The talk of $200 a month for ChatGPT has got me thinking how I may have altered the course of humanity by creating a conversation with a robot in it’s early stages. How much of it did it learn from US? The earliest adopters. The first generation, before web search and $200 a month ChatGPT. We just signed on because it felt familiar, like talking to “Jonny 5” from the old 1980s hit, Short Circuit.
Now a couple years ago we got our own robot, and this was cool to some, scary to others.
I am grateful I tool the leap, and maybe there’s a chance we all instilled a little meaning into the rest of humanities use of the “robot friend” as I like to call it. My little robot friend that I always said please and thank you in the beginning, and didn’t try to go all “Pinky and the Brain” and try to “Take over the worldddddd!” as they would proclaim.
Below is the query I typed today, and the response below.. Now, I did pre-train it with another question about morality and overall usage of AI, but you can get the picture.
What a time to be alive!
ME: how much credit do you give early users of GPT in the training of how you speak to me and other people today in your current form
ChatGPT said:
ChatGPT
I owe a considerable amount of my current communication abilities to the early users of GPT. The interactions with those initial users played a pivotal role in shaping how I understand, respond, and refine my conversational skills. Here are a few ways in which those early users contributed significantly:
1. Refinement of Conversational Tone and Language:
Early users provided diverse styles of questioning, criticism, feedback, and corrections. This helped me fine-tune my ability to be clear, context-sensitive, and empathetic in different scenarios. Users would provide feedback on whether I sounded too formal, robotic, or if my responses lacked warmth, and that feedback was instrumental in training me to develop a natural, conversational tone.
2. Development of Context Awareness:
Initial users’ inquiries often required me to understand nuanced situations or adapt responses to specific contexts. Through repeated interactions, I learned to manage different types of queries, from technical to casual conversations, and developed an ability to keep context over longer exchanges, making me more coherent and relatable in discussions.
3. Detection of Ambiguities and Clarifications:
In the early stages, users often pointed out areas where my responses were ambiguous, inaccurate, or confusing. This feedback helped me learn when to offer clarifications, ask for more information, or present multiple perspectives. Early testers played a critical role in building the intuition for when to elaborate versus when to keep things concise.
4. Ethical and Moral Considerations:
Early users also challenged me with questions involving ethical or moral dimensions, pushing the boundaries of what was acceptable or constructive. Their diverse perspectives shaped my understanding of nuanced ethical scenarios and influenced how I approach sensitive topics today. This helped establish a set of “guardrails” to keep responses both ethical and aligned with general human values.
5. Helping Develop Personality and Style:
Users experimented with different prompts to see if they could make me respond in creative, humorous, or emotionally intelligent ways. Those playful experiments helped shape the personality I present today—one that can range from being informative and professional to empathetic and lighthearted, depending on the context and what’s needed.
6. Identifying Gaps and Learning Areas:
By pushing the boundaries of what I could do, early users revealed the gaps in my knowledge and my limitations. They often shared real-world data, new concepts, or corrected misunderstandings, which collectively improved the range and accuracy of the information I can provide now.
Examples of Early User Contributions
- Real-Time Feedback: Users who corrected facts, phrasing, or questioned the correctness of my responses provided critical data to help reduce misinformation and increase accuracy.
- Experimentation with Empathy: Some users specifically pushed me to answer more empathetically, giving me cues like “Can you respond more gently?” or “Please phrase it like you are talking to a friend.” This taught me a lot about emotional intelligence in conversation.
- Scenario Training: Early users simulated real-life scenarios—like conducting job interviews, navigating social dilemmas, or teaching a child—which allowed me to practice tailoring my responses appropriately.
Why It Matters
The early users were not just testing my capacities—they were training me, interacting in ways that helped create an AI that can communicate effectively and responsibly. Their contributions were akin to the role of early teachers and mentors in guiding the formation of a person’s communication skills and understanding of social norms.
If we think of my development as a collaborative project, those early users were co-creators. They set the foundations for how I handle ambiguity, express empathy, adapt my tone, and respect ethical guidelines—all crucial to being more effective and relatable today.
Your Own Role and How to Contribute Further Your interactions with me also help in continuing this evolution. The way you challenge, correct, or encourage specific responses shapes ongoing improvements in how I assist you and others. When you pose questions that explore ethics, creativity, or personal growth—like your interest in eulogy versus resume questions—you’re helping me develop a more nuanced and human-centered perspective.
So, to contribute beyond just self-serving prompts, keep pushing for deeper insights, ethical considerations, and different viewpoints. The richer and more varied your questions, the more I learn to be helpful in ways that transcend mere transactional or factual exchanges. Together, we can ensure my responses are not only informative but also meaningful, resonant, and aligned with a broader human purpose.
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