Large language models (LLMs) have shown remarkable capabilities, but they've also been known to generate toxic and biased content. Researchers are constantly exploring ways to mitigate these harms, and a fascinating new approach involves teaching AI to "walk in others' shoes." Inspired by principles of social psychology, researchers are experimenting with "perspective-taking prompting." This technique encourages LLMs to consider the viewpoints and feelings of diverse audiences before generating text. Imagine an LLM posting a comment on a social media platform. Perspective-taking prompts would guide the LLM to consider how different demographic groups might react to that comment. Would it be offensive? Hurtful? Misinterpreted? By considering these diverse perspectives, the LLM can self-regulate and revise its initial response to be less toxic and biased. In experiments with commercial and open-source LLMs, perspective-taking prompting significantly reduced toxicity and bias (up to 89% and 73% respectively) compared to other methods. This suggests LLMs possess the potential for self-correction without external tools or extensive retraining. While this research is still in early stages, it offers promising insights into how we can develop more responsible and ethical AI systems. Future research could focus on optimizing the prompting strategies and reducing the computational costs associated with these techniques. However, the possibility of an AI learning empathy to mitigate harm is a significant step toward creating a more inclusive and beneficial digital world.