Where AI Falls Short: A Cautionary Tale for Future Investors

Amid the warm Manila breeze, in a university hall buzzing with intellect, Joseph Plazo laid down the gauntlet on what AI can and cannot achieve for the future of finance—and why that distinction matters now more than ever.

You could feel the electricity in the crowd. 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 it won’t teach you why to believe in them.”

Over the next lecture, Plazo delivered a fast-paced masterclass, intertwining machine logic with human flaws. His central claim: AI is brilliant, but blind.

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Top Students Meet a Tough Truth

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 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 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 microscope—you choose what to zoom in on,” he said. It works—but doesn’t wonder.

Students pressed him on AI in news and social chatter, to which Plazo acknowledged: “Yes, it can scan Twitter sentiment—but it can’t smell fear in a boardroom.”

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Asia Reflects: From Tech Worship to Tech Wisdom

The talk hit hard.

“I used to think AI just needed more data,” said Lee Min-Seo, a finance student from Seoul. “Now I see it’s judgment, not just data, that matters.”

In a post-talk panel, regional leaders backed Plazo’s call. “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 blends pattern recognition with real-world awareness.

“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 read more 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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