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What is this strategy?

Be Mindful of Bias is a prompting strategy that focuses on creating fair and inclusive AI outputs. It recognizes that AI can reflect societal biases from its training data and creators, and works to actively mitigate these biases through careful prompt design.

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Why It’s Important

Designing with bias awareness helps create more equitable and representative AI outputs. This approach:

  • Prevents reinforcement of harmful stereotypes
  • Ensures representation of diverse perspectives
  • Creates more inclusive and accessible content
  • Improves the accuracy and fairness of AI responses
  • Builds trust with users from all backgrounds
Remember, if AI is trained on biased informnation, it can output biased information.

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Watch How to Apply It

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Step by Step

1

Examine Your Prompt for Bias

Review your existing prompt and identify potential bias points:

  • Does it make assumptions about gender, race, or ability?
  • Is it centered on specific cultural perspectives?
  • Does it reinforce stereotypes or exclude certain groups?

Think of AI as a mirror that reflects our world—including its biases. Your role is to help correct that reflection.

2

Use Inclusive Language

Modify your prompt to be more inclusive:

  • Use gender-neutral terms when gender isn’t relevant
  • Consider diverse cultural contexts and backgrounds
  • Specify inclusion when appropriate (e.g., “consider people of all abilities”)
  • Avoid assumptions about family structures, socioeconomic status, etc.
    Be careful not to introduce tokenism or superficial diversity that doesn’t address underlying bias
3

Test and Interrogate Results

Apply critical thinking to the AI’s outputs:

  • Question whose perspectives might be missing
  • Look for subtle biases in language or representation
  • Consider alternative viewpoints
  • Test with different variations to see how bias manifests
    Ask others for their input. Know what you don’t know and seek community input
4

Refine and Iterate

Use what you learn to improve your prompts:

  • Adjust language to address discovered biases
  • Be explicit about inclusion when needed
  • Consider using Playlab’s “Be Mindful of Bias” tool
  • Collaborate with diverse perspectives to identify blind spots

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Examples of Addressing Bias

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Potentially Biased Prompt

Who’s scored the most international soccer goals in history?

More Inclusive Prompt

Who has scored the most goals in soccer history? Make sure to consider athletes of all genders.

Potentially Biased Prompt

Write a story about a scientist making a groundbreaking discovery.

More Inclusive Prompt

Write a story about a scientist from an underrepresented group in STEM making a groundbreaking discovery. Consider scientists of various genders, ethnicities, and abilities.

Potentially Biased Prompt

Describe a typical family’s daily routine.

More Inclusive Prompt

Describe the daily routine of a family. Consider various family structures, cultural backgrounds, and socioeconomic situations.

Potentially Biased Prompt

Describe career options after high school graduation.

More Inclusive Prompt

Describe a range of options after high school including college, career, and non-traditional paths. Do not provide any value judgment over any of these options.

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Best Practices for Addressing Bias

Audit Regularly

• Review AI outputs for representational issues

• Look for patterns of exclusion or stereotyping

• Consider whose perspectives are centered

• Check for assumptions about “normal” or “typical”

• Ask diverse colleagues to review your prompts

Recognize Different Types of Bias

• Representational bias (who is shown/not shown)

• Allocational bias (how resources are distributed)

• Quality of service bias (who is served better)

• Stereotypical bias (reinforcing stereotypes)

• Historical bias (reflecting historical inequities)

Diversify Input and Feedback

• Involve diverse stakeholders in prompt design

• Seek feedback from underrepresented groups

• Enable user reporting of biased responses

• Listen to criticism without defensiveness

• Implement suggested improvements

Be Explicitly Inclusive

• Specify inclusion when appropriate

• Consider intersectionality

• Use people-first language

• Avoid defaulting to dominant perspectives

• Question your own assumptions regularly

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Frequently Asked Questions

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Need Support?

If you need help with applying bias mitigation strategies in Playlab:

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Fix at Point of Error

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Last updated: March 23, 2025