“MACHINES CAN TRADE. BUT CAN THEY GOVERN?”“MACHINES CAN TRADE. BUT CAN THEY GOVERN?”

“Machines Can Trade. But Can They Govern?”“Machines Can Trade. But Can They Govern?”

“Machines Can Trade. But Can They Govern?”“Machines Can Trade. But Can They Govern?”

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At a recent event hosted by the Asian Institute of Management in Manila, the algorithmic investor and strategist Joseph Plazo argued that automation may have outpaced accountability.

His message was simple: speed must not replace strategy.

“AI can make correct decisions. But are they the right ones?”

???? **A Technologist’s Dilemma**

Mr. Plazo is not a critic from the fringe. His algorithms are widely used by institutional investors from Europe to East Asia.

But that success, he suggests, carries risk.

“Optimisation without orientation is simply acceleration in an unknown direction.”

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 interpreted data, not decisions.”

???? **Machines Act Quickly. Humans Are Meant to Think.**

Plazo referred to what he terms **“strategic friction”**—the time it takes to think before a trade.

“Frictions allow institutional investors to consider second-order effects.”

He presented a framework his firm uses, called **Conviction Calculus**. It includes three questions:

- Does this trade align with the organisation’s ethical posture?
- Would an experienced fund manager endorse this move?
- Is the leadership team prepared to justify the trade beyond performance metrics?

???? **The Ethical Gap in Asia’s Fintech Race**

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:

“Technology is advancing—but decision-making frameworks are not.”

In 2024, two hedge funds in Hong Kong lost here billions after AI models failed to factor in geopolitical risk—a result of logic executed too quickly, and too narrowly.

“The models did what they were told. But no one asked whether they should.”

???? **The Case for Narrative-Aware AI**

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.

“We need models that don’t just predict—but interpret.”

Investors from Tokyo and Jakarta reportedly expressed interest in these models after the speech. One regional fund manager noted:

“If AI is to be sustainable, it must learn to say no—not just go faster.”

???? **The Final Warning: Crises May Be Logical, Not Emotional**

Plazo ended with a line that encapsulated his thesis:

“It won’t be chaos that brings us down—but confidence in models we don’t challenge.”

His tone was not alarmist, but realistic: growth must be governed.

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