🧠 Why AI Feels Wrong When It Gets Everything Right

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Welcome back AI prodigies!

In today’s Sunday Special:

• 📜The Prelude

• 🤖Limitations of Technological Progress

• 🛒The Customer Service Case Study

• 🍺The Consumer Backlash Brews

• 🔑Key Takeaway

Read Time: 7 minutes

🎓Key Terms

• Voice Agent: An autonomous virtual employee designed to communicate like humans.

• AI Trustworthiness: The confidence that AI Models will behave fairly, safely, and predictably. In short, performance alone doesn’t satisfy humans.

🩺 PULSE CHECK

📜THE PRELUDE

You crouch with muscles coiled like springs, camouflaged by the frost-coated tall grass. Your tribe’s been hunting woolly mammoths from dawn to dusk, tracking these beasts one by one across the frozen frontier. The broken spears and crushed tribesmen signal the price of survival.

But today, your tribe’s chief unveils a new strategy: force the herd over the jagged edge of a snowy cliff. You fan out across the frozen tundra with torches flaring like wildfires. Suddenly, a wave of chaotic shouts and primal roars tears at the silence.

At first, the woolly mammoths shuffle cautiously. Then, panic ripples throughout the herd. They surge forward, hooves shaking the ice-crusted soil beneath you, before disappearing over the snowy cliff’s edge one by one.

You’re triumphant. The new strategy yields so much success that the tribe repeats it with each passing season. But with the next thaw, the frozen tundra lies empty. What felt like a genius new strategy wiped out the local woolly mammoth population. You created a new problem far greater than the first.

Today, we face the same unintended consequences. AI advancements promise efficiency, convenience, and capability. And it delivers. Despite this, each problem solved seems to spark another, forcing us to consider: “If AI does more for us, why do we often still feel worse off?”

🤖LIMITATIONS OF TECHNOLOGICAL PROGRESS

⦿ 1️⃣ Three Assumptions of Progress?

Humans are naturally drawn to measure progress by looking backward. Individually, we compare old photos, past friends, and former habits. Societally, we measure changes across health, wealth, and longevity.

In 1900, the average life expectancy of a newborn was 32 years. By 2021, it had more than doubled to 71 years. In 1990, nearly 45% of the world lived in extreme poverty. By 2021, that number had fallen below 10%.

The scientific breakthroughs and industrial revolutions improved the average life expectancy and enhanced the average quality of life. But this success story of innovation and progress depends on three default assumptions:

1. 🟢 Linearity: Tomorrow will automatically be better than today.

2. 🟡 Aggregation: Improving averages is assumed to help everyone.

3. 🔴 Basic Metrics: Progress is judged by what’s easy to count.

These default assumptions can blind us to the ways efficiency quietly erodes our daily satisfaction.

⦿ 2️⃣ How Progress Limits Our Mindset?

It turns out twentieth-century philosophers saw this coming. In 1949, German philosopher Martin Heidegger coined the term Gestell (i.e., “Enframing”) to describe how modern technological progress reshapes our worldview. Nothing possesses inherent worth; everything is reduced to a resource. A river isn’t a natural wonder; it’s hydroelectric potential. A person isn’t an individual; they’re labor waiting to be tapped.

This data-driven mindset strips away autonomy, meaning, and dignity. In other words, if we view everything and everyone through the lens of utility, we lose the ability to appreciate any intrinsic worth. In a data-driven society, people literally become data points, while efficiency reigns supreme, threatening the very human values that modern technological progress aims to enhance.

⦿ 3️⃣ How Progress Limits Our Behavior?

In 1945, French sociologist Jacques Ellul extended this critique in “The Technological Society,” where he examined how modern technological progress reshapes our behavior. He argued that modern civilization has become ruled by La Technique: the relentless, all-consuming pursuit of maximum efficiency.

“The only thing that matters [to technique] is yield,” Ellul wrote, “and this yield can only be obtained by the total mobilization of human beings, body and soul.” Where Heidegger warned that we start to think like machines, Ellul warned that we begin to act like machines. Simply put, efficiency-obsessed leaders say, “If we can do it, we must do it.” Few pause to ask, “Should we do it?”

🛒THE CUSTOMER SERVICE CASE STUDY

⦿ 4️⃣ Progress FOR Whom?

Today, frontier AI firms like OpenAI and Anthropic follow Ellul’s dogma. If something can be built faster, smarter, or cheaper, they must build it because fierce competitors are building it too. With AI, hesitating doesn’t just cost profits; it costs our way of life. The U.S. frames AI developments as an existential technological race with China. In other words, slowing down AI developments risks sacrificing free speech and the military dominance of the Western world.

When efficiency reigns supreme, fueled by the Global AI Arms Race, customers become a bottleneck in the process. Every other customer-centric value gets downgraded. That’s exactly what we’re witnessing across customer service initiatives right now.

⦿ 5️⃣ Customer Service Without Human Touch?

For Big Tech companies, the math is irresistible. If you implement Voice Agents into your customer service, you can handle up to 70% of common customer inquiries swiftly while cutting operational costs by about 30%. It’s scalable, efficient, and brutally effective at reducing employee headcount and shrinking customer wait times.

But that very success explains why so many customers want to pull their hair out. Even when Voice Agents resolve the customer’s complaint, the interaction feels unempathetic and inflexible. These autonomous virtual employees are optimized around Ellul’s single criterion: “yield.” But sometimes the best way to help customers is to empathize with their frustration.

In blind tests where customers didn’t know they were talking to a Voice Agent, satisfaction levels still came in lower than with human representatives, purely because something felt off. It turns out that well-functioning Voice Agents might efficiently handle 10 routine customer complaints within the same time a human representative handles one. But if 9 out of those 10 customers feel like they weren’t truly heard, respected, or helped, it doesn’t matter. No wonder 64% of U.S. consumers wish Big Tech companies wouldn’t use any form of AI in customer service.

🍺THE CONSUMER BACKLASH BREWS

⦿ 6️⃣ How the World REALLY Feels About AI?

The Pew Research Center surveyed 36,961 citizens across 25 countries spanning six global regions to learn how people around the world feel about AI. 42% are equally concerned and excited, 34% are more concerned than excited, and 16% are more excited than concerned.

In the U.S., skepticism around AI is accelerating. In 2022, 38% of Americans felt more concerned than excited about the transformative potential of the technology. By 2025, that figure reached 50%. AI isn’t facing a tiny wave of anti-tech Luddites; it’s facing mainstream skepticism.

🔑KEY TAKEAWAY

When efficiency becomes the only measurements of modern technological progress, we risk sacrificing what makes humans feel valued. AI earns trust not through speed or scale, but by making people feel seen and valued.

📒FINAL NOTE

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