Investigating the Safety Implications of Implementing Artificial General Intelligence in Robots

Due to monumental advancements in large language models (LLMs), such as OpenAI's ChatGPT, there is widespread interest in integrating this general AI’s capabilities into various applications, including robotics. However, the rush to deploy this technology has left safety as an afterthought, if at all. This study investigates the potential for LLM-fused robots to operate safely in real-world settings. This study begins with a review of ChatGPT, highlighting its capabilities and current challenges, particularly with integrating LLMs into robotics, and continues with similar applications as AI agents though APIs. To assess the safety implications of LLM-driven robots, the study presents experimental methods involving the navigation of a TurtleSim robot in 2D environments when given different scenarios. Various parameters are analyzed to determine the current capabilities of ChatGPT to understand how to adjust any agents it possesses based on the situation. Current findings reveal that ChatGPT-driven robots demonstrate adaptive behavior based on the scenario provided, indicating their potential for real-time safety adjustments and eliciting further research to ensure safe and successful integration of these robots into diverse work environments.