Wharton professor Ethan Mollick has stirred conversations about artificial intelligence (AI) in financial circles, suggesting that if artificial general intelligence (AGI) were to surpass human intelligence, the first to notice would likely be financial traders. Mollick shared his thoughts on social media platform X, igniting speculation among the cryptocurrency community.
Mollick, who authored Co-Intelligence: Living and Working with AI, argued that traders would recognize AGI’s emergence as their strategies and models suddenly become ineffective.
In his post, he theorized that an unknown firm, powered by AGI, could dominate the markets, consistently landing on the winning side of trades. This disruption in financial markets, he believes, would be one of the earliest indicators of AI achieving superintelligence.
AGI refers to a hypothetical AI system capable of performing any task a human can but with greater speed, accuracy, and efficiency.
While AGI remains speculative, Mollick suggests that its potential in financial markets would be too tempting for companies to ignore. An advanced AI system capable of optimal trading strategies could dramatically reshape the landscape, especially in areas like cryptocurrency and digital assets.
Mollick’s comments quickly caught the attention of the cryptocurrency community. Many speculated that AGI could first make its mark in decentralized finance (DeFi) and cryptocurrency markets, where speed and automation are already integral to trading.
The decentralized nature of these markets, along with their susceptibility to algorithmic trading, makes them a fertile ground for AGI to flex its capabilities.
If AGI emerges, cryptocurrency traders might face unpredictable shifts in trading patterns, as an AI-powered entity could manipulate altcoins or other digital assets. The broader financial markets, including stocks and banking systems, would also be vulnerable to such disruption.
Though there is no exact scientific consensus on when or how AGI might develop, some companies are making bold predictions that human-level AI could be achieved within the next few years.
As AI systems become more advanced, the question of whether AGI will emerge through deliberate human effort or as a result of AI’s self-evolution remains open.
While Mollick’s scenario suggests traders could be the first to detect AGI, other experts argue that the earliest signs of superintelligence might surface elsewhere.
For instance, if AI systems can outperform human engineers and developers, companies might stop hiring humans for certain technical roles. The replacement of human workers by AI could be another clear indication that AGI has arrived.
