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

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In a packed amphitheater at the University of the Philippines, Joseph Plazo laid down the gauntlet on what AI can and cannot achieve for the future of finance—and why understanding this may define who wins in tomorrow’s markets.

You could feel the electricity in the crowd. Students—some furiously taking notes, others capturing every word via livestream—waited for a man known not only as an AI visionary, but also a contrarian investor.

“Machines will execute trades flawlessly,” Plazo opened with authority. “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: AI is brilliant, but blind.

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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 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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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 works—but doesn’t wonder.

Students here pressed him on behavioral economics, to which Plazo acknowledged: “Yes, it can scan Twitter sentiment—but it can’t smell fear in a boardroom.”

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The Ripple Effect on a Digital Generation

The talk left a mark.

“I thought AI could replace intuition,” said Lee Min-Seo, a quant-in-training from South Korea. “Now I see it’s judgment, not just data, that matters.”

In a post-talk panel, tech mentors agreed with his sentiment. “They’ve been raised by data—but instinct,” said Dr. Raymond Tan, “is only half the story.”

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Co-Intelligence: Merging Math with Meaning

Plazo shared that his firm is building “hybrid cognition models”—AI that understands not just volatility, but motive.

“Ethics can’t be outsourced to software,” he reminded. “Judgment remains human territory.”

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An Ending That Sparked a Beginning

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.”

Perhaps, in drawing boundaries for AI, we expand our own.

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