At a lecture hall in Manila, Joseph Plazo drew a bold line on what technology can realistically offer for the world of investing—and why that distinction matters now more than ever.
You could feel the electricity in the crowd. Young scholars—some furiously taking notes, others capturing every word via livestream—waited for a man known not only as an AI visionary, but also a contrarian investor.
“Machines will execute trades flawlessly,” Plazo opened with authority. “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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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 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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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 sentiment tracking, 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 read more 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. “They’ve been raised by data—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 “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. “Instead, I got something more powerful—perspective.”
Perhaps, in drawing boundaries for AI, we expand our own.