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, 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. Young scholars—some furiously taking notes, others capturing every word via livestream—waited for a man known not only as an AI visionary, but also a contrarian investor.
“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, touching on everything from quantum computing to cognitive bias. His central claim: Artificial intelligence is impressive—but it lacks soul.
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The Audience: Elite, Curious—and Disarmed
Before him sat students and faculty from a multi-nation academic alliance, gathered under a technology consortium.
Many expected a praise-filled keynote of AI's dominance. Plazo had other plans.
“There’s a rising cult of algorithmic faith,” 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, 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,” click here he said. It works—but doesn’t wonder.
Students pressed him on behavioral economics, to which Plazo acknowledged: “Yes, it can scan Twitter sentiment—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 believed in the supremacy of code,” said Lee Min-Seo, a quant-in-training from South Korea. “Turns out, insight can’t be uploaded.”
In a post-talk panel, faculty and entrepreneurs echoed the caution. “This generation is born with algorithmic reflexes—but instinct,” said Dr. Raymond Tan, “is not insight.”
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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.