“Joseph Plazo on Why Algorithms Still Need Human Judgment”“Joseph Plazo on Why Algorithms Still Need Human Judgment”
“Joseph Plazo on Why Algorithms Still Need Human Judgment”“Joseph Plazo on Why Algorithms Still Need Human Judgment”
Blog Article
During a speech delivered at one of Southeast Asia’s top business schools, Joseph Plazo, voiced concerns that many in his field tend to ignore.
His argument was not anti-technology, but pro-governance.
“Delegating execution does not mean abdicating responsibility.”
???? **The Model Is Perfect. The Context Is Missing.**
Mr. Plazo is not a critic from the fringe. His firm’s systems have achieved a 99% success rate across various assets and timeframes.
But that success, he suggests, carries risk.
“A well-trained model can still make perfectly logical errors.”
He cited a case during the COVID-19 pandemic when a bot under his supervision flagged a short on gold—just before the US Federal Reserve announced an intervention.
“We cancelled the trade. It failed to anticipate a shift that any seasoned investor would have questioned.”
???? **Why Delay Still Matters**
Plazo referred to what he terms **“strategic friction”**—the time it takes to think before a trade.
“Speed without governance is simply exposure.”
He presented a framework his firm uses, called **Conviction Calculus**. It includes three questions:
- Are we trading in line with our long-term thesis—or merely responding to signals?
- Has the recommendation been challenged by human insight—policy awareness, historical precedent, market tone?
- If this fails, will someone check here take responsibility—or will the blame lie with the code?
???? **Governance in the Age of Machine Capital**
Plazo’s comments come at a time of accelerating fintech growth across Asia. From Singapore to Seoul, AI-led investing is seen as both policy strategy and capital advantage.
But as Mr. Plazo points out:
“You can scale capital faster than accountability.”
In 2024, two hedge funds in Hong Kong lost billions after AI models failed to factor in geopolitical risk—a result of logic executed too quickly, and too narrowly.
“It was not error, but automation without skepticism.”
???? **AI That Understands More Than Market Signals**
Plazo remains bullish on AI’s potential—but not its current limitations.
His firm is building what he describes as **“narrative-integrated AI”**—systems that account for macro context, cultural tone, and regulatory environment, not just price and volume.
“Data is abundant. Insight is scarce.”
Investors from Tokyo and Jakarta reportedly expressed interest in these models after the speech. One regional fund manager noted:
“This is the first practical answer to AI’s ethical vacuum we’ve seen in Asia.”
???? **What Happens When the Machine Is Always Right—But Still Wrong?**
Plazo ended with a line that encapsulated his thesis:
“The next financial crisis will not be triggered by emotion—but by perfect logic, executed too quickly, and left unquestioned.”
For investors and policymakers alike, the message was clear: AI is here to stay. But leadership cannot be automated.