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AI boom could expose investors’ natural stupidity

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Summary

This article written by Felix Martin discusses the current AI boom and how investors should be aware of the pitfalls of natural stupidity when investing in AI-related stocks. It mentions how the enthusiasm for AI has seen stocks like Nvidia, Microsoft, and Alphabet surge in value over the past few months. The article then goes on to discuss how AI has achieved impressive results such as AlphaFold and ChatGPT, but that the big unknown is whether AI can replicate this success in the real world. It finishes by discussing potential problems that AI may face such as sampling bias and Goodhart's Law.

Q&As

What is the main message of the article?
The main message of the article is that investors should be aware of the potential for natural stupidity to drive stock market valuations to unrealistic extremes, and should be cautious when attempting to apply AI in the wild.

What insights does behavioural economics offer investors hoping to cash in on AI?
Insights from behavioural economics offer investors hoping to cash in on AI warnings about herding, overconfidence, confirmation bias, and the fear of missing out.

What have been the macroeconomic consequences of the AI boom?
The macroeconomic consequences of the AI boom include a new 90-billion-euro sovereign wealth fund in Ireland, largely funded by a corporate tax windfall from tech giants, and the S&P 500 Index being up 8% year-to-date, excluding AI-related gains.

How can AI replicate its extraordinary predictive abilities in areas of commercial, financial, and political life?
AI can replicate its extraordinary predictive abilities in areas of commercial, financial, and political life by recognizing patterns which elude both human intuition and traditional statistical analysis, and then leveraging these patterns for predictive purposes.

What challenges have been identified when attempting to apply AI in the wild?
Challenges identified when attempting to apply AI in the wild include the problem of sampling bias when building predictive models based on statistical learning, and Goodhart's Law, which states that when a metric becomes a policy target it ceases to be a reliable metric.

AI Comments

👍 This article provides great insight into the potential risks of investing in AI and provides great advice on how to better manage decision-making in order to protect against large losses.

👎 This article is too long-winded and fails to provide concrete advice on how to invest in AI while mitigating the risks associated with it.

AI Discussion

Me: It's about how the AI boom could expose investors' natural stupidity. It talks about how AI is being incorporated into major companies like Microsoft, Google, and Apple, and how the enthusiasm around AI has caused a lot of stock market volatility. But the article also talks about the potential pitfalls of investing in AI, such as the risk of bubbles, herding behavior, and Goodhart's Law.

Friend: That's interesting. It sounds like investing in AI could be a risky endeavor.

Me: Yeah, that's definitely true. The article makes a good point about how investors should be aware of the potential for bubbles and irrational behavior when investing in AI. It also talks about the need to be aware of the potential for sampling bias and Goodhart's Law when using AI to make predictions. The article is a good reminder that although AI can be incredibly powerful, it's important to be aware of the potential risks.

Action items

Research the potential risks associated with investing in AI-related stocks and other assets.
Consider the potential for sampling bias when building predictive models based on statistical learning.
Utilize simple heuristics such as Benjamin Graham’s “margin of safety” to mitigate the risk of investing in AI-related stocks and other assets.

Technical terms

AI (Artificial Intelligence): AI is a type of computer technology that is designed to simulate human intelligence and behavior. It is used to create computer programs that can think and act like humans.
ChatGPT: ChatGPT is a chatbot developed by OpenAI, a research laboratory focused on artificial intelligence. It is designed to generate human-like conversations in response to user input.
Nvidia (NVDA.O): Nvidia is a technology company that specializes in the design and manufacture of computer graphics cards and other computer components.
Microsoft (MSFT.O): Microsoft is a technology company that develops and sells computer software, hardware, and services.
Alphabet (GOOGL.O): Alphabet is a holding company that owns Google and other subsidiaries.
Apple (AAPL.O): Apple is a technology company that designs, manufactures, and markets consumer electronics, computer software, and online services.
Chegg (CHGG.N): Chegg is an online learning platform that provides digital textbooks, online tutoring, and other educational services.
S&P 500 Index (.SPX): The S&P 500 Index is a stock market index that tracks the performance of 500 large companies listed on the New York Stock Exchange and the NASDAQ.
OpenAI: OpenAI is a research laboratory focused on artificial intelligence. It is dedicated to developing artificial general intelligence (AGI) in a way that is safe and beneficial to humanity.
AlphaFold: AlphaFold is a computer program developed by Google DeepMind that can predict the structures into which proteins fold based only on the sequences of their constituent amino acids.
Royal Society: The Royal Society is a British scientific institution that promotes the natural and applied sciences.
Large Language Models: Large language models are computer programs that use artificial intelligence to generate human-like conversations in response to user input.
Behavioural Economics: Behavioural economics is a field of economics that studies how psychological, emotional, and social factors affect human decision-making.
Herding: Herding is a phenomenon in which people tend to follow the actions of others, even if those actions are not in their own best interests.
Overconfidence: Overconfidence is the tendency to overestimate one's own abilities or knowledge.
Confirmation Bias: Confirmation bias is the tendency to search for, interpret, or prioritize information in a way that confirms one's preexisting beliefs.