News and Insights
Tips for Mitigating Risk of Bias
January 18, 2024
This guide helps users of Generative AI recognize and mitigate the risk of bias in Generative AI.
- Understand AI’s limitations
Generative AI models can ‘inherit’ biases from their training data and other sources. When evaluating outputs, be mindful that they may include societal biases or stereotypes. - Diversify input data
When prompting an AI tool, always try to provide diverse and inclusive data and/or content that represents different demographics, cultures, and perspectives.
- Critically review and edit outputs
Look for biases or inaccuracies that may have been inadvertently produced by the tool(s) you’re using.
- Treat sensitive topics with care
When generating content for topics like race, gender, or religion, take extra time to scrutinize (and potentially revise) outputs to ensure they’re fair and respectful.
- Use multiple models
Because generative AI systems may exhibit varying levels of bias depending on their training data and architecture, it’s best to experiment with different models and compare outputs.
- Edit outputs
Fix outputs that seem biased or inappropriate and share corrections with models.
- Stay informed
Keep up-to-date with the current issues and best practices surrounding bias in generative AI and share your discoveries
- Provide feedback to developers
Most generative AI platforms welcome user feedback – if you encounter biased outputs consistently from a specific AI tool, share your thoughts and help them improve.
- Educate yourself
Knowledge can empower you to make informed decisions when using generative AI tools. Learn more about how they work and the factors that can contribute to bias in their models.
- Be a champion for the ethical use of AI
Encourage responsible AI use and advocate for diversity, fairness, and inclusivity in AI – your voice can contribute to creating a more ethical AI ecosystem.