Where AI Falls Short: A Cautionary Tale for Future Investors
Where AI Falls Short: A Cautionary Tale for Future Investors
Blog Article
Amid the warm Manila breeze, in a university hall buzzing with intellect, Joseph Plazo laid down the gauntlet on what AI can and cannot achieve for the future of finance—and why that distinction matters now more than ever.
You could feel the electricity in the crowd. Students—some furiously taking notes, 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 opened with authority. “It won’t tell you when not to trust them.”
Over the next hour, he swept across global tech frontiers, touching on everything from quantum computing to cognitive bias. 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, an Oxford visiting fellow. “This lecture was a rare, necessary dose of skepticism.”
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When Algorithms click here 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, but misses motives.”
He cited examples like AI systems freezing during the 2020 pandemic declaration, noting, “AI lagged—while humans had already hedged.”
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The Astronomer Analogy
He didn’t bash the machines—he put them in their place.
“AI is the telescope—but you are still the astronomer,” 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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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. “Turns out, insight can’t be uploaded.”
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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Co-Intelligence: Merging Math with Meaning
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, the crowd rose. But more importantly, they lingered.
“I came for machine learning,” said a PhD candidate. “But I left understanding myself better.”
In knowing what AI can’t do, we sharpen what we can.