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 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 lecture, he swept across global tech frontiers, balancing data science with real-world decision making. His central claim: Machines are powerful, but not wise.
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Bright Minds Confront the Machine’s Limits
Before him sat students and faculty from prestigious universities across Asia, united by a shared fascination with finance and AI.
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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When Algorithms Miss the Mark
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 get more info 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
Rather than dismiss AI, Plazo proposed a partnership.
“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: “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 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 “hybrid cognition models”—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.”
Perhaps, in drawing boundaries for AI, we expand our own.