AI cannot mimic human actions done without "thinking" effectively yet.
Driving a car involves a mix of skills and awareness that can't simply be taught through words or texts. Many aspects, like starting the car, reversing, and shifting gears, require practical experience. You can watch someone drive from the passenger seat, but ultimately, you have to take control yourself”steer, feel the road, practice gear changes, and use the brakes. To learn to drive, you need to engage both your body and your brain”using your senses and common sense together.
Becoming a proficient driver means reaching a stage where your actions become automatic, requiring little conscious thought. If learning to drive were merely about this, artificial intelligence (AI) could excel at it. However, AI hasn't mastered driving because it demands rapid pattern recognition, quick decision-making, and immediate responses to avoid accidents, especially in diverse and challenging conditions like bad weather or encountering unpredictable elements such as other drivers, pedestrians, or animals. Even leading companies with substantial resources struggle to develop algorithms that can handle every driving scenario. So, while driving might feel second nature to us once we've learned it, the complexity of real-world driving remains a formidable challenge for technology.
The Reality of AI in Everyday Chaos
Amid daily life's messy and unpredictable nature, there's a belief among developers and investors that AI, armed with massive data, will soon master these chaotic environments. However, current AI capabilities are mostly confined to controlled settings tailored for them. For instance, AI excels in managing conditions within modern Google server farms but struggled when a 75-year-old high school replaced its janitor with automated sensors. This was due to the technology's inability to match the janitor's nuanced understanding of the building's unique and intricate characteristics, such as its outdated windows and boilers.
Western dualism separates mind from body, restricting œthinking to the brain.
René Descartes, the 17th-century French philosopher, introduced Cartesian dualism, which proposes that the mind and body operate independently. This concept, pivotal in the "Age of Reason," has profoundly shaped Western philosophy. Descartes viewed the body as a vessel controlled by the mind, which he deemed superior and distinct. According to Cartesian philosophy, the body's intelligence is comparable to a mechanical device following the mind's directives. Descartes' philosophy tends to minimize the significance of senses and emotions, considering them unreliable distractions, while advocating for rational thought driven by the intellect of the mind, thus laying the groundwork for modern scientific methods emphasizing experimentation and evidence-based reasoning.
Descartes' ideas have influenced human thinking for centuries, even contributing to the development of computing. However, intelligence isn't just a brain function”it's shaped by how our bodies interact with the world around us. Descartes believed the body was merely a tool for the mind, famously stating, "I think, therefore I am." Yet, our bodies aren't just sensors; they play a vital role in how we understand the world. Through our experiences and interactions, both body and brain gain knowledge. So, rather than viewing the body as a passive tool, consider it a key source of intelligence.
Big data provides raw, uncontextualized information.

Algorithms can sift through huge amounts of data to spot patterns and even predict when and where crimes might happen. But to make sense of these predictions, analysts need to connect the data to real-life situations and experiences.
Today's students will confront strong competition from advanced AI. Humans excel in practical skills and real-world knowledge, but schools often emphasize memorization over hands-on learning, an area where machines surpass humans. Many students fail to see the relevance of their school-based learning, which mainly occurs in passive classroom settings, lacking the engaging, active experiences needed for real-world readiness.
Learn through Experience

Think about how you react at a music concert. You don't just listen; you feel the music deep inside. Your body responds, moving with the rhythm alongside thousands of others in the crowd. This physical connection is all about experiencing the music, not overthinking or analyzing it. This sensory learning isn't just for kids; it's something we all do, especially when it comes to music. You probably "felt" the music more than you analyzed it.
When you learn to cook a new dish, you might start by following a recipe closely. But after a while, something interesting happens. Your body seems to take over, and you can cook that dish almost automatically, even if you're busy talking on the phone or watching TV. Many things we do each day happen without us thinking about them. Life is full of routines and experiences that become almost second nature to us. This is what we call embodied knowledge.
Gain practical wisdom by watching, doing, feeling, and repeating.

