The Limits of Artificial Intelligence
The Limits of Artificial Intelligence
Blog Article
At a lecture hall in Manila, renowned AI investor Joseph Plazo laid down the gauntlet on what AI can and cannot achieve for the future of finance—and why understanding this may define who wins in tomorrow’s markets.
Tension and curiosity pulsed through the room. Students—some furiously taking notes, others streaming the moment live—waited for a man revered for blending code with contrarianism.
“Machines will execute trades flawlessly,” he said with gravity. “But understanding the why—that’s still on you.”
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 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 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 vehicle—but you decide the direction,” 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 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, 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 “hybrid cognition models”—AI that understands not just volatility, but motive.
“Ethics can’t be outsourced to software,” he reminded. “Judgment remains human territory.”
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An Ending That Sparked a Beginning
As Plazo exited the stage, students applauded. But more importantly, they stayed behind.
“I came for machine learning,” said a PhD here candidate. “But I got a lesson in human insight.”
And maybe that’s the real power of AI’s limits: they force us to rediscover our own.