The Limits of Artificial Intelligence
The Limits of Artificial Intelligence
Blog Article
At a lecture hall in Manila, Joseph Plazo laid down the gauntlet on what technology can realistically offer for the world of investing—and why that distinction matters now more than ever.
The air was charged with anticipation. A sea of bright minds—some eagerly recording on their phones, others broadcasting to friends across Asia—waited for a man revered for blending code with contrarianism.
“AI will make trades for you,” 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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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. Plazo had other plans.
“There’s a rising cult of algorithmic faith,” said Prof. Maria Castillo, a respected AI ethicist from the UK. “We need this kind of discomfort in academia.”
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The Machine’s Blindness: Plazo’s Case for Caution
Plazo’s core thesis was both simple and unsettling: AI does not grasp nuance.
“AI won’t flinch, but neither will it foresee,” he warned. “It recognizes patterns—but ignores the power structures.”
He cited examples like the market chaos of early 2020, 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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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 more info 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.