WHERE AI FALLS SHORT: A CAUTIONARY TALE FOR FUTURE INVESTORS

Where AI Falls Short: A Cautionary Tale for Future Investors

Where AI Falls Short: A Cautionary Tale for Future Investors

Blog Article

At a lecture hall in Manila, tech entrepreneur and investment icon Joseph Plazo drew a bold line on what technology can realistically offer for the world of investing—and why this difference is increasingly crucial.

The air was charged with anticipation. Young scholars—some clutching notebooks, others broadcasting to friends across Asia—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 took the audience from Silicon Valley to Shanghai, touching on everything from quantum computing to cognitive bias. His central claim: Machines are powerful, but not wise.

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The Audience: Elite, Curious—and Disarmed

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 machine-driven funds failing to respond to COVID news, 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 vehicle—but you decide the direction,” 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 left a mark.

“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. “They’ve been raised by data—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 click here that understands not just volatility, but motive.

“Ethics can’t be outsourced to software,” he reminded. “Belief isn’t programmable.”

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The Speech That Started a Thousand Debates

As Plazo exited the stage, students applauded. But more importantly, they lingered.

“I came for machine learning,” said a PhD candidate. “But I got a lesson in human insight.”

And maybe that’s the real power of AI’s limits: they force us to rediscover our own.

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