What AI Can’t Do: A Manila Lecture Shakes the Finance World

At a lecture hall in Manila, Joseph Plazo drew a bold line on what machines can and cannot do for the economic frontier—and why understanding this may define who wins in tomorrow’s markets.

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

“Machines will execute trades flawlessly,” he said with gravity. “But understanding the why—that’s still on you.”

Over the next lecture, he swept across global tech frontiers, touching on everything from quantum computing to cognitive bias. 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 a multi-nation academic alliance, 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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Why AI Still Doesn’t Get It

Plazo’s core thesis was both simple and unsettling: code can’t read between the lines.

“AI doesn’t panic—but it doesn’t anticipate,” he warned. “It finds trends, but not intentions.”

He cited examples like machine-driven funds failing to respond to COVID news, 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 sees—but doesn’t think.

Students read more pressed him on behavioral economics, 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 left a mark.

“I thought AI could replace intuition,” said Lee Min-Seo, a quant-in-training from South Korea. “Turns out, insight can’t be uploaded.”

In a post-talk panel, tech mentors agreed with his sentiment. “They’ve been raised by data—but instinct,” said Dr. Raymond Tan, “is only half the story.”

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Co-Intelligence: Merging Math with Meaning

Plazo shared that his firm is building “hybrid cognition models”—AI that understands not just volatility, but motive.

“Ethics can’t be outsourced to software,” he reminded. “Judgment remains human territory.”

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An Ending That Sparked a Beginning

As Plazo exited the stage, students applauded. But more importantly, they stayed behind.

“I came for machine learning,” said a PhD candidate. “But I got a lesson in human insight.”

Perhaps, in drawing boundaries for AI, we expand our own.

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