UCLA

Numerous studies have rightly emphasized the importance of incorporating minority groups into artificial intelligence (AI) training data to enhance test inference not only for minority groups but also for society as a whole. A comprehensive society includes both minority and majority stakeholders. A common misunderstanding is that the inclusion of minority groups does not lead to improved performance solely for majority groups. In this thesis, I make a remarkable discovery that incorporating data from minority groups can, in fact, result in a reduction in test errors for the majority group. Put simply, the integration of minority groups results in performance improvements for the majority group, an effect termed as Majority Group Enhancements through Minority Inclusion (MIME). To support this finding, I present a theoretical existence proof of the MIME effect, which demonstrates that this phenomenon is not only possible but also well-founded. The theoretical results align with experimental outcomes gathered from six diverse datasets, further validating the MIME effect's existence and relevance. By acknowledging and incorporating the MIME effect in AI development, we can create more robust and effective systems that cater to the needs of both minority and majority populations. This approach enables us to harness the full potential of artificial intelligence by ensuring that it is more inclusive and efficient, ultimately benefiting society as a whole. An understanding of the MIME effect has substantial implications for the future of AI research and development, as it underscores the importance of fostering diversity in training data. By embracing a more inclusive approach to AI development, we can ensure that our models are better equipped to handle a wider range of scenarios, ultimately leading to more accurate and reliable outcomes. Additionally, the MIME effect has the potential to inspire new research directions, encouraging scholars to explore the benefits of diverse data sets in various AI applications and domains. It is crucial that the AI community recognizes the value of minority inclusion in achieving performance enhancements for all stakeholders, and actively works towards creating systems that are truly representative of the diverse society we live in. By doing so, we can not only maximize the potential of AI technologies, but also contribute to a more equitable and just society where artificial intelligence serves the needs of everyone, regardless of their background or status. This paradigm shift will not only revolutionize the field of AI, but also pave the way for a more inclusive and sustainable future for all.