At a lecture hall in Manila, Joseph Plazo drew a bold line on what machines can and cannot do for the economic frontier—and why understanding this may define who wins in tomorrow’s markets.
Tension and curiosity pulsed through the room. A sea of bright minds—some eagerly recording on their phones, others broadcasting to friends across Asia—waited for a man both celebrated and controversial in AI circles.
“Algorithms can execute,” Plazo opened with authority. “It won’t tell you when not to trust them.”
Over the next hour, he took the audience from Silicon Valley to Shanghai, 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 celebration of AI's dominance. Instead, they got a reality check.
“There’s a growing religion around AI,” said Prof. Maria Castillo, guest faculty from Europe. “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 recognizes patterns—but ignores the power structures.”
He cited examples like machine-driven funds failing to respond to COVID news, noting, “Machines were late 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 analyzes—but lacks awareness.
Students pressed him on AI in news and social chatter, to which Plazo acknowledged: “Of course, it parses language patterns—but it can’t discern hesitation in a policymaker’s tone.”
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A Mental Shift Among Asia’s Finest
The talk sparked introspection.
“I used to think AI just needed more data,” 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 “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 read more came for machine learning,” said a PhD candidate. “But I got a lesson in human insight.”
Perhaps, in drawing boundaries for AI, we expand our own.