Exploring Ways to Engineer Prompts in ChatGPT: Embracing Continuous Learning and Experimentation

This is part 4 of a series of guides on how to create better prompts in ChatGPT 4. In this project, I plan to have ChatGPT generate almost all the content, from the useful tips (for prompt engineering) to its written format as a blog post. My role will be to prompt such results, and checking to ensure that the content generated is in fact useful information (as far as I can tell, of course).

The outline for the guide, for now, is centered around various useful tips that can help you create prompts that better produce the responses you desire from ChatGPT. The major themes are;
1) Setting the Basic Context and Purpose
2) Refining and Tweaking the Response
3) Dealing with Complex or Unusual Requests
4) Continuous Learning and Experimentation
5) Generating Ideas and Creative Output.
In addition to this, I will add further methods such as adversarial prompting and any such new techniques as they are developed or discovered, to create a comprehensive guide to prompting ChatGPT.

Now, let’s continue with the fourth chapter of this guide: Continuous Learning and Experimentation

Welcome to the ChatGPT 4 Guide — Episode 4: Embracing Continuous Learning and Experimentation

In this episode, we dive into an important and often overlooked aspect of interacting with AI models such as ChatGPT 4 — the art of continuous learning and experimentation. We will be discussing strategies to cultivate a feedback loop, enhance comprehension through active listening, and how to gracefully handle AI limitations. Let’s get started!

1. Patience and Experimentation

AI interactions aren’t always perfect. They may require some tweaking and adjustment to achieve desired results.

Prompt: “Give me an elaborate explanation of the current economic situation.”
Response: “I’m sorry, I can’t assist with that.”
Improved Prompt: “Please provide an overview of general economic principles such as inflation, GDP, and unemployment rates.”

In the improved prompt, we break down the topic into recognizable terms that the AI can handle, demonstrating patience and willingness to experiment with the query.

2. The Feedback Loop

The Feedback Loop is a strategy that involves giving constructive feedback to the AI based on its previous responses. If the AI’s response doesn’t exactly align with what you were hoping for, you can use your next prompt to give feedback about what you actually wanted. This method will help to steer the conversation back on track, offering the AI clearer guidance on your desired response.

Let’s see it in action:

Prompt: “Tell me about the environmental impacts of climate change.” Response: [General discussion about climate change]

In this case, the AI has provided a generic discussion about climate change. While informative, it doesn’t exactly address your specific interest in the environmental impacts.

Improved Prompt: “Your explanation about climate change is informative. However, I’m specifically interested in its environmental impacts, such as effects on wildlife, forests, and ocean ecosystems. Could you provide more details on these?”

Now, you’ve given feedback about the original response and clarified your interests. This should help steer the AI towards a response more in line with your original request.

3. Rephrase if Needed

‘Rephrase if Needed’ is a valuable method to improve communication with the AI when it’s not providing the information you’re seeking. If a prompt isn’t yielding the desired response, don’t be afraid to rephrase it. Different wording or a slightly altered perspective can often help elicit a better answer from the AI.

Now, let’s delve into some examples:

Prompt: “What’s the big deal about climate change?”
Response: [Vague explanation about the importance of climate change]

In this case, the AI provides a somewhat vague response, possibly due to the broad and colloquial nature of the original prompt.

Improved Prompt: “Could you explain the major consequences of climate change on our planet?”

In the improved prompt, the language is more direct and specific. This helps to focus the AI’s response towards a detailed discussion on the serious impacts of climate change.

4. Use of Questions

The ‘Use of Questions’ is a simple yet powerful strategy. By asking clear and direct questions, we can guide the AI towards providing the precise information we’re seeking. An important tip here is to be as specific as possible; the more explicit your question, the more targeted the AI’s response will be.

Let’s move forward with some examples:

Prompt: “Chat about climate change.”
Response: [General discussion about climate change]

The initial prompt here is rather open-ended and can lead to a wide array of responses from the AI.

Improved Prompt: “What are the main human activities contributing to climate change?”

With the improved prompt, the question is much more specific, which helps guide the AI towards providing a more focused answer.

5. Avoid Leading Questions

Leading questions are ones that prompt or encourage a specific answer. They’re often loaded with assumptions or biases that steer the conversation in a particular direction. When interacting with AI, these kinds of questions can limit the scope of the AI’s responses, and you might miss out on other important insights or perspectives. To get unbiased and broad answers, try to phrase your questions in a neutral way.

