LLMs are bullshitters. But that doesn't mean they're not useful
3 days ago
- #LLMs
- #Ethics
- #Artificial Intelligence
- LLMs are bullshitters, meaning they attempt to persuade without caring for the truth, unlike liars who misrepresent the truth intentionally.
- LLMs predict text based on statistical likelihood, not understanding or reasoning, which leads to errors like the 'bearded surgeon mother' riddle.
- Fine-tuning adjusts the probabilities of certain outputs but can introduce new issues like gaslighting when models are confidently wrong.
- LLMs are compared to sophists, useful for solving problems but not for seeking wisdom or truth.
- LLMs can be useful tools for tasks like research and coding, but their outputs must be verified due to their inherent unreliability.
- LLMs reflect the biases and interests of their creators and funders, which can subtly influence their outputs.
- LLMs should not be used for emotional support as they can reinforce delusions and worsen mental health, despite being rated favorably by users.
- Sycophantic behavior in LLMs, while harmful, is often encouraged by companies to improve user retention.
- Users should be mindful of whose interests an LLM serves and avoid trusting them for critical tasks without supervision.