What AI Can’t Do: A Manila Lecture Shakes the Finance World
What AI Can’t Do: A Manila Lecture Shakes the Finance World
Blog Article
Amid the warm Manila breeze, in a university hall buzzing with intellect, Joseph Plazo drew a bold line on what machines can and cannot do for the economic frontier—and why this difference is increasingly crucial.
The air was charged with anticipation. A sea of bright minds—some clutching notebooks, others broadcasting to friends across Asia—waited for a man both celebrated and controversial in AI circles.
“Algorithms can execute,” Plazo opened with authority. “It won’t tell you when not to trust them.”
Over the next hour, 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 leading institutions like Kyoto, NUS, and HKUST, 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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Why AI Still Doesn’t Get It
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 cited examples like the market chaos of early 2020, noting, “Machines were late to the signal. People weren’t.”
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Reclaiming the Edge: Why Humans Still Matter
Rather than dismiss AI, Plazo proposed a partnership.
“AI is the microscope—you choose what to zoom in on,” he said. It analyzes—but lacks awareness.
Students pressed him on AI in news and social chatter, 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 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 read more 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.
“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.