When you repeatedly do something, your body and senses learn and remember without much effort. For instance, as an artist, you reach a point where painting becomes second nature. Instead of focusing on how to paint, you can concentrate on what you want to paint and the emotions you want to convey. This deep understanding and skill allow you to express your artistic vision more freely.

Learn embodied knowledge through five key methods.

• Experience with All Your Senses: Learning isn't just about watching”it's about feeling and doing. When you watch a skilled tennis player, your brain and body react as if you're playing too. You can almost feel the movements and hear the racket hitting the ball.
• Practice Makes Perfect: You can't learn to ride a bike just by watching. Skills like skiing or sailing require hands-on experience, practice, and guidance. With enough practice, these activities become second nature.
• Adapting to the Unpredictable: Life isn't like a game with set rules. The ability to learn from trial and error, recognize patterns, and make decisions with incomplete information is vital. For instance, firefighters can sense when a building might collapse based on patterns they've learned over time”they can œfeel it.
• Understand Through Empathy: To truly understand how someone uses tools or moves through the world, engage all your senses. Mirror neurons in your brain help you relate to others' feelings through their expressions and body language.
• Memory in Motion: Memories aren't just in your brain”your body holds them too. Tasting or smelling something can trigger vivid memories. Muscle memory allows you to perform tasks automatically, without much conscious thought.

Create a strong plan using emotional and experiential understanding.
Companies spend big on gathering and analyzing data to predict market trends, but the stock market isn't just about numbers”logic and feelings drive it. Many business leaders believe that more data means a better understanding of consumers, but data alone isn't the whole picture. Relying solely on data can disconnect businesses from their customers' real-life experiences. Decision-makers need experience to use data effectively and make meaningful insights.

Duracell's marketing team wanted to learn about the outdoor market for their products. So, they flew to California and went camping for three days. They set up tents at night, cooked meals in the rain, and slept in different temperatures. By experiencing camping firsthand, the marketers discovered how campers use and depend on their batteries. This adventure led to one of Duracell's most successful advertising campaigns ever.
Innovative Business Strategies

Facebook's success in reaching emerging markets partly stems from its engineers spending time in rural India. They used the same types of phones and internet connections as local users, even when back in Silicon Valley. Procter & Gamble improved its organic and sustainable products based on feedback from developers who tested prototypes in their own homes.

Business leaders and policymakers often rely heavily on numbers to make decisions. But when they step into simulations, like living as a refugee for a weekend, their views change a lot. After facing some of the struggles refugees deal with every day, policymakers start asking more natural questions and looking at a wider range of solutions. Similarly, Larry Summers, a famous economist, had an eye-opening experience after traveling 2,000 miles through the American West. He realized that understanding the economy isn't just about crunching data; it's also about immersing yourself in the towns, streets, and people of the economy.
Develop exceptional products using insights from direct experiences.
Pixar ensures every movie feels authentic by sending its staff to real-world locations depicted in the films, like the mountains of Wyoming or the kitchens of top restaurants in Paris. By experiencing these places firsthand”touching, smelling, and listening”they gain insights that enhance the animation. This attention to detail, from a stove smudge to the look of a cloud, makes Pixar's movies feel incredibly lifelike and captivating for audiences. Everything just œfeels right.

When Motorola decided to create a phone for underserved markets worldwide, its designers went straight to the favelas of Brazil. They met with users there who explained what worked and what didn™t with existing phone features. For instance, they found that a complicated way to send an SOS message wasn™t practical. This hands-on approach to design, known as œbody storming, helped create a new product that became the best-selling phone in Motorola's history.

AI and robotics can learn from experience to progress.

Efforts to make AI and robots replicate human intelligence and skills purely through data have fallen short. Developers now realize that for AI and robots to progress, they need to learn from real-world experiences, much like humans do.
Some tasks have seen success with a different approach to artificial intelligence. Instead of relying solely on data analysis, AI that learns by repeating actions and trying various strategies has outperformed humans in complex games. However, in most real-world situations, humans still hold the upper hand. AI might never match the quick thinking required for driving, or the precise physical abilities needed to interact with and learn from the real world.