Decoding Large-Language Models: A Systematic Overview of Socio-Technical Impacts, Constraints, and Emerging Questions

TL;DR

This paper systematically reviews large language models, highlighting their advancements, societal impacts, ethical challenges, and future research directions in natural language processing and AI.

Contribution

It provides a comprehensive overview of LLM developments, impacts, limitations, and ethical considerations, identifying key themes and future research directions.

Findings

Highlights societal and ethical implications of LLMs

Identifies key limitations and challenges in current LLM research

Suggests future directions for responsible and effective LLM development

Abstract

There have been rapid advancements in the capabilities of large language models (LLMs) in recent years, greatly revolutionizing the field of natural language processing (NLP) and artificial intelligence (AI) to understand and interact with human language. Therefore, in this work, we conduct a systematic investigation of the literature to identify the prominent themes and directions of LLM developments, impacts, and limitations. Our findings illustrate the aims, methodologies, limitations, and future directions of LLM research. It includes responsible development considerations, algorithmic improvements, ethical challenges, and societal implications of LLM development. Overall, this paper provides a rigorous and comprehensive overview of current research in LLM and identifies potential directions for future development. The article highlights the application areas that could have a positive impact on society along with the ethical considerations.