AI, Automation, and the Human Cost

AI has already completely changed the way we communicate, learn, and work. Language models, chatbots, and generative AI have made headlines and provided a preview of a machine intelligence-powered future.

However, the reality is that words by themselves cannot change the world. AI needs to go beyond speech and into actual physical action if it is to genuinely transform economies and civilizations.

Digital assistants and text generators are not the only innovations of the future. It has to do with robotics.

There are signs everywhere. The world’s first “Robot Olympics” were held in China, where spectators watched humanoids stumble, run, and lift.

Robots are now more intelligent and versatile than ever thanks to Nvidia’s AI-optimized chips, which have become the “Brains” of machines. Furthermore, automation isn’t just coming — it’s advancing as labor shortages put pressure on sectors around the world.

The production of things, the delivery of services, and even the provision of care will all be transformed by the robotics revolution. This article examines the history of robotics, the industries it has impacted, the nations at the forefront of the race, and the significant effects it will have on daily life, employment, and economies.

Disclaimer: I have conducted my own web research and have compiled publicly accessible data and market trends into this post. Although my goal is to provide timely and accurate observations, the financial environment is subject to rapid change, and new discoveries may arise that cast doubt on or alter the viewpoints expressed here. I don’t work as a financial advisor or journalist. Cross-referencing information and drawing their own conclusions are encouraged for readers. This material is just meant to be informative and should not be interpreted as investing or financial advice.

Image Credit Goes To DC Studio [freepik.com]

An Overview of Robotics’ Early Theories and Concepts Artificial assistants have long captivated humanity. According to Greek mythology, the island of Crete was protected by a bronze giant named Talos. Emperors were reportedly served by mechanical servants made of wood and gears in ancient China. A timeless human drive to create robots that protect, serve, or enhance our skills is revealed by these mythologies. It wasn’t until 1920 that the modern word robot appeared. It was first used by Czech playwright Karel Čapek in Rossum’s Universal Robots. In his story, people are served by artificial workers, but the partnership ends in anarchy and rebellion. A theme that has persisted ever since was hinted at in the story: Robots as both a threat and a hope.

Three Laws and Science Fiction Isaac Asimov reframed the argument in the middle of the 20th century. As long as the first two criteria are followed, his “Three Laws of Robotics” — that robots must not injure people, obey commands, and defend themselves — became legendary. This idea was expanded by science fiction and then Hollywood. Robots evoked both hopes and anxieties about technology, from friendly assistants like R2-D2 to menacing masterminds like the Terminator. But whereas fiction envisioned expansive futures, reality proceeded more slowly and steadily.

AI-Powered Machines and Assembly Lines

Roots in Industry

Unimate, the first operational industrial robot, debuted in 1961. It was installed at a General Motors facility and was designed to constantly lift hot metal components without complaining, not to win over people. It signaled the beginning of practical robotics, or devices created for functionality rather than show. With WABOT-1, a humanoid robot that could walk and grasp objects with its hands, Japan advanced the field by the 1970s. Despite its simplicity, it demonstrated the idea of human design. Honda’s ASIMO rose to fame in the early 2000s. ASIMO was able to jog, wave to crowds, and climb stairs, unlike the cumbersome robots of the past. For many, it was their first impression of an almost living robot.

The Revolution in AI

Robots were confined to stiff, repetitive jobs for decades. They were basically blind, always making the same gestures without comprehending what was going on around them. Now, that restriction is breaking down. When AI is incorporated, robots can:

• Real-time object recognition and classification.
• Adjust their motions to the new environment.
• Comprehend and obey intricate spoken instructions.
• With the help of GPU-based “brains” from firms like Nvidia, learn tasks dynamically.

This change isn’t really noticeable. Hollywood films don’t feature robots as the main characters. They are quietly integrating AI to become flexible, effective, and essential in factories, warehouses, and hospitals.

Today’s Workplaces for Robots

“Dark Manufacturing” and factories Manufacturing is the most advanced application of robotics. Whole establishments function as “Dark factories,” so called because they don’t require air conditioning, lights, or even human labor.

Every three seconds, Xiaomi’s Changping Smart Factory in China produces a new smartphone without putting a human on the line.

Packaging, testing, and assembly are done by robots.

Real-time quality monitoring by AI systems allows them to spot mistakes more quickly than any human inspector could. These establishments are open around-the-clock and have raised the bar for efficiency worldwide.

Robotic Service Workers in Everyday Life

Service robots are gradually making their way into everyday settings outside of industries.

• Robots in hospitals assist patients, clean rooms, and deliver medication.
• Packages are swiftly and precisely moved over large floors by fleets of machines in warehouses.
• Robots now serve food, provide room service, and even make coffee in hotels and restaurants.

Amazon serves as an example of the magnitude of this change. For every robot, its warehouses had five human employees in 2017.

When that ratio dropped to two people per robot by 2024, Amazon gained unmatched logistical strength.

In the meantime, robotics is being extended into public areas and logistics by drones and driverless cars, which can be used to guide passengers, clean airport floors, and replenish store shelves.

The Boundaries of Specialization

The majority of machines are still highly specialized, despite the excitement around general-purpose robots.

A bot in a warehouse can carry boxes perfectly, but it can’t pour drinks. A medical robot is capable of delivering medication, but it cannot maneuver through a busy roadway. Because specialized machines are useful, economical, and instantly lucrative, investors continue to support them.

