Where AI Falls Short: A Cautionary Tale for Future Investors

Amid the warm Manila breeze, in a university hall buzzing with intellect, tech entrepreneur and investment icon Joseph Plazo made a striking distinction on what AI can and cannot achieve for the world of investing—and why this difference is increasingly crucial.

The air was charged with anticipation. Young scholars—some clutching notebooks, others broadcasting to friends across Asia—waited for a man both celebrated and controversial in AI circles.

“AI will make trades for you,” Plazo began, calm but direct. “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: AI is brilliant, but blind.

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Bright Minds Confront the Machine’s Limits

Before him sat students and faculty from leading institutions like Kyoto, NUS, and HKUST, united by a shared fascination with finance and AI.

Many expected a celebration of AI's dominance. What they received was a provocation.

“There’s too much blind trust in code,” said Prof. Maria Castillo, an Oxford visiting fellow. “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 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 check here 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 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. “These kids speak machine natively—but instinct,” said Dr. Raymond Tan, “doesn’t replace perspective.”

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The Future Isn’t Autonomous—It’s Collaborative

Plazo shared that his firm is building “symbiotic systems”—AI that pairs statistical logic with situational nuance.

“Only you can judge character,” he reminded. “Belief isn’t programmable.”

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The Speech That Started a Thousand Debates

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

“I came for machine learning,” said a PhD candidate. “Instead, I got something more powerful—perspective.”

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

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