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, Joseph Plazo laid down the gauntlet 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.

“Algorithms can execute,” Plazo began, calm but direct. “But it won’t teach you why to believe in them.”

Over the next sixty minutes, 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 machine-driven funds failing to respond to COVID news, noting, “Machines were late to the signal. People weren’t.”

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Reclaiming the Edge: Why Humans Still Matter

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 behavioral economics, to which Plazo acknowledged: “Yes, it can scan Twitter sentiment—but it can’t feel a market’s pulse.”

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The Ripple Effect on a Digital Generation

The talk sparked introspection.

“I believed in the supremacy of code,” said Lee Min-Seo, a quant-in-training from South Korea. “Turns out, insight can’t be uploaded.”

In a post-talk panel, tech mentors agreed with his sentiment. “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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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 check here candidate. “Instead, I got something more powerful—perspective.”

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

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