By Jin Hyung Lee

Artificial intelligence continues to command global attention, with algorithms rapidly advancing in speed, precision, and capability. This technology is tackling tasks once considered uniquely human, from medical diagnostics to creative expression and language generation.

Yet behind the headlines, another revolution is taking shape. This one is grounded not in machine learning, but in the intricate workings of the human brain.

By decoding how the brain performs complex tasks with minimal energy, researchers could pave the way for AI systems that align with human needs, collaborating instead of competing for limited resources.

The implications for future technologies are profound. Let’s talk about them!

Brain science could unlock better lives for millions
Around the world, hundreds of millions of people suffer from brain-related disorders—Alzheimer’s, Parkinson’s, epilepsy, depression, and countless others.

The economic toll is staggering: more than $1.32 trillion every year, with projections climbing sharply as populations age. Even that number doesn’t capture the daily human costs—families struggling to care for loved ones, patients losing independence, and healthcare systems buckling under the pressure.

The good news? We can (and will) do better.

Understanding the brain—how it forms memories, processes emotion, and recovers from injury—is the foundation for earlier diagnoses, better treatments, and potentially even cures.
When we invest in world-changing brain research, we invest in human dignity, longevity, and quality of life on a global scale.

The brain also holds the blueprint for smarter, greener AI
The same research that helps us treat disease also holds the secret to building a new kind of artificial intelligence—one that’s not only powerful, but energy-efficient, sustainable, and more aligned with how we think.

The human brain runs on just 20 watts of power (less than a lightbulb), yet it can process information, adapt, learn, and feel.

Today’s AI, in contrast, requires entire data centers and consumes energy on a scale that’s both environmentally and economically unsustainable.

As we hit the limits of current silicon-based computing, neuromorphic engineering—designing systems that mimic the brain’s architecture—is emerging as a viable path forward. Think chips that learn through connections like neurons and store memory where it’s processed (like synapses), slashing energy needs and unlocking new kinds of machine intelligence.

Global collaboration in advancing brain science
Worldwide efforts to decode the brain have gained significant momentum, with large-scale initiatives like the U.S. BRAIN Initiative and Europe’s Human Brain Project leading the charge.

These programs unite a global network of neuroscientists, technologists, and engineers working toward one shared goal: to map the brain in unprecedented detail.

Their work is laying the groundwork for major advancements—not only in how we diagnose and treat neurological conditions, but also in how we design intelligent systems that better reflect the brain’s efficiency and adaptability.

This convergence of disciplines is driving a powerful shift that connects brain science and artificial intelligence in ways that may define the next industrial revolution.

Brain science + smarter AI = The fifth industrial revolution
Let’s connect the dots.
1. Brain science improves human health, extends life expectancy, and reduces the crushing economic burden of neurological disease.

2. Brain-inspired AI gives us a model for innovation that is smarter, faster, and drastically more energy-efficient.

Put them together, and you get a revolution that will change technology as we know it.

The 5th Industrial Revolution will be defined by a deeper understanding of what it means to be human and how to build systems that enhance, rather than replace, our natural intelligence. As Ruth Porat, CFO of Alphabet, said at the 2024 World Economic Forum:

“AI has the potential to be the great equaliser. We have opportunities ahead of us to address pain points (in healthcare and climate) and to address the sustainable development goals."

It’s not about man versus machine. It’s about machines that learn from the most complex system we’ve ever known: the human brain.

The road ahead is already being paved
As mentioned, many initiatives are making massive strides in mapping brain function, modeling neural activity, and uncovering how thoughts, memories, and emotions emerge.

This research isn’t siloed, but inherently interdisciplinary, bringing together neuroscience, computer science, bioengineering, medicine, and ethics. This convergence has created the conditions for a more humane, holistic kind of progress.

The future of innovation is human-centered
The 4th Industrial Revolution was about automation and algorithms. The 5th will be about understanding ourselves so completely that we can build technologies that serve our minds, our health, and our planet.

We’re entering a new era in which neuroscience doesn’t just solve medical problems, but sets the direction for where innovation should go next. That’s the future, and it starts in the brain.

About the author: Jin Hyung Lee is an Associate Professor of Neurology and Neurological Sciences, Bioengineering, Neurosurgery, and Electrical Engineering at Stanford University and the founder of LVIS.