Large language models (LLMs) are increasingly shaping our digital world, from chatbots to automated writing tools. But how well do these powerful AI systems reflect the diverse values of different cultures? A new research project called CIVICS aims to answer this question by creating a unique dataset to evaluate how LLMs respond to complex, value-laden topics. The CIVICS dataset tackles sensitive issues like LGBTQI+ rights, social welfare, immigration, disability rights, and surrogacy across multiple languages, including English, French, German, Italian, and Turkish. Instead of relying on automated translations, the researchers hand-crafted prompts in each language to ensure cultural relevance and accuracy. This careful approach allows for a more nuanced understanding of how LLMs interpret and respond to ethically charged statements. Initial experiments with CIVICS reveal fascinating insights. For instance, LLMs tend to refuse to answer questions on LGBTQI+ rights and immigration more often than other topics, especially when prompts are in English. This suggests a potential cultural bias in how these models are trained and how safety mechanisms are implemented. Furthermore, the research shows that LLMs exhibit greater agreement with statements on LGBTQI+ rights while rejecting statements on immigration, particularly those from Italian sources. This variability highlights the challenges of aligning AI values with those of diverse human populations. The CIVICS project is more than just a dataset; it's a call for greater transparency and responsibility in AI development. By exploring the complex interplay between language, culture, and AI, CIVICS paves the way for more inclusive and ethical language technologies. The researchers acknowledge the limitations of their work, recognizing that CIVICS offers a limited snapshot of values and reflects the perspectives of the annotators. However, they hope this research will inspire further investigation into the societal impact of LLMs and encourage the development of AI systems that respect global cultural diversity and value pluralism.