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 machines can and cannot do for the future of finance—and why that distinction matters now more than ever.
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.
“Machines will execute trades flawlessly,” 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, intertwining machine logic with human flaws. His central claim: AI is brilliant, but blind.
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Top Students Meet a Tough Truth
Before him sat students and faculty from prestigious universities across Asia, assembled under a pan-Asian finance forum.
Many expected a victory lap 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. website “It recognizes patterns—but ignores the power structures.”
He cited examples like the market chaos of early 2020, 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 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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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. “These kids speak machine natively—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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The Speech That Started a Thousand Debates
As Plazo exited the stage, students applauded. But more importantly, they lingered.
“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.