The Limits of Artificial Intelligence

In a packed amphitheater at the University of the Philippines, renowned AI investor Joseph Plazo laid down the gauntlet on what AI can and cannot achieve for the future of finance—and why understanding this may define who wins in tomorrow’s markets.

You could feel the electricity in the crowd. A sea of bright minds—some eagerly recording on their phones, 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, balancing data science with real-world decision making. His central claim: AI is brilliant, but blind.

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Bright Minds Confront the Machine’s Limits

Before him sat students and faculty from prestigious universities across Asia, assembled under a pan-Asian finance forum.

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 read more 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, “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 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, 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 that understands not just volatility, but motive.

“Ethics can’t be outsourced to software,” he reminded. “Judgment remains human territory.”

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The Speech That Started a Thousand Debates

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.

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