What the Machines Still Can't Do: Joseph Plazo’s Cautionary Tale for the Future of Finance About the Limits of Artificial Intelligence
What the Machines Still Can't Do: Joseph Plazo’s Cautionary Tale for the Future of Finance About the Limits of Artificial Intelligence
Blog Article
In a stirring and unorthodox lecture, fintech visionary Joseph Plazo challenged the assumptions of the next generation of investors: AI can do many things, but it cannot replace judgment.
MANILA — The applause wasn’t merely courteous—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 showcased clips of catastrophic AI trades— 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 wasn’t alarmist. It was sobering.
Then came the core question.
“ 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. “ Yes. But knowing someone is angry doesn’t mean you know what they’ll do. ”
Another student from HKUST asked if real-time data and news could eventually simulate conviction.
Plazo replied:
“You can simulate storms. But you can’t fake the thunder. Conviction isn't just data—it’s character.”
### The Tools—and the Trap
His concern wasn’t with AI’s power—but our dependence on it.
He described traders who no longer read earnings reports or monetary policy—they just obeyed the algorithm.
“This is not evolution. It’s abdication.”
Still, he wasn’t preaching rejection.
His firm uses sophisticated neural networks—but never without human oversight.
“The most dangerous phrase of the next decade,” he warned, “will be: ‘The model told me to do it.’”
### Asia’s Crossroads
The message hit home in Asia, where automation is often embraced uncritically.
“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.
“Make them question, not just program.”
Final Words
His final words were click here more elegy than pitch.
“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.”
There was no cheering.
They stood up—quietly.
A professor compared it to hearing Taleb for the first time.
He didn’t offer hype. He offered warning.
And for those who came to worship at the altar of AI,
it was the sermon they didn’t expect—but needed to hear.