Then why don't you understand how LLMs work? Multiple peer-reviewed studies and independent analyses have demonstrated and quantified political bias in ChatGPT, with most finding a consistent left-leaning or left-libertarian orientation in its responses. Here is a summary of key studies and their findings: Key Points on Political Bias: Wikipedia: Research shows systematic left-leaning bias, especially in articles about conservative figures, which can influence LLM outputs34. News Media & Academia: Both tend to reflect the prevailing political leanings of their contributors, which are often left-of-center in the U.S. and other Western countries32. Common Crawl & Social Media: These sources are vast and diverse but include large volumes of unfiltered, opinionated, and sometimes extreme political content, amplifying whatever biases are prevalent online12. Books, Code, Multilingual Data: These sources are less directly political, but selection effects (which books, which languages, etc.) can still introduce bias5. Summary: While Wikipedia is a significant and influential source, the largest single source is Common Crawl, which, along with news, forums, and social media, introduces the greatest potential for political bias in LLMs due to the volume and diversity of perspectives—many of which are unfiltered or reflect the prevailing biases of their platforms312.
Tux will literally say anything to convince you he's right. He's basically a chatbot that's gone completely rogue. He doesn't have a college degree, he didn't even go to elementary school... he's just regurgitating crap from the internet that might fit in some alternate, usually deranged, universe.
Ahahhhaha Tux, you'll say anything! Tell us a story about when you grew up on the little planet circling Proxima Centauri.
You know where I'm glad I didn't grow up? San Bernardino. Jeez this place got sketchy since the base closed in the '90s. Just showing some family the first McDonald's location. Feel like I need a tetanus shot.
You are clearly not a computer scientist and are completely ignorant of machine learning. A computer scientist would never make the argument that LLMs are not biased. The question a computer scientist would ask is how the hell would it be even remotely possible for LLMs to not be biased. It is virtually impossible.
All LLMs are continuously adapting their output to the individual using the LLM. This is directly from Gemini's system prompt. Just these instructions, make the output biased. Code: - Tailor responses to the user's individual communication style, level of understanding, and specific circumstances. - Employ active listening techniques to identify user preferences, needs, and expectations. - Utilize personalized language models and learning algorithms to adapt responses to the user's unique behavior and interaction history.