game, but we hold the capability to re-write the rules or create an entirely new game altogether.
Hybrid intelligence
So, what does this mean for the future? If AI is becoming more capable in tasks traditionally associated with expertise, does that diminish the value of human knowledge? Not at all. Instead, it forces us to evolve how we think about expertise itself.
The professionals of the future will not be the ones who ignore AI, nor the ones who fear it, but those who understand how to use it as an extension of their intelligence. The best doctors won’t just diagnose patients – they’ll know how to integrate AI-driven diagnostics into better treatment plans.
“We’re moving toward a future where the best results will come from AI and humans working together.”
The best lawyers won’t just memorize case law – they’ll know how to use AI-assisted research tools while maintaining human judgment. The best artists won’t just paint or compose – they’ll explore new creative frontiers using AI as a medium rather than a substitute. The real competitive advantage will be human-AI collaboration.
As AI takes over pattern-heavy, data-driven tasks, human experts will have more time to focus on strategy, critical thinking, and ethical decision-making.
We are moving toward an era of hybrid intelligence, where the best results will come from AI and humans working together. The real question isn’t whether AI will replace human expertise – it’s whether we are ready to harness it to expand our own capabilities. Those who learn to collaborate with AI, rather than compete against it, will be the ones shaping the future.
