This research paper explores the increasingly blurred lines between humans and AI, particularly in how Large Language Models (LLMs) might exhibit human-like psychology. The authors created PsychoBench, a tool that uses well-established psychological tests to assess LLMs in four areas: personality traits, how they relate to others, their motivations, and their emotional abilities. They tested popular models like ChatGPT and GPT-4, even using a "jailbreak" method to bypass AI safety protocols and reveal underlying tendencies.

Key findings:

• LLMs showed distinct personality profiles, but often leaned towards helpful and agreeable personalities, likely due to their design as assistants.

• They displayed more fairness towards different ethnic groups compared to the average human, probably due to their training to avoid bias.

• LLMs seemed more motivated, optimistic, and self-confident than the average person, particularly the advanced GPT-4 model.

• They exhibited higher anxiety about relationships than humans, possibly because they are trained on massive text data that might overrepresent anxieties in human communication.

• When assigned different roles (like "hero" or "liar"), LLMs' behavior and test results aligned with those roles, demonstrating a degree of role-playing ability.