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, Joseph Plazo drew a bold line on what AI can and cannot achieve for the world of investing—and why that distinction matters now more than ever.
The air was charged with anticipation. Young scholars—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, an Oxford visiting fellow. “This lecture was a rare, necessary dose of skepticism.”
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When Algorithms Miss the Mark
Plazo’s core thesis was both simple and unsettling: machines lack context.
“AI is fearless, but also clueless,” he warned. “It detects movements, website but misses motives.”
He cited examples like AI systems freezing during the 2020 pandemic declaration, 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 vehicle—but you decide the direction,” 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 feel a market’s pulse.”
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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 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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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.”
Perhaps, in drawing boundaries for AI, we expand our own.