Assigning Roles

Introduction

This document dives into role prompting, a technique that allows users to assign roles to an AI model to control the style, tone, or depth of its generated text. You'll learn how role prompting is applied to various use cases, including text styling and improving accuracy in tasks like reviews, emails, and math problems.

1. What is Role Prompting?
2. Application #1: Styling Text
   • Example #1: Changing the Style of a Food Review
   • Example #2: Writing Email
3. Application #2: Improving Accuracy
4. Conclusion
5. FAQ

1. What is Role Prompting?

Role prompting is a technique that involves assigning a role or persona to an AI model, such as "food critic" or "mathematician," to control the style or accuracy of its responses.

By instructing the model to take on a specific role, you can shape how it processes and delivers information. This technique is widely used across many applications, from creative writing to problem-solving.

2. Application #1: Styling Text

Role prompting is most commonly used to alter the style of AI-generated text. By assigning a role, such as a food critic or a marketing expert, the AI can adjust its tone, language, and the depth of its responses based on the given persona.

2.1 Example #1: Changing the Style of a Food Review

To ensure your review resonates with your intended audience, consider factors like length, style, language, and tone, and use these to craft a review that speaks directly to your readers' interests and expectations. With a thoughtful approach and a focus on quality content, you can create a review that truly captures the essence of the pizza place you're writing about. Let's start with a simple prompt without a role.

Simple Review Prompt:

Let’s see how assigning the AI the role of a food critic or a Michelin Guide reviewer changes the output when writing a food review.

Role Prompt - Food Critic:

We can see that it adds more detail and goes a bit more in-depth. Now let's go a step further and make it assume the role of a writer for the Michelin guide:

Role Prompt - Michelin Guide Reviewer:

Now we can see how assigning ChatGPT the role of a food critic makes the review seem more "rich" and "professional" in its description.

You can try it for yourself here:

2.2 Example #2: Writing Email

Let's consider another example of styling text with role prompting. Let's say you ask the AI to write an email to a client to inform them about a delay in the delivery schedule due to logistical issues. Your goal is to effectively convey this update while ensuring the client's confidence in your services remains unwavering.

When drafting emails, role prompting can significantly change the tone of the message depending on the role assigned to the AI.

Communications Specialist:

For instance, one possible role is that of a communications specialist, whose style might be clear, professional, and to the point:

Marketing Expert:

Alternatively, have the model adopt the role of a marketing expert to lean more on persuasion, positivity, and relationship building:

Customer Service Representative:

Lastly, the role of a customer service representative might lead to a more relational and solution-oriented output:

Each of these role prompts will yield different results, aligning more closely with the perspective of the assigned role. Whether you need the directness of a communications specialist, the persuasive positivity of a marketing expert, or the empathetic problem-solving approach of a customer service representative, role prompts allow you to tailor the language model to better fit your needs.

Application #2: Improving Accuracy

Role prompting can also improve the accuracy of AI outputs , especially in mathematical problem-solving.

Consider this example:

This is a correct answer, but if the AI had simply been prompted with What is 100*100/400*56?, it would have answered 280 (incorrect).

Try it here:

4. Conclusion

Role prompting is a versatile prompting technique for shaping the output of generative AI models. By assigning specific roles to the AI, users can control the style, tone, and even the accuracy of the responses, making it highly effective for tasks like writing, problem-solving, and more. As you explore the capabilities of AI, role prompting will continue to play a crucial role in improving the quality of outputs.

5. FAQ

Why should I use role prompting?

Role prompting is an effective method of getting the AI model to respond in a specific style and is commonly used in system instructions.

What are some examples of role prompting?

Some examples of role prompting are assigning the role of a food critic to write a better review, the role of a marketing expert to improve email writing, and the role of a brilliant mathematician to get a more accurate response to an arithmetic problem.

Sander Schulhoff

Sander Schulhoff is the Founder of Learn Prompting and an ML Researcher at the University of Maryland. He created the first open-source Prompt Engineering guide, reaching 3M+ people and teaching them to use tools like ChatGPT. Sander also led a team behind Prompt Report, the most comprehensive study of prompting ever done, co-authored with researchers from the University of Maryland, OpenAI, Microsoft, Google, Princeton, Stanford, and other leading institutions. This 76-page survey analyzed 1,500+ academic papers and covered 200+ prompting techniques.

Footnotes

1. Shanahan, M., McDonell, K., & Reynolds, L. (2023). Role-Play with Large Language Models. ↩

2. Li, G., Hammoud, H. A. A. K., Itani, H., Khizbullin, D., & Ghanem, B. (2023). CAMEL: Communicative Agents for “Mind” Exploration of Large Scale Language Model Society. ↩

3. Santu, S. K. K., & Feng, D. (2023). TELeR: A General Taxonomy of LLM Prompts for Benchmarking Complex Tasks. ↩

4. This appears to be less effective with newer models. Read Revisiting Roles for more information. ↩