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

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 that distinction matters now more than ever.

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. “But understanding the why—that’s still on you.”

Over the next hour, he swept across global tech frontiers, touching on everything from quantum computing to cognitive bias. His central claim: Machines are powerful, but not wise.

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The Audience: Elite, Curious—and Disarmed

Before him sat students and faculty from leading institutions like Kyoto, NUS, and HKUST, united by a shared fascination with finance and AI.

Many expected a celebration of AI's dominance. What they received was a provocation.

“There’s too much blind trust in code,” said Prof. Maria Castillo, an Oxford visiting fellow. “This lecture was a website rare, necessary dose of skepticism.”

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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 detects movements, but misses motives.”

He cited examples like the market chaos of early 2020, noting, “AI lagged—while humans had already hedged.”

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Wisdom in a World of Code

Plazo didn’t argue against AI—but for boundaries.

“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 left a mark.

“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, 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.

“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, the hall erupted. 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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