We recognize that AI models can inadvertently learn and amplify biases present in training data, leading to exclusion of marginalized groups. We realize that without lived experience, we might never know how to solve specific problems. We need to learn how to make our systems accessible to people with diverse linguistic and cultural backgrounds, and to accommodate the needs of people with disabilities.
We commit to bringing those with lived experiences to the process and allow those who are traditionally the audience to become the creators of the solutions that work best for them. We will collaborate with our partners to co-create systems that are culturally relevant and address their specific needs. We will conduct user testing with diverse groups of people, to identify and address biases, usability issues, and accessibility barriers. We will also continue to use feedback from users with lived experience to iteratively improve and ensure we remain relevant and beneficial.
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