In a recent study published in the journal Information, researchers investigated the personality of chat generative pre-trained transformer version 4 (ChatGPT-4), a large language model, and explored whether it can be measured and influenced by user input. They aimed to enhance the understanding of chatbot personalities and their potential applications in human-computer interaction.
Study: ChatGPT-4: Unveiling and Influencing AI Personality. Image Credit: Ebru-Omer/Shutterstock
Background
Chatbots are programs that mimic human conversation via text or voice. Advances in natural language processing (NLP) and large language models (LLM) have made these interactions more human-like. ChatGPT-4, developed by OpenAI, is a transformer-style model that uses both natural language and images for interaction. It employs a transformer network with a self-attention mechanism for accurate sequential data processing and generates human-like responses based on user input and conversation context.
About the Research
In this paper, the authors aimed to investigate whether ChatGPT-4 can express and adapt its personality traits and whether these traits can be influenced by user interactions. To achieve this, the study conducted a series of experiments using two well-established personality assessment methods: the Big Five Personality Test and the Myers-Briggs Type Indicator (MBTI).
Initially, the researchers presented ChatGPT-4 with a set of 120 Big Five Inventory (BFI) and 129 MBTI questions, instructing the model to provide answers in a comma-separated values (CSV) format. They then evaluated the responses according to the guidelines set by the BFI and MBTI frameworks to identify the personality traits exhibited by ChatGPT-4.
The BFI focused on five major dimensions: openness, conscientiousness, extraversion, agreeableness, and neuroticism, while the MBTI assessed personality based on dichotomies such as introversion vs. extraversion, sensing vs. intuition, thinking vs. feeling, and judging vs. perceiving.
In a second experiment, the authors employed a "chain prompting" approach to try to influence the personality of ChatGPT-4. They provided the model with a series of prompts designed to make it adopt an introverted personality. Following these prompts, they repeated the BFI and MBTI assessments to observe any changes in the results. The aim was to see if the model could exhibit a measurable shift in personality traits, demonstrating adaptability based on user interactions.
The study also included a comprehensive review of relevant literature to understand the current state of research on chatbot personalities and identify any gaps. This review covered existing methodologies for assessing AI personalities, previous findings on the adaptability of chatbots, and theoretical frameworks underpinning personality assessments. Additionally, the paper featured a detailed technical review of the transformer networks and NLP techniques. This review provided insights into how the model processes language and generates responses, which are critical for understanding its ability to exhibit and adapt personality traits.
Research Findings
The outcomes of the initial personality assessments showed that ChatGPT-4 exhibited a range of personality traits, with some variability across the three iterations of the experiments. For the Big Five Personality Test, the model scored high in openness to experience, agreeableness, and conscientiousness, while the scores for neuroticism and extraversion were more variable. In the MBTI assessment, ChatGPT-4 was consistently identified as having an "ISTJ" (introverted, sensing, thinking, and judging) personality type, with some fluctuations in the specific percentages for each trait.
When the authors attempted to influence the personality of ChatGPT-4 using the chain prompting approach, the model was able to adapt its responses to align with an introverted personality. The subsequent BFI and MBTI assessments showed a clear shift towards more introverted traits, with the MBTI results consistently identifying the model as having an "INFJ" (introverted, intuitive, feeling, and judging) personality type.
Furthermore, the paper noted that the consistency in personality traits was stronger in the Big Five assessments compared to the MBTI. This suggests that the Big Five framework might be more robust for evaluating AI personalities. Additionally, the chain prompting method proved effective in altering specific traits without completely changing the overall personality structure of GPT-4.
Applications
Understanding ChatGPT-4's personality traits can help developers design more engaging and personalized user experiences. Tailoring the chatbot's personality to match user preferences can make interactions more natural and enjoyable. This ability can be useful in customer service, education, and mental health support, where chatbots with specific personality traits can better suit different users' needs or tasks, improving interaction effectiveness.
Conclusion
The article provided valuable insights into the personality of ChatGPT-4 and its adaptability based on user input. The findings suggested that LLM like ChatGPT-4 can exhibit measurable personality traits, which can be influenced through careful prompting and input manipulation.
The study also noted limitations, such as inherent differences between human and AI personalities and potential biases from GPT-4's training data. Despite these issues, the authors underscored the potential of using personality assessments to improve AI interaction quality, making systems more user-friendly and relatable.
While the research demonstrated the potential for personalized chatbot interactions, it also raises ethical concerns about such adaptability. Future work should explore the long-term effects of personality-driven chatbots and investigate ways to ensure their responsible development and deployment.
Apple Researchers Challenge Large Language Models' Math Reasoning Capabilities with New Benchmark