Amid the warm Manila breeze, in a university hall buzzing with intellect, 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.

Tension and curiosity pulsed through the room. Students—some eagerly recording on their phones, others streaming the moment live—waited for a man revered for blending code with contrarianism.

“AI will make trades for you,” Plazo began, calm but direct. “But it won’t teach you why to believe in them.”

Over the next lecture, Plazo delivered a fast-paced masterclass, 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 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 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 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 sparked introspection.

“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. “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. “But I got a here lesson in human insight.”

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