WHAT AI CAN’T DO: A MANILA LECTURE SHAKES THE FINANCE WORLD

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

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

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In a packed amphitheater at the University of the Philippines, renowned AI investor Joseph Plazo made a striking distinction on what AI can and cannot achieve for the future of finance—and why understanding this may define who wins in tomorrow’s markets.

Tension and curiosity pulsed through the room. Students—some furiously taking notes, 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, balancing data science with real-world decision making. His central claim: AI is brilliant, but blind.

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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. “This lecture was a rare, necessary dose of skepticism.”

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When Algorithms Miss the Mark

Plazo’s core thesis was both simple and unsettling: machines lack context.

“AI is fearless, but also clueless,” he warned. “It finds trends, but not intentions.”

He cited examples like machine-driven funds failing to respond to COVID news, noting, “Machines were late to the signal. People weren’t.”

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Wisdom in a World of Code

Plazo didn’t argue against AI—but for boundaries.

“AI is the telescope—but you are still the astronomer,” he said. It analyzes—but lacks awareness.

Students pressed him on sentiment tracking, to which Plazo acknowledged: “Sure, it can flag Reddit anomalies—but it can’t discern hesitation in a policymaker’s tone.”

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A Mental Shift more info 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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The Future Isn’t Autonomous—It’s Collaborative

Plazo shared that his firm is building “symbiotic systems”—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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