The Limits of Artificial Intelligence
The Limits of Artificial Intelligence
Blog Article
Amid the warm Manila breeze, in a university hall buzzing with intellect, Joseph Plazo laid down the gauntlet on what AI can and cannot achieve for the future of finance—and why that distinction matters now more than ever.
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.
“AI will make trades for you,” he said with gravity. “But it won’t teach you why to believe in them.”
Over the next lecture, Plazo delivered a fast-paced masterclass, intertwining machine logic with human flaws. His central claim: AI is brilliant, but blind.
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Top Students Meet a Tough Truth
Before him sat students and faculty from prestigious universities across Asia, assembled under a pan-Asian finance forum.
Many expected a victory lap of AI's dominance. Instead, they got a reality check.
“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 read more 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, “AI lagged—while humans had already hedged.”
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Wisdom in a World of Code
Plazo didn’t argue against AI—but for boundaries.
“AI is the telescope—but you are still the astronomer,” he said. It analyzes—but lacks awareness.
Students pressed him on sentiment tracking, to which Plazo acknowledged: “Sure, it can flag Reddit anomalies—but it can’t discern hesitation in a policymaker’s tone.”
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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, 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 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. “Instead, I got something more powerful—perspective.”
Perhaps, in drawing boundaries for AI, we expand our own.