The Limits of Artificial Intelligence
The Limits of Artificial Intelligence
Blog Article
At a lecture hall in Manila, tech entrepreneur and investment icon Joseph Plazo made a striking distinction on what machines can and cannot do for the economic frontier—and why this difference is increasingly crucial.
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 leading institutions like Kyoto, NUS, and HKUST, united by a shared fascination with finance and AI.
Many expected a celebration of AI's dominance. What they received was a provocation.
“There’s too much blind trust in code,” said Prof. Maria Castillo, an Oxford visiting fellow. “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 is fearless, but also clueless,” he warned. “It detects movements, but misses motives.”
He cited examples like AI systems freezing during the 2020 pandemic declaration, noting, “AI lagged—while humans had already hedged.”
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Wisdom in a World of Code
He didn’t bash the machines—he put them in their place.
“AI is the telescope—but you are still more info the astronomer,” he said. It analyzes—but lacks awareness.
Students pressed him on sentiment tracking, to which Plazo acknowledged: “Of course, it parses language patterns—but it can’t discern hesitation in a policymaker’s tone.”
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A Mental Shift Among Asia’s Finest
The talk hit hard.
“I used to think AI just needed more data,” said Lee Min-Seo, a finance student from Seoul. “Now I realize it also needs wisdom—and that’s the hard part.”
In a post-talk panel, faculty and entrepreneurs echoed the caution. “These kids speak machine natively—but instinct,” said Dr. Raymond Tan, “doesn’t replace perspective.”
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The Future Isn’t Autonomous—It’s Collaborative
Plazo shared that his firm is building “symbiotic systems”—AI that pairs statistical logic with situational nuance.
“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 crowd rose. 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.