Where AI Falls Short: A Cautionary Tale for Future Investors

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,” he said with gravity. “But understanding the why—that’s still on you.”

Over the next hour, he swept across global tech frontiers, balancing data science with real-world decision making. His central claim: Machines are powerful, but not wise.

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Bright Minds Confront the Machine’s Limits

Before him sat students and faculty from prestigious universities across Asia, 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, guest faculty from Europe. “This lecture was a rare, necessary dose of skepticism.”

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When Algorithms Miss the Mark

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

He didn’t bash the machines—he put them in their place.

“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: “Sure, it can flag Reddit anomalies—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, 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. “Belief isn’t programmable.”

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The Speech That Started a Thousand Debates

As Plazo exited the stage, students applauded. But more importantly, they lingered.

“I came for machine learning,” said a PhD candidate. “But I got a lesson in human insight.”

And maybe that’s the real power of AI’s limits: they force us to rediscover our here own.

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