Ik herlees Nicholas Nassim Taleb’s Fooled By Randomness. Heel veel voorspellingskracht wordt gevonden in historische data. Maar niet de Black Swans. Ik moet denk aan de hype rond AI die momenteel heerst.

AI en ML leven van historische data. Black Swan events komen niet voor in historische data.

De AI is dus net zo stom als mensen: onze AI ziet grote hoeveelheden witte zwanen. Als je de AI vraag welke kleur een zwaan heeft, zegt hij dus: wit. Zwarte zwanen bestaan ook voor de AI niet.

AI is waardeloos waar het gaat om Black Swan Events.

ChatGPT zegt het zelf:

AI systems, including those based on advanced algorithms like GPT-3.5, have limitations when it comes to predicting black swan events. Black swan events are extremely rare, unpredictable, and have a significant impact. These events are, by definition, unforeseen and often fall outside the range of normal expectations.

AI models, including machine learning algorithms, are generally trained on historical data. If black swan events have never occurred in the training set, the AI model would not have learned to predict them explicitly. Traditional AI models work based on patterns and correlations found in the data they were trained on. They are not capable of inventing entirely new and unprecedented events beyond the scope of their training data.

However, it’s essential to note that AI can be helpful in preparing for unexpected events, even if they cannot predict black swan events directly. Here’s how:

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Despite these capabilities, it’s important to maintain a cautious approach when relying on AI for preparing for black swan events. Human judgment, expert analysis, and continuous monitoring are essential elements in mitigating the impacts of truly unforeseen and exceptional events.