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 world of investing—and why that distinction matters now more than ever.
You could feel the electricity in the crowd. Young scholars—some clutching notebooks, others capturing every word via livestream—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 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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Top Students Meet a Tough Truth
Before him sat students and faculty from a multi-nation academic alliance, gathered under a technology consortium.
Many expected a victory lap of AI's dominance. Instead, they got a reality check.
“There’s a growing religion around AI,” said Prof. Maria Castillo, guest faculty from Europe. “Plazo’s words were uncomfortable—but essential.”
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Why AI Still Doesn’t Get It
Plazo’s core thesis was both simple and unsettling: code can’t read between the lines.
“AI doesn’t panic—but it doesn’t anticipate,” he warned. “It check here finds trends, but not intentions.”
He cited examples like machine-driven funds failing to respond to COVID news, noting, “By the time the algorithms adjusted, the humans were already positioned.”
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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 sentiment tracking, to which Plazo acknowledged: “Sure, it can flag Reddit anomalies—but it can’t feel a market’s pulse.”
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A Mental Shift Among Asia’s Finest
The talk sparked introspection.
“I believed in the supremacy of code,” said Lee Min-Seo, a quant-in-training from South Korea. “Now I realize it also needs wisdom—and that’s the hard part.”
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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Standing Ovation, Unfinished Conversations
As Plazo exited the stage, the hall erupted. But more importantly, they started debating.
“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.