A Reckoning with the Machines: Joseph Plazo’s Hard Truths for the Next Generation of Investors on the Boundaries of Artificial Intelligence
A Reckoning with the Machines: Joseph Plazo’s Hard Truths for the Next Generation of Investors on the Boundaries of Artificial Intelligence
Blog Article
In a stirring and unorthodox lecture, AI trading pioneer Joseph Plazo issued a warning to the next generation of investors: AI can do many things, but it cannot replace judgment.
MANILA — What followed wasn’t thunderous, but resonant—it reflected a deep, perhaps uneasy, resonance. Within the echoing walls of UP’s lecture forum, 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.”
Students leaned in.
What ensued was described by one professor as “a reality check.”
### Machines Without Meaning
His talk unraveled a common misconception: that data-driven machines can foresee financial futures alone.
He presented visual case studies of trading bots gone wrong— trades that defied logic, machines acting on misread signals, and neural nets confused by human nuance.
“Most models are just beautiful regressions of yesterday. But tomorrow is where money is made.”
It was less condemnation, more contemplation.
Then he delivered his punchline.
“ Can an algorithm simulate the disbelief of 2008? Not the price drop—the fear. The disbelief. The moment institutions collapsed like dominoes? ”
No one answered.
### When Students Pushed Back
The Q&A wasn’t shy.
A doctoral student from Kyoto proposed that large language models are already detecting sentiment and adjusting forecasts.
Plazo nodded. “ Sure. But emotion detection isn’t the same as consequence prediction.”
Another student from HKUST asked if real-time data and news could eventually simulate conviction.
Plazo replied:
“You can model lightning. But you don’t know when or where it’ll strike. Conviction isn’t math. It’s a stance.”
### The Tools—and the Trap
His concern wasn’t with AI’s power—but our dependence on it.
He described traders who surrendered their judgment to the machine.
“This is not evolution. It’s abdication.”
But he clarified: he’s not anti-AI.
His firm uses sophisticated neural networks—with rigorous human validation.
“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.
“Automation here is almost sacred,” noted Dr. Anton Leung, AI ethicist. “The warning is clear: intelligence without interpretation is still dangerous.”
During a closed-door discussion afterward, Plazo urged for AI literacy—not just in code, but in consequence.
“Teach them to think with AI, not just build it.”
Final Words
His closing didn’t feel like a tech talk. It felt like here a warning.
“The market,” Plazo said, “is not a spreadsheet. It’s a novel. And if your AI doesn’t read character, it will miss the plot.”
No one clapped right away.
They stood up—quietly.
A professor compared it to hearing Taleb for the first time.
Plazo didn’t sell a vision.
And for those who came to worship at the altar of AI,
it was the sermon they didn’t expect—but needed to hear.