At a lecture hall in Manila, Joseph Plazo made a striking distinction on what machines can and cannot do 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 both celebrated and controversial in AI circles.

“Algorithms can execute,” Plazo began, calm but direct. “It won’t tell you when not to trust them.”

Over the next sixty minutes, 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 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, an Oxford visiting fellow. “We need this kind of discomfort in academia.”

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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 recognizes patterns—but ignores the power structures.”

He cited examples like the market chaos of early 2020, noting, “Machines were late more info to the signal. People weren’t.”

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Reclaiming the Edge: Why Humans Still Matter

Rather than dismiss AI, Plazo proposed a partnership.

“AI is the microscope—you choose what to zoom in on,” he said. It works—but doesn’t wonder.

Students pressed him on AI in news and social chatter, to which Plazo acknowledged: “Yes, it can scan Twitter sentiment—but it can’t smell fear in a boardroom.”

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The Ripple Effect on a Digital Generation

The talk left a mark.

“I thought AI could replace intuition,” 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, 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.”

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