Amid the warm Manila breeze, in a university hall buzzing with intellect, tech entrepreneur and investment icon Joseph Plazo made a striking distinction on what machines can and cannot do for the future of finance—and why understanding this may define who wins in tomorrow’s markets.
Tension and curiosity pulsed through the room. Students—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.
“Algorithms can execute,” Plazo opened with authority. “It won’t tell you when not to trust them.”
Over the next sixty minutes, Plazo delivered a fast-paced masterclass, intertwining machine logic with human flaws. His central claim: Machines are powerful, but not wise.
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Top Students Meet a Tough Truth
Before him sat students and faculty from prestigious universities across Asia, assembled under a pan-Asian finance forum.
Many expected a victory lap 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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The Machine’s Blindness: Plazo’s Case for Caution
Plazo’s core thesis was both simple and unsettling: AI does not grasp nuance.
“AI won’t flinch, but neither will it foresee,” he warned. “It recognizes patterns—but ignores the power structures.”
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 sentiment tracking, to which Plazo acknowledged: “Sure, it can flag Reddit anomalies—but it can’t discern hesitation in a policymaker’s tone.”
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A Mental Shift Among Asia’s Finest
The talk hit hard.
“I click here used to think AI just needed more data,” said Lee Min-Seo, a finance student from Seoul. “Now I see it’s judgment, not just data, that matters.”
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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An Ending That Sparked a Beginning
As Plazo exited the stage, the hall erupted. But more importantly, they stayed behind.
“I came for machine learning,” said a PhD candidate. “Instead, I got something more powerful—perspective.”
In knowing what AI can’t do, we sharpen what we can.