Where AI Falls Short: A Cautionary Tale for Future Investors
Where AI Falls Short: A Cautionary Tale for Future Investors
Blog Article
In a packed amphitheater at the University of the Philippines, tech entrepreneur and investment icon 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. Young scholars—some clutching notebooks, others streaming the moment live—waited for a man known not only as an AI visionary, but also a contrarian investor.
“Algorithms can execute,” 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: AI is brilliant, but blind.
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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, click here 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, 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 telescope—but you are still the astronomer,” he said. It analyzes—but lacks awareness.
Students pressed him on sentiment tracking, to which Plazo acknowledged: “Of course, it parses language patterns—but it can’t discern hesitation in a policymaker’s tone.”
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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 realize it also needs wisdom—and that’s the hard part.”
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 “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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Standing Ovation, Unfinished Conversations
As Plazo exited the stage, the crowd rose. But more importantly, they lingered.
“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.