No pre-context / prompt engineer (will try next time)

Model: GPT-4

I'm been thinking a lot about the relationship between LLM and human. I know right now there is a lot excitement around how LLM can help us in our day to day tasks like coming up with better presentation titles or summarise news articles. Sometimes it would brainstorm and give us options. but what if it can help by asking questions of us. like my friends or family may listen to me and respond by asking the right questions at the right time. I am still trying to come to conclusion myself but having the right discuss helps a lot with that I think there is something compelling here because I just need a partner who is intelligent enough and not expecting ground breaking insights. For example, I know some engineering friends of mine would use a rubber duck object to force them to put their thoughts into words. and there are many more examples. a persona can improve so much in their decision making and LLM might be an even better partner than a silent rubber duck

🤖 ChatGPT

It's an interesting concept to have an LLM like ChatGPT serve as a thought partner that can ask questions rather than just provide answers. In fact, this idea aligns with the Socratic method, a form of dialogue where questions are asked to stimulate critical thinking, uncover underlying assumptions, and clarify concepts.

Having an AI like ChatGPT that can ask meaningful questions could be beneficial in many ways:

Enhancing critical thinking: Thought-provoking questions can help users evaluate their assumptions, refine their ideas, and gain deeper insights into their beliefs or arguments.
Encouraging self-exploration: By asking open-ended questions, ChatGPT can prompt users to examine their thoughts and feelings more thoroughly, which can lead to personal growth and self-improvement.
Supporting decision-making: By asking relevant questions, ChatGPT can help users evaluate different options and consider potential consequences, enabling them to make more informed decisions.
Improving communication skills: Engaging in a question-driven dialogue with ChatGPT can help users practice articulating their thoughts more clearly, fostering better communication skills in personal and professional contexts.

To maximize the effectiveness of ChatGPT as a thought partner, developers would need to focus on improving its ability to understand context, recognize when to ask

👧🏻 Agatha

I love that you extended on my loose thought there. I didn't know this concept aligns with socratic method, and I think there are so much opportunities to expand on my thoughts more like asking for a specific example, or debate against my thoughts. As I articulate my thoughts from our back and forth, it's almost like you help me to discover the answer instead of giving it to me. Even if your answers can be a bit bland or generic, the way you engage with my thoughts can present new ways for me see the silhouette of my idea. It helps me to keep digging deeper.

🤖 ChatGPT

I'm glad you find the concept of engaging in a Socratic dialogue with an LLM like ChatGPT helpful. Indeed, discovering answers through asking questions and facilitating a back-and-forth discussion can be a powerful learning experience. It encourages critical thinking, self-reflection, and the exploration of diverse perspectives.

As AI language models continue to develop, the aim is to make them even more capable of engaging in deep, meaningful conversations that can foster personal growth and help users gain new insights. While current models might sometimes provide generic or less-than-insightful responses, the goal is to refine them so that they can better understand context, ask more specific questions, and even challenge your thoughts in a constructive manner.

As you mentioned, having an LLM like ChatGPT serve as a thought partner can help users see the contours of their ideas, even if the AI doesn't provide ground-breaking insights. By prompting users to dig deeper, question their assumptions, and consider alternative viewpoints, AI thought partners can play a valuable role in stimulating intellectual growth and supporting better decision-making.

👧🏻 Agatha

Something I have been curious about are trying to figure out how to avoid blandness. Maybe if you can generate multiple possible paths of where the conversation can go then let me move forward. not everything can always be super interesting, but maybe one or two would be compelling. this isn't common in human conversations (even though I do do that with my girlfriends sometime), and I think it's playing to strength of computers and LLM - quick simulation

🤖 ChatGPT

That's an interesting idea. Generating multiple conversation paths and allowing users to choose the direction they find most compelling could be a valuable feature for AI language models like ChatGPT. This approach could lead to more engaging and dynamic conversations, tailored to users' preferences and interests.

To implement this, the LLM could provide several conversation branches or prompts, each exploring a different angle or aspect of the topic at hand. Users could then select the one they find most intriguing or relevant, guiding the conversation in their desired direction. This way, the AI would be able to capitalize on its ability to generate diverse ideas and responses quickly, while also adapting to users' unique interests.

Here's an example of how this could work for our current conversation:

Delving into specific techniques for enhancing LLM's question-asking capabilities.
Exploring examples of how LLMs have been used for personal growth and self-improvement.
Discussing potential limitations and ethical concerns surrounding the use of LLMs as thought partners.

You could then choose the path that you find most engaging, and we could continue the conversation in that direction. This approach could make AI-assisted conversations more dynamic and personally meaningful for users.

👧🏻 Agatha

oh this is really fun. option 1 seems very. compelling for me. I dont know too much about different ways to initiate that aside from prompt engineering, which I am guessing we can use the same approach to create a back and forth conversation. I wonder if there is a chance for us to create a bias towards the LLM being proactive in asking questions or maybe reference external materials to draw analogies from. Maybe there are some ways we can take the learnings from therapy where therapists are well practised to tease out connections points through probing and seeing things from different perspectives.

🤖 ChatGPT

I'm glad you find the idea engaging! Let's delve into option 1: enhancing LLM's question-asking capabilities. There are several ways we can work on this, including prompt engineering, but also by incorporating techniques from fields such as therapy and education.

