THE LIMITS OF ARTIFICIAL INTELLIGENCE

The Limits of Artificial Intelligence

The Limits of Artificial Intelligence

Blog Article

In a packed amphitheater at the University of the Philippines, Joseph Plazo drew a bold line on what technology can realistically offer for the economic frontier—and why this difference is increasingly crucial.

Tension and curiosity pulsed through the room. A sea of bright minds—some eagerly recording on their phones, others streaming the moment live—waited for a man revered for blending code with contrarianism.

“AI will make trades for you,” he said with gravity. “But it won’t teach you why to believe in them.”

Over the next lecture, Plazo delivered a fast-paced masterclass, balancing data science with real-world decision making. His central claim: Machines are powerful, but not wise.

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The Audience: Elite, Curious—and Disarmed

Before him sat students and faculty from leading institutions like Kyoto, NUS, and HKUST, gathered under a technology consortium.

Many expected a praise-filled keynote of AI's dominance. Plazo had other plans.

“There’s a rising cult of algorithmic faith,” said Prof. Maria Castillo, a respected AI ethicist from the UK. “We need this kind of discomfort in academia.”

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The Machine’s Blindness: Plazo’s Case for Caution

Plazo’s core thesis was both simple and unsettling: AI does not grasp nuance.

“AI won’t flinch, but neither will it foresee,” he warned. “It recognizes patterns—but ignores the power structures.”

He cited examples like the market chaos of early 2020, noting, “By the time the algorithms adjusted, the humans were already positioned.”

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Reclaiming the Edge: Why Humans Still Matter

Rather than dismiss AI, Plazo proposed a partnership.

“AI is the vehicle—but you decide the direction,” he said. It works—but doesn’t wonder.

Students pressed him on behavioral economics, Joseph Plazo to which Plazo acknowledged: “Yes, it can scan Twitter sentiment—but it can’t feel a market’s pulse.”

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The Ripple Effect on a Digital Generation

The talk sparked introspection.

“I believed in the supremacy of code,” said Lee Min-Seo, a quant-in-training from South Korea. “Now I realize it also needs wisdom—and that’s the hard part.”

In a post-talk panel, faculty and entrepreneurs echoed the caution. “This generation is born with algorithmic reflexes—but instinct,” said Dr. Raymond Tan, “is not insight.”

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What’s Next? AI That Thinks in Narratives

Plazo shared that his firm is building “co-intelligence”—AI that blends pattern recognition with real-world awareness.

“No machine can tell you who to trust,” he reminded. “Capital still requires conviction.”

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Standing Ovation, Unfinished Conversations

As Plazo exited the stage, the crowd rose. But more importantly, they started debating.

“I came for machine learning,” said a PhD candidate. “But I left understanding myself better.”

In knowing what AI can’t do, we sharpen what we can.

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