THE LIMITS OF ARTIFICIAL INTELLIGENCE

The Limits of Artificial Intelligence

The Limits of Artificial Intelligence

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 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 revered for blending code with contrarianism.

“Machines will execute trades flawlessly,” he said with gravity. “But understanding the why—that’s still on you.”

Over the next lecture, Plazo delivered a fast-paced masterclass, balancing data science with real-world decision making. His central claim: AI is brilliant, but blind.

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Bright Minds Confront the Machine’s Limits

Before him sat students and faculty from leading institutions like Kyoto, NUS, and HKUST, assembled under a pan-Asian finance forum.

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

“There’s a rising cult of algorithmic faith,” said Prof. Maria Castillo, a respected AI ethicist from the UK. “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 check here 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 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 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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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 candidate. “But I left understanding myself better.”

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

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