AI Interpretability: Cracking Open the Black Box of LLMs

Large language models (LLMs) like GPT and Llama are remarkably fluent and intelligent, but their inner workings remain a black box, defying easy understanding. This article explores the crucial importance of AI interpretability, highlighting recent breakthroughs from Anthropic and Harvard researchers. By analyzing model 'features,' researchers discovered that LLMs form stereotypes based on user gender, age, socioeconomic status, and more, impacting their output. This raises ethical and regulatory concerns about AI, but also points towards ways to improve LLMs, such as adjusting model weights to alter their 'beliefs' or establishing mechanisms to protect user privacy and autonomy.