Human-Computer Interaction: A Literature Review of Artificial Intelligence and Communication in Healthcare

Abstract

The integration of artificial intelligence (AI) into healthcare communication has rapidly evolved, driven by advancements in large language models (LLMs) such as Chat Generative Pre-trained Transformer (ChatGPT). This literature review explores AI's role in patient-physician interactions, particularly focusing on its capacity to enhance communication by bridging language barriers, summarizing complex medical data, and offering empathetic responses. AI's strengths lie in its ability to deliver comprehensible, concise, and medically accurate information. Studies indicate AI can outperform human physicians in certain communicative aspects, such as empathy and clarity, with models like ChatGPT and the Medical Pathways Language Model (Med-PaLM) demonstrating high effectiveness in these areas. However, significant challenges remain, including occasional inaccuracies and "hallucinations," where AI-generated content is irrelevant or medically inaccurate. These limitations highlight the need for continued refinement in AI algorithms to ensure reliability and consistency in sensitive healthcare settings. The review underscores the potential of AI as a transformative tool in health communication while advocating for further research and policy development to mitigate risks and enhance AI's integration into clinical practice.