Large Language Models (LLMs) represent a transformative leap in Artificial Intelligence (AI), delivering remarkable language-processing capabilities that are reshaping how we interact with technology in our daily lives. With their ability to perform tasks such as summarisation, translation, classification, and text generation, LLMs have demonstrated unparalleled versatility and power. Drawing from vast and diverse knowledge bases, these models hold the potential to revolutionise a wide range of fields, including education, media, law, psychology, and beyond. From assisting educators in creating personalised learning experiences to enabling legal professionals to draft documents or supporting mental health practitioners with preliminary assessments, the applications of LLMs are both expansive and profound.

However, alongside their impressive strengths, LLMs also face significant limitations that raise critical ethical questions. Unlike humans, these models lack essential qualities such as emotional intelligence, contextual empathy, and nuanced ethical reasoning. While they can generate coherent and contextually relevant responses, they do not possess the ability to fully understand the emotional or moral implications of their outputs. This gap becomes particularly concerning when LLMs are deployed in sensitive domains where human values, cultural nuances, and ethical considerations are paramount. For example, biases embedded in training data can lead to unfair or discriminatory outcomes, while the absence of ethical reasoning may result in outputs that inadvertently harm individuals or communities. These limitations highlight the urgent need for robust research in Natural Language Processing (NLP) to address the ethical dimensions of LLMs. Advancements in NLP research are crucial for developing methods to detect and mitigate biases, enhance transparency in model decision-making, and incorporate ethical frameworks that align with human values. By prioritising ethics in NLP research, we can better understand the societal implications of LLMs and ensure their development and deployment are guided by principles of fairness, accountability, and respect for human dignity. This workshop will dive into these pressing issues, fostering a collaborative effort to shape the future of LLMs as tools that not only excel in technical performance but also uphold the highest ethical standards.