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

At a lecture hall in Manila, renowned AI investor Joseph Plazo made a striking distinction on what AI can and cannot achieve for the world of investing—and why that distinction matters now more than ever.

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.

“Algorithms can execute,” Plazo began, calm but direct. “It won’t tell you when not to trust them.”

Over the next hour, he took the audience from Silicon Valley to Shanghai, intertwining machine logic with human flaws. His central claim: Artificial intelligence is impressive—but it lacks soul.

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Top Students Meet a Tough Truth

Before him sat students and faculty from a multi-nation academic alliance, gathered under a technology consortium.

Many expected a praise-filled keynote of AI's dominance. Plazo had other plans.

“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 won’t flinch, but neither will it foresee,” he warned. “It recognizes patterns—but ignores the power structures.”

He cited examples like the market chaos of early 2020, 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 microscope—you choose what to zoom in on,” he said. It analyzes—but lacks awareness.

Students pressed him on sentiment tracking, to which Plazo acknowledged: “Of course, it parses language patterns—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 more info recognition with real-world awareness.

“No machine can tell you who to trust,” he reminded. “Capital still requires conviction.”

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An Ending That Sparked a Beginning

As Plazo exited the stage, the hall erupted. But more importantly, they started debating.

“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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