The notion that AI is the ultimate tech bubble, one to burst them all. According to experts Brent Goldfarb and David A. Kirsch, authors of "Bubbles and Crashes: The Boom and Bust of Technological Innovation", a reliable means of evaluating and understanding the AI mania involves applying their framework for determining whether a particular innovation leads to a bubble.
The framework considers four principal factors: (1) uncertainty, (2) pure plays, (3) novice investors, and (4) narratives around commercial innovations. Goldfarb and Kirsch identify and evaluate these factors and rank historical examples on a scale of 0 to 8โ8 being the most likely to predict a bubble.
The application of this framework to generative AI reveals that it meets all four criteria: uncertainty is high due to the challenges in integrating AI into organizations; pure plays, such as Nvidia and OpenAI, dominate the market with their focus on building chips and AGI; novice investors, including retail traders on platforms like E-Trade and Robinhood, are pouring money into AI companies; and a compelling narrative, one of superintelligence and limitless possibilities, is driving investment.
Goldfarb notes that everyone is "something of a novice investor" when it comes to AI due to the new field and technology. He also highlights the power of coordinating narratives in inflating bubbles, as seen in aviation and broadcast radio history. The AI narrative, with its promises of curing cancer, automating jobs, and ushering in an age of superpowerful technology, is uniquely powerful in its bubble-inflating capacities.
The authors conclude that, yes, Goldfarb says, AI has all the hallmarks of a bubble. It hits all the right notes: uncertainty, pure plays, novice investors, and a great narrative. On their 0-to-8 scale, it's an 8โbuyer beware.
Ultimately, as with any speculative market, there is always a risk that the promised benefits of AI may not materialize, leaving investors with significant losses.
The framework considers four principal factors: (1) uncertainty, (2) pure plays, (3) novice investors, and (4) narratives around commercial innovations. Goldfarb and Kirsch identify and evaluate these factors and rank historical examples on a scale of 0 to 8โ8 being the most likely to predict a bubble.
The application of this framework to generative AI reveals that it meets all four criteria: uncertainty is high due to the challenges in integrating AI into organizations; pure plays, such as Nvidia and OpenAI, dominate the market with their focus on building chips and AGI; novice investors, including retail traders on platforms like E-Trade and Robinhood, are pouring money into AI companies; and a compelling narrative, one of superintelligence and limitless possibilities, is driving investment.
Goldfarb notes that everyone is "something of a novice investor" when it comes to AI due to the new field and technology. He also highlights the power of coordinating narratives in inflating bubbles, as seen in aviation and broadcast radio history. The AI narrative, with its promises of curing cancer, automating jobs, and ushering in an age of superpowerful technology, is uniquely powerful in its bubble-inflating capacities.
The authors conclude that, yes, Goldfarb says, AI has all the hallmarks of a bubble. It hits all the right notes: uncertainty, pure plays, novice investors, and a great narrative. On their 0-to-8 scale, it's an 8โbuyer beware.
Ultimately, as with any speculative market, there is always a risk that the promised benefits of AI may not materialize, leaving investors with significant losses.