What AI Can’t Do: A Manila Lecture Shakes the Finance World
At a lecture hall in Manila, Joseph Plazo laid down the gauntlet on what technology can realistically offer for the world of investing—and why this difference is increasingly crucial.The air was charged with anticipation. 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.
“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, 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 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 more info anomalies—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 believed in the supremacy of code,” said Lee Min-Seo, a finance student from Seoul. “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, “doesn’t replace perspective.”
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The Future Isn’t Autonomous—It’s Collaborative
Plazo shared that his firm is building “symbiotic systems”—AI that pairs statistical logic with situational nuance.
“Only you can judge character,” he reminded. “Belief isn’t programmable.”
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Standing Ovation, Unfinished Conversations
As Plazo exited the stage, the crowd rose. But more importantly, they lingered.
“I came for machine learning,” said a PhD candidate. “But I got a lesson in human insight.”
And maybe that’s the real power of AI’s limits: they force us to rediscover our own.