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.
Tension and curiosity pulsed through the room. 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.
“AI will make trades for you,” he said with gravity. “But understanding the why—that’s still on you.”
Over the next lecture, he swept across global tech frontiers, 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. What they received was a provocation.
“There’s too much blind trust in code,” said Prof. Maria Castillo, a respected AI ethicist from the UK. “We need this kind of discomfort in academia.”
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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. “It recognizes patterns—but ignores the power structures.”
He cited examples like the market chaos of early 2020, check here 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 microscope—you choose what to zoom in on,” he said. It works—but doesn’t wonder.
Students pressed him on AI in news and social chatter, to which Plazo acknowledged: “Yes, it can scan Twitter sentiment—but it can’t smell fear in a boardroom.”
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The Ripple Effect on a Digital Generation
The talk left a mark.
“I thought AI could replace intuition,” said Lee Min-Seo, a quant-in-training from South Korea. “Now I see it’s judgment, not just data, that matters.”
In a post-talk panel, tech mentors agreed with his sentiment. “They’ve been raised by data—but instinct,” said Dr. Raymond Tan, “is only half the story.”
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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 started debating.
“I came for machine learning,” said a PhD candidate. “Instead, I got something more powerful—perspective.”
In knowing what AI can’t do, we sharpen what we can.