WHERE AI FALLS SHORT: A CAUTIONARY TALE FOR FUTURE INVESTORS

Where AI Falls Short: A Cautionary Tale for Future Investors

Where AI Falls Short: A Cautionary Tale for Future Investors

Blog Article

Amid the warm Manila breeze, in a university hall buzzing with intellect, Joseph Plazo laid down the gauntlet on what technology can realistically offer for the world of investing—and why this difference is increasingly crucial.

The air was charged with anticipation. A sea of bright minds—some eagerly recording on their phones, 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 sixty minutes, 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 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 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 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 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 “co-intelligence”—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 check here 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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