The Limits of Artificial Intelligence
The Limits of Artificial Intelligence
Blog Article
At a lecture hall in Manila, tech entrepreneur and investment icon Joseph Plazo made a striking distinction on what machines can and cannot do for the world of investing—and why this difference is increasingly crucial.
The air was charged with anticipation. Young scholars—some clutching notebooks, others capturing every word via livestream—waited for a man known not only as an AI visionary, but also a contrarian investor.
“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, 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, gathered under a technology consortium.
Many expected a praise-filled keynote of AI's dominance. Plazo had other plans.
“There’s a rising cult of algorithmic faith,” said Prof. Maria Castillo, an Oxford visiting fellow. “We need this kind of discomfort in academia.”
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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 telescope—but you are still the astronomer,” 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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The Ripple Effect on a Digital Generation
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 only half the story.”
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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 read more stayed behind.
“I came for machine learning,” said a PhD candidate. “Instead, I got something more powerful—perspective.”
And maybe that’s the real power of AI’s limits: they force us to rediscover our own.