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 drew a bold line on what technology can realistically offer for the world of investing—and why that distinction matters now more than ever.
You could feel the electricity in the crowd. 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.
“Machines will execute trades flawlessly,” Plazo opened with authority. “But understanding the why—that’s still on you.”
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 prestigious universities across Asia, assembled under a pan-Asian finance forum.
Many expected a victory lap of AI's dominance. Instead, they got a reality check.
“There’s too much blind trust in code,” said Prof. Maria Castillo, guest faculty from Europe. “This lecture was a rare, necessary dose of skepticism.”
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When Algorithms Miss the Mark
Plazo’s core thesis was both simple and unsettling: machines lack context.
“AI doesn’t panic—but it doesn’t anticipate,” he warned. “It detects movements, but misses motives.”
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 click here 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.