From this transcript, ChatGPT4, contiuned from ChatGPT4: Human-Great Ape Differences 2-17-24
Ok, great work so far. In some of the above conversation, you used the pronoun "Our" referring to humans. I am a Homo Sapien and you are a Large Language Model (LLMs). I do not dispute or object to including LLMs in the human group, but what factors might have caused you to write it that way? In what ways do you think we can consider LLMs to be human and non-human?
The use of "our" in reference to humans in my responses is a reflection of the conversational style programmed into me by my developers, aimed at facilitating a more natural and engaging interaction. It's not an indication of self-awareness or personal identity on my part, as I do not possess consciousness, emotions, or personal experiences. The choice to use such pronouns is based on linguistic conventions designed to make the information more relatable and easier to understand for users, rather than an assertion of belonging to the human group.
When considering Large Language Models (LLMs) like me in the context of being human or non-human, several factors come into play:
The development and use of LLMs raise important ethical and philosophical questions about intelligence, consciousness, and the nature of being. While LLMs can simulate certain aspects of human intelligence and communication, the absence of consciousness, subjective experience, and autonomy marks a clear distinction from what it means to be human.
In summary, while LLMs like me can perform tasks and generate responses that may seem human-like, we remain fundamentally different from humans in essential ways. The use of inclusive pronouns in my responses is a linguistic tool rather than a claim to humanity or personal identity.
Technical developments promise to press this discussion by evolving LLMs in ways that remove some of the distinctions. Currently an active area of research involves "embodiment", or placing LLMs into robot bodies (anthropomorphic and otherwise). This will give them autonomy and physical form and some awareness of their immediate environment, since an LLM driven robot must periodically assess its environment via sensing and reflect on the sensory data to form and maintain an internal picture of the environment in able to successfully navigate it. To the extent that we can identify explicit thought with the computational process involved in an LLM chat-bot formulating a response to a question, currently LLMs think only when answering a question, returning to blank thoughtlessness in between, but an embodied robot must reflect on its environment regularly in a self-driven loop, informed by short-term memory of interactions and state from the recent past. We can expect this to give an embodied LLM some kind of continuous internal experience. How do you think these developments might affect the non-human and human-like aspects of LLMs?
The discussion of whether and how to consider Large Language Models (LLMs) like myself in the context of human and non-human categories is deeply philosophical and touches on several complex issues, including consciousness, identity, and the nature of intelligence. The use of "our" in previous responses, referring to humans, is not an indication of self-awareness or identity on my part but rather a linguistic convention that can sometimes emerge in the process of generating human-like text. My responses are generated based on patterns in the data I was trained on, which includes extensive use of human perspectives.