Imagine a world where your political voice is amplified by a personalized AI assistant, navigating the complex landscape of policies and proposals on your behalf. This is the vision of augmented democracy, a concept explored in recent research using Large Language Models (LLMs). Researchers delved into the potential of LLMs to act as digital twins, representing individual citizens' preferences with remarkable accuracy. Using data from a real-world participatory experiment during the 2022 Brazilian presidential election, they trained LLMs to predict how individuals would vote on specific policy proposals. Surprisingly, these AI assistants outperformed simple predictions based on party lines, suggesting they capture the nuances of individual political views. The study also examined how LLMs could improve the accuracy of opinion polls. By augmenting smaller samples with LLM predictions, they found a significant boost in the ability to represent the overall preferences of a larger population. This has exciting implications for understanding public opinion and potentially shaping future democratic processes. However, the research also highlighted important challenges. The LLMs showed biases, predicting preferences more accurately for younger, liberal, and more educated participants. This raises concerns about fair representation and the potential for these technologies to exacerbate existing inequalities. Furthermore, the lack of transparency in how LLMs make decisions poses a significant hurdle for building trust and ensuring accountability in democratic systems. While the vision of AI-powered democracy is still in its early stages, this research offers a glimpse into both its potential and its pitfalls. Addressing the challenges of bias, transparency, and manipulation will be crucial for harnessing the power of LLMs to create a more inclusive and representative democratic future.