The widespread use of generative AI raises concerns about bias, particularly when it comes to training on human-generated content. The biases inherent in the data used to train language models (LLMs) can influence their outputs, impacting interpretations and opinions. Issues such as access restrictions, delayed deployment in specific languages, and intellectual property concerns also contribute to bias. To ensure responsible AI, transparency in product and process development is essential. Lawmakers can play a role in promoting transparency, but global cooperation and harmonized rules are crucial for addressing these challenges in the AI landscape.
