Prompt Engineering Challenges

In this era, AI models have become an essential part of our daily lives. LLMs and their abilities are evolving with every passing day with the launch of every upgraded version. As AI continues to become part of our lives, concerns about bias and fair responses rise.

Ethical prompt engineering

Although Meta AI added special guidelines to refine the way Llama 3 responds to questions about social issues and politics, it still often generates biased responses based on the data used to train the model. For example:

• Generating gender-specific responses for professions like doctors or engineers.

• Associating hobbies or interests with specific genders.

• Making assumptions about personality traits based on appearance.

• Assuming a specific age range for a particular profession or activity, etc.

Ethical prompt engineering has emerged as a tool to address these issues. It is the process of carefully writing prompts that minimize the probability of generating biased responses.

Ethical prompt engineering means to responsibly use AI to avoid biased and objectionable responses. By carefully crafting the input question, we can ensure that the Llama 3 model generates fair and transparent responses that align with human values.

Troubleshooting common issues

Like any LLM, the Llama 3 model also has some risks and challenges with its use. Let's troubleshoot some of the common issues we face while prompting it.

Ambiguous response

Let's see when the model results in an ambiguous response and how to avoid it.

Problem

The Llama 3 model often misinterprets the prompt, which results in an ambiguous and irrelevant response.

Solution

To avoid such unexpected results, write a concise prompt with clear instructions without using difficult vocabulary and complex sentence structure.