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
Amid the warm Manila breeze, in a university hall buzzing with intellect, tech entrepreneur and investment icon 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 clutching notebooks, 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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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. Plazo had other plans.
“There’s a rising cult of algorithmic faith,” said Prof. Maria Castillo, a respected AI ethicist from the UK. “We need this kind of discomfort website in academia.”
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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 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 hit hard.
“I used to think AI just needed more data,” said Lee Min-Seo, a finance student from Seoul. “Now I see it’s judgment, not just data, that matters.”
In a post-talk panel, regional leaders backed Plazo’s call. “These kids speak machine natively—but instinct,” said Dr. Raymond Tan, “doesn’t replace perspective.”
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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.
“Only you can judge character,” he reminded. “Belief isn’t programmable.”
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The Speech That Started a Thousand Debates
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 lesson in human insight.”
Perhaps, in drawing boundaries for AI, we expand our own.