Artificial intelligence (AI) is all around us these days. Whether you’re writing a document or reading a PDF, you might come across an AI assistant offering to help you. However, if you’ve ever used ChatGPT or similar programs, you may have encountered a common issue – they sometimes make things up, leading people to question the accuracy of their responses.
Instead of referring to these inaccuracies as “hallucinations,” some experts suggest calling them what they really are – bullshit. When someone engages in bullshit, they are not concerned with the truthfulness of their statements, but they are not necessarily lying either. In the case of ChatGPT and other AI language models, they simply generate text without any real understanding or concern for accuracy.
These AI models, such as ChatGPT, Gemini, and Llama, operate based on large language models (LLMs) trained on massive amounts of text data from the internet. They predict the next word or phrase in a sentence based on the input they receive. While these models can produce human-like text, they lack the ability to verify the truthfulness of their output.
As a result, inaccuracies and falsehoods can occur, as seen in cases where ChatGPT provided fake legal citations in a lawyer’s research. These errors highlight the limitations of AI language models and the importance of not attributing human-like qualities, such as understanding or intention, to these machines.
By reframing the conversation around AI-generated content as “bullshit” rather than “hallucinations,” we can more accurately convey the nature of these inaccuracies. This shift in terminology can help prevent misunderstandings about the capabilities and limitations of AI technology and clarify accountability when errors occur.
So, the next time you encounter false information from an AI model like ChatGPT, remember to call it what it is – bullshit. This simple change in language can lead to a better understanding of AI technology and its implications for society.
