Where AI Falls Short: A Cautionary Tale for Future Investors

At a lecture hall in Manila, tech entrepreneur and investment icon Joseph Plazo made a striking distinction on what machines can and cannot do for the economic frontier—and why this difference is increasingly crucial.

The air was charged with anticipation. Students—some furiously taking notes, 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 understanding the why—that’s still on you.”

Over the next lecture, he swept across global tech frontiers, balancing data science with real-world decision making. His central claim: Machines are powerful, but not wise.

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Bright Minds Confront the Machine’s Limits

Before him sat students and faculty from prestigious universities across Asia, assembled under a pan-Asian finance forum.

Many expected a victory lap of AI's dominance. Instead, they got a reality check.

“There’s a growing religion around AI,” said Prof. Maria Castillo, guest faculty from Europe. “Plazo’s words were uncomfortable—but essential.”

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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 click here 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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The Astronomer Analogy

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 pressed him on behavioral economics, to which Plazo acknowledged: “Sure, it can flag Reddit anomalies—but it can’t feel a market’s pulse.”

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A Mental Shift Among Asia’s Finest

The talk sparked introspection.

“I used to think AI just needed more data,” said Lee Min-Seo, a finance student from Seoul. “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 “symbiotic systems”—AI that pairs statistical logic with situational nuance.

“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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