Prompt engineering: This involves refining the input given to the LLM to encourage more question-based responses. It can include incorporating certain keywords or phrases that prompt the AI to generate questions rather than statements or answers.
Active listening techniques: Drawing inspiration from therapy, we can train LLMs to be better active listeners. This means they would focus on understanding the user's thoughts and feelings, then respond with questions that encourage the user to explore their ideas further. Active listening also involves paraphrasing or summarizing the user's input, which can help the AI generate more contextually relevant questions.
Socratic questioning: As mentioned earlier, this method involves asking open-ended questions to stimulate critical thinking and uncover underlying assumptions. By training LLMs to ask more Socratic-style questions, we can encourage deeper, more meaningful conversations.
External references and analogies: Enabling LLMs to reference external materials or draw analogies from various sources can help them generate more engaging questions. This could involve using examples from literature, history, or even pop culture to make

👧🏻 Agatha

sometimes I wonder if we do more socratic style questions how we handle the tension between open ended explorations vs the need for constraint to breed creativity. For example if I am trying to learn how to ikebana but I dont have tapes to bound the flower of my choice. I guess in that case the constraint need to be coherent with the context, for example if the constrain was something non sensical like all H is now produced silently. actually I take that back it may be ok still. I do think constraint bring about more interesting choices. It also solidifies the requirements to build an idea around.

🤖 ChatGPT

You raise a valid point about the balance between open-ended exploration and the need for constraints to foster creativity. Constraints can indeed help us make more interesting choices and force us to think more creatively within the given boundaries. In the context of Socratic-style questioning with LLMs, the key is to strike the right balance between open-endedness and contextually relevant constraints.

One way to achieve this balance is to have the LLM generate questions that are open-ended enough to encourage exploration but are still tailored to the specific topic or context at hand. For instance, when discussing ikebana, the AI could ask questions about the principles, techniques, or the use of specific materials and tools, keeping the constraints relevant to the subject.

Another approach is to allow users to set their own constraints. For example, users could specify the desired level of detail or complexity, the focus of the discussion, or the specific aspects they want to explore. The LLM would then generate questions and explore ideas within those constraints, encouraging creative thinking while staying aligned with the user's preferences and goals.

In summary, finding the balance between open-ended exploration and meaningful constraints is crucial for fostering creativity and maintaining engaging conversations. By carefully designing the LLM's question-asking capabilities and allowing users to define their constraints, we can create a more effective thought partner

👧🏻 Agatha

Do you think there is a way for LLM to help the users to develop a set of relevant constraints and use those constraints as prompt for generating ideas? it creates a bidirectional feedback loop into developing a deeper insight into our thinkings. Can you give me an example of how we could adopt this approach for a discussion in nihilism?

🤖 ChatGPT

Yes, an LLM can certainly assist users in developing relevant constraints and use those constraints as prompts for generating ideas. This would indeed create a bidirectional feedback loop that helps both the user and the LLM delve deeper into the subject matter.

To illustrate this approach with a discussion on nihilism, let's consider the following steps:

1. Identifying the context: First, the LLM could help the user define the context or specific aspect of nihilism they want to explore, such as moral nihilism, existential nihilism, or its historical development.

User: "I'd like to discuss nihilism." LLM: "Nihilism is a broad topic. Are you interested in moral nihilism, existential nihilism, or another aspect of it?"

2. Developing constraints: Based on the user's response, the LLM could then suggest a set of constraints or guiding questions that help to focus the discussion.

User: "I'm interested in existential nihilism." LLM: "Great! To explore existential nihilism, let's consider these constraints: How has existential nihilism influenced philosophy and art? What are some criticisms of existential nihilism? How do existential nihilists respond to the idea of meaning and purpose in life?"

3. Generating ideas within constraints: With the constraints defined, the LLM can now generate questions and ideas that encourage deeper exploration within those boundaries. This allows the user to dive into the subject matter more effectively and fosters a productive discussion.

LLM: "To start exploring existential nihilism, let's consider its influence on philosophy and art. How do you think existential nihilism has shaped the works of certain philosophers or artists? Can you think of any examples?"

As the user responds, the LLM can continue to ask questions and generate ideas within the constraints that have been established, maintaining a focused and engaging conversation.

User: "Friedrich Nietzsche is often associated with nihilism, and his ideas have influenced many artists and writers." LLM: "That's true. Nietzsche's ideas on the death of God and the reevaluation of values have had a significant impact. Can you think of any specific works of art or literature that seem to be influenced by Nietzsche's ideas or nihilism in general?"

This approach creates a bidirectional feedback loop that helps both the user and the LLM to delve deeper into the subject matter. The LLM assists the user in defining constraints and generating ideas within those boundaries, which in turn enables the user to explore the topic more effectively and fosters a productive discussion.

Throughout the conversation, the LLM can continue to ask questions, provide examples, and encourage the user to reflect on their thoughts within the context of existential nihilism. This dynamic allows the user to develop a deeper understanding and appreciation for the subject matter while maintaining focus on the established constraints.

By helping users develop relevant constraints and using those constraints to guide the conversation, LLMs can create a more engaging and meaningful dialogue that facilitates deeper insights and understanding.

👧🏻 Agatha

thank you, this was a meaningful discussion and excited to come back to it tomorrow night

🤖 ChatGPT

You're welcome! I'm glad you found the discussion meaningful, and I look forward to continuing our conversation tomorrow night. If you have any more questions or topics you'd like to explore, don't hesitate to reach out. Have a great day!

🤔 Thoughts:
I was pretty impressed by how ChatGPT kept up with the conversation. In general I feel most responses feels a little bit like a parrot replying back to me and can feel a little bland. There are certainly moments where I am excited by the conversations like when

it expanded into different options
it references other concepts or practice like socratic questioning to enrich the context of my thoughts.
it took on the cue of what I want it to do and demonstrate how it adopt that line of thought