Prompt Engineering Challenges
Explore common challenges in prompt engineering with Llama 3, including ethical concerns, ambiguous responses, knowledge cutoff, hallucinations, and model limitations. Learn strategies to craft ethical prompts, troubleshoot issues, and optimize the use of Llama 3 for more accurate and fair AI outputs.
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 ...