Let’s delve into an example:

Prompt: “Isn’t renewable energy the best solution to climate change?” Response: “Renewable energy is indeed a promising solution to climate change…”

In the initial prompt, the question is leading because it assumes that renewable energy is the best solution to climate change. This phrasing can guide the AI towards agreeing with this assertion, potentially bypassing other solutions.

Improved Prompt: “What are various solutions to tackle climate change?”

In the improved prompt, we remove the bias by asking an open-ended question about climate change solutions. This allows the AI to provide a more comprehensive answer.

6. Avoid Overloading the Prompt

Overloading a prompt is when you ask multiple complex questions or bring up various subjects in a single query. Although ChatGPT 4 is powerful, it performs best when dealing with one concept or question at a time. Overloading can make the task unnecessarily complex and may lead to less precise responses.

Let’s break this down with an example:

Prompt: “Can you explain the theory of relativity, and also the law of conservation of energy, and tell me how they both relate to the creation of the universe?”
Response: [Possibly a confusing mix of various concepts]

The initial prompt is overloaded with multiple complex questions. It’s asking for explanations of two distinct theories and their relation to the universe’s creation, all in one go. This can lead to a response that’s hard to follow or lacking in depth for each concept.

Improved Prompt 1: “Can you explain the theory of relativity?”
Improved Prompt 2: “Now, could you explain the law of conservation of energy?”
Improved Prompt 3: “How might these two theories relate to the creation of the universe?”

By breaking up the prompt into three simpler ones, we allow the AI to tackle each concept separately, leading to clearer, more in-depth responses.

7. Acknowledge AI Limitations

ChatGPT 4 doesn’t have access to real-time or personal information. It can’t provide advice like a human might, drawing on personal experiences, and it doesn’t have access to personal databases unless details are shared during the conversation. This means that some responses might not be as tailored or specific as one would get from a human conversationalist.

Let’s see this in action:

Prompt: “What’s the weather like in New York today?”
Response: “I’m sorry, but as an AI, I don’t have real-time data access. I can’t provide the current weather.”

In the prompt, the user asked for real-time information, which the AI can’t provide. Now, let’s look at an improved version of this interaction:

Improved Prompt: “Can you tell me how I could find out the weather in New York today?”
Response: “Sure! You can find out the weather by checking a reliable weather forecast website or app like the Weather Channel or Weather.com. Alternatively, if you have a voice assistant like Google Assistant or Alexa, you can ask them for the current weather in New York.”

In the improved prompt, the user acknowledges the AI’s limitations and instead asks for guidance on how to obtain the information they need, leading to a helpful response.

8. Practice Active Listening

Active listening is when you reflect back or summarize the AI’s responses in your own words. It can help clarify your understanding and, as a result, generate more targeted responses from the AI. It may seem unusual to apply active listening to an AI conversation, but the benefits to comprehension and communication are noteworthy.

Let’s illustrate this with an example:

Prompt: “What’s the difference between a virus and bacteria?”
Response: “Bacteria are single-celled, living organisms that can survive in different environments, including the human body. Some bacteria can cause disease, but others are essential for functions such as digestion. Viruses, on the other hand, are smaller than bacteria and are not living organisms. They need a host, like a human or animal, to multiply and often lead to diseases.”

Imagine the user misunderstood the response:

Next Prompt: “So, if I got this right, both viruses and bacteria aren’t living things and they both need a host to multiply, right?”
Response: “I’m sorry if I didn’t explain it clearly. Bacteria are indeed living organisms and they don’t necessarily need a host to multiply. They can reproduce on their own in various environments. Viruses, however, are not considered living entities outside a host. They require a host’s cells to replicate and multiply. I hope this clarifies the difference.”

In the second prompt, the user reflected their understanding, which was incorrect. The AI was then able to correct the misunderstanding and provide a more precise explanation. That’s the power of active listening.

Remember, mastery comes with practice. The more you interact with the model, the better you become at eliciting desired responses. The journey with AI is about continuous learning and adjustment. We hope these tips enhance your interactions with ChatGPT 4.

Stay tuned for the next episode of our ChatGPT 4 Guide. Happy experimenting!

Thank you for reading, and I hope you found it informative and interesting.

I would love to hear any thoughts from you on my experiment with ChatGPT. If you are interested in discussing more about how ChatGPT can be used in such political contexts, or have any questions, contact me at hello@simplawfy.ca

Disclaimer: This story is only intended to be used for educational or recreational purposes. Responses by ChatGPT, if mentioned in this story, should NOT be relied upon as factual.