The Limits of Artificial Intelligence
The Limits of Artificial Intelligence
Blog Article
At a lecture hall in Manila, renowned AI investor 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. A sea of bright minds—some eagerly recording on their phones, others streaming the moment live—waited for a man both celebrated and controversial in AI circles.
“AI will make trades for you,” Plazo began, calm but direct. “But it won’t teach you why to believe in them.”
Over the next sixty minutes, Plazo delivered a fast-paced masterclass, intertwining machine logic with human flaws. His central claim: AI is brilliant, but blind.
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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 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, “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 here 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. “Turns out, insight can’t be uploaded.”
In a post-talk panel, tech mentors agreed with his sentiment. “This generation is born with algorithmic reflexes—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 candidate. “But I got a lesson in human insight.”
Perhaps, in drawing boundaries for AI, we expand our own.