What AI Can’t Do: A Manila Lecture Shakes the Finance World
What AI Can’t Do: A Manila Lecture Shakes the Finance World
Blog Article
In a packed amphitheater at the University of the Philippines, Joseph Plazo drew a bold line 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 streaming the moment live—waited for a man revered for blending code with contrarianism.
“AI will make trades for you,” he said with gravity. “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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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, click here noting, “Machines were late to the signal. People weren’t.”
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Reclaiming the Edge: Why Humans Still Matter
Plazo didn’t argue against AI—but for boundaries.
“AI is the vehicle—but you decide the direction,” 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. “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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Standing Ovation, Unfinished Conversations
As Plazo exited the stage, the crowd rose. But more importantly, they started debating.
“I came for machine learning,” said a PhD candidate. “But I left understanding myself better.”
And maybe that’s the real power of AI’s limits: they force us to rediscover our own.