Although general-purpose humanoids might pique interest, specialization currently covers the costs. Humanoids: Myth versus Fact

Why Construct Humanoids?

The appeal of humanoid robots is clear. Doors, tools, and stairs are all made to accommodate human bodies.

Theoretically, a machine with our shape might traverse it without requiring infrastructure change. Psychology is another. Humanoids are perceived as more personable by people. In situations such as elder care or companionship, a robot with eyes and arms is less frightening.

Engineering Difficulties

However, creating a humanoid is no easy task. After millions of years of development, humans have developed their balance, dexterity, and energy efficiency. It takes intricate networks of sensors, gyroscopes, cameras, and algorithms to replicate them in machines.

Even the most sophisticated prototypes have trouble handling everyday activities like opening doors, navigating uneven terrain, and avoiding collisions in congested areas. Leaders in the Industry

• Elon Musk has referred to the Tesla Optimus as the “Biggest product ever,” but detractors contend that the project won’t be used for years.
• Figure AI: BMW factories already employ its Figure 2 humanoid to do basic tasks.
• Boston Dynamics and Agility Robotics are leaders in mobility, creating robots with incredible agility for running, jumping, and balancing.
• Humanoids competed in China’s Robot Olympics, but many of them faltered or crashed, serving as a reminder of how far we still have to go.

The Obstacles That Remain

• Reliability: It is much more difficult to obtain near-perfect reliability (99.999%) than 90%.
• Cost: Humanoids are too expensive for widespread use, frequently costing over $100,000 per.
• Training Data: Robots do not have access to large amounts of data on physical interactions, in contrast to AI that has been trained on billions of web pages.
• AI Limits: Although powerful, current systems are not yet able to think like general-purpose intelligence.

Although they are still considered aspirational rather than necessary, humanoids have the potential to revolutionize industries in the future. The World Robotics Competition

China: Size and Velocity

The adoption of robotics around the world is now concentrated in China. It installed 276,000 new robots in 2023 alone, which is more than half of the demand worldwide. With 470 robots per 10,000 workers, it now holds the third-highest robot density in the world. China’s Made in China 2025 agenda promotes automation-driven industrial domination and “Dark factories.” However, it continues to rely significantly on foreign parts for sophisticated sensors and electronics, making it susceptible to export limitations.

South Korea: Density Leader in the World

With 1,012 robots per 10,000 workers, South Korea has the highest robot density in the world. The country is significantly ahead of other developed economies due to its heavy reliance on robotics in its electronics and automotive industries.

Germany and Japan: Historical Powerhouses

• Japan: Still the world’s second-largest market for industrial robots, Japan is home to robotics behemoths like Fanuc, Yaskawa, and Kawasaki.
• Germany: With 429 robots per 10,000 employees, this European robotics hub is bolstered by EU programs. Precision engineering and automobile manufacture are its strong points.

America: Falling Behind in Deployment

The US is just tenth in the world for robot density, while being the leader in AI software. Many analysts caution that the United States runs the risk of lagging behind in the physical layer of artificial intelligence if it does not have a cohesive national robotics plan.

Important Takeaway

Scale, depth, and intelligence are necessary for success in robotics.

• China is large.
• Germany and Japan contribute depth and manufacturing know-how.
• The United States is a leader in AI invention and software.

However, none of the three countries have yet to unite. The race around the world is still open. Economics, Employment, and Society

The Dilemma of Automation

Naturally, robotics begs the question, “What about jobs?” More than 100 million people are employed in manufacturing in China alone. Millions could be displaced due to widespread automation. The most vulnerable jobs worldwide are those that are routine and repetitive, such as manufacturing, warehousing, cleaning, and even some aspects of healthcare.

Changing Needs of the Workforce

However, automation alters employment rather than simply removing them. There are new positions appearing in:

• Repair and maintenance of robotics.
• AI supervision and security tracking.
• Process optimization and automation oversight.

Retraining presents a challenge. Low-skilled individuals cannot be quickly or easily moved into high-skilled technical professions. Winners and Losers

• Winners: Proactive countries, IT behemoths, and sophisticated manufacturers.
• Losers: Employees in low-skilled, repetitive jobs without opportunities for retraining.

Human Worth

Robots lack emotional intelligence, empathy, and creativity despite their quick advancement. The functions of educators, caregivers, therapists, and artists continue to be distinctively human. Society still relies on human interaction for the time being.

Getting Ready for the Future of Robots

The robotics revolution is real and not just a pipe dream. While humanoids make headlines, the true shift is taking place in the background as specialized machines power cities, factories, warehouses, and hospitals. These robots are already changing sectors, increasing productivity, and cutting expenses. However, the result isn’t set in stone. Who succeeds and who fails will depend on national policies, investment plans, and labor retraining.

The lessons for people are obvious:

• Invest in upskilling if the task you do is repetitious.
• Instead than fighting against automation, learn to work with it.
• Keep up with changes in technology and legislation that are affecting your sector.

The Earth won’t be overrun by robots in the future. Their ascent, however, is unavoidable and quickening. The decisions we make today will determine whether they strengthen or weaken societies.

Read the full article here: https://medium.com/@dipanshuchaudhry9/ai-automation-and-the-human-cost-8ccbafe61eb4