The Limits of Artificial Intelligence
The Limits of Artificial Intelligence
Blog Article
At a lecture hall in Manila, renowned AI investor Joseph Plazo laid down the gauntlet on what technology can realistically offer for the world of investing—and why that distinction matters now more than ever.
The air was charged with anticipation. 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 sixty minutes, Plazo delivered a fast-paced masterclass, balancing data science with real-world decision making. His central claim: AI is brilliant, but blind.
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Bright Minds Confront the Machine’s Limits
Before him sat students and faculty from prestigious universities across Asia, 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 won’t flinch, but neither will it foresee,” he warned. “It detects movements, but misses motives.”
He cited examples like the market chaos of early 2020, noting, “AI lagged—while humans had already hedged.”
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Wisdom in a World of Code
Plazo didn’t argue against AI—but for boundaries.
“AI is the microscope—you choose what to zoom in on,” he said. It analyzes—but lacks awareness.
Students pressed him on AI in news and social chatter, to which Plazo acknowledged: “Of course, it parses language patterns—but it can’t smell fear in a boardroom.”
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Asia Reflects: From Tech Worship to Tech Wisdom
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 here 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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The Future Isn’t Autonomous—It’s Collaborative
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.