The Limits of Artificial Intelligence

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. Young scholars—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 victory lap of AI's dominance. Instead, they got a reality check.

“There’s too much blind trust in code,” said Prof. Maria Castillo, an Oxford visiting fellow. “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: machines lack context.

“AI is fearless, but also clueless,” he warned. “It detects movements, but misses motives.”

He cited examples like AI systems freezing during the 2020 pandemic declaration, noting, “AI lagged—while humans had already hedged.”

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The Astronomer Analogy

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

“AI is the telescope—but you are still the astronomer,” he said. It sees—but doesn’t think.

Students pressed him on sentiment tracking, to which Plazo acknowledged: “Sure, it can flag Reddit anomalies—but it can’t feel a market’s pulse.”

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A Mental Shift Among Asia’s Finest

The talk sparked introspection.

“I believed in the supremacy of code,” said Lee Min-Seo, a quant-in-training from South Korea. “Now I realize it also needs wisdom—and that’s check here 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 recognition with real-world awareness.

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

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Standing Ovation, Unfinished Conversations

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

“I came for machine learning,” said a PhD candidate. “But I left understanding myself better.”

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

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