What the Machines Still Can't Do: Joseph Plazo’s Hard Truths for the Next Generation of Investors on the Boundaries of Artificial Intelligence
What the Machines Still Can't Do: Joseph Plazo’s Hard Truths for the Next Generation of Investors on the Boundaries of Artificial Intelligence
Blog Article
In a rare keynote that blended technical acumen with philosophical depth, financial technologist Joseph Plazo challenged the assumptions of the academic elite: there are frontiers even AI cannot cross.
MANILA — The ovation at the end wasn’t routine—it echoed with the sound of reevaluation. At the packed University of the Philippines auditorium, future leaders from NUS, Kyoto, HKUST and AIM expected a triumphant ode to AI’s dominance in finance.
But they left with something deeper: a challenge.
Joseph Plazo, the architect behind high-accuracy trading machines, chose not to pitch another product. Instead, he opened with a paradox:
“AI can beat the market. But only if you teach it when not to try.”
The crowd stiffened.
What followed wasn’t evangelism. It was inquiry.
### Machines Without Meaning
Plazo systematically debunked the myth that AI can autonomously outwit human investors.
He presented visual case studies of trading bots gone wrong—algorithms buying into crashes, bots shorting bull runs, systems misreading sarcasm as market optimism.
“ Most of what we call AI is trained on yesterday. But tomorrow is where money is made.”
His tone wasn’t cynical—it was reflective.
Then he paused, looked around, and asked:
“Can your AI model 2008 panic? Not the price check here charts—the dread. The stunned silence. The smell of collapse?”
And no one needed to.
### When Students Pushed Back
Naturally, the audience engaged.
A doctoral student from Kyoto proposed that large language models are already analyzing tone to improve predictions.
Plazo nodded. “Yes. But sensing anger is not the same as understanding it. ”
Another student from HKUST asked if real-time data and news could eventually simulate conviction.
Plazo replied:
“Lightning can be charted. But not predicted. Conviction is a choice, not a calculation.”
### The Tools—and the Trap
He shifted the conversation: from tech to temptation.
He described traders who waited for AI signals as gospel.
“This is not evolution. It’s abdication.”
But he clarified: he’s not anti-AI.
His systems parse liquidity, news, and institutional behavior—but humans remain in charge.
“The most dangerous phrase of the next decade,” he warned, “will be: ‘The model told me to do it.’”
### Asia’s Crossroads
In Asia—where AI is lionized—Plazo’s tone was a jolt.
“There’s a spiritual reverence for AI here,” said Dr. Anton Leung, an ethics professor from Singapore. “Plazo reminded us that even intelligence needs wisdom.”
In a follow-up faculty roundtable, Plazo urged for AI literacy—not just in code, but in consequence.
“We don’t just need AI coders—we need AI philosophers.”
Final Words
The ending wasn’t applause bait. It was a challenge.
“The market,” Plazo said, “isn’t just numbers. It’s a story. And if your AI doesn’t read character, it’ll trade noise for narrative.”
No one clapped right away.
The applause, when it came, was subdued.
Another said it reminded them of Steve Jobs at Stanford.
He didn’t market a machine.
And for those who came to worship at the altar of AI,
it was the lecture that questioned their faith.