As we approach the two-year mark of ChatGPT and the subsequent explosion of generative AI applications, it’s clear that while AI technology has the potential to greatly improve our lives, there are also risks of bias that need to be addressed.
AI has quickly moved from assisting with simple tasks to making decisions that have significant impacts on our lives, such as insurance claims and housing decisions. The bias present in these models is concerning, especially when they have such a direct influence on our livelihoods.
To address bias in AI, we need more diversity in the talent developing these models. Currently, women and minorities are underrepresented in STEM fields, which has a direct impact on the diversity of AI teams. By encouraging early education and exposure to STEM for women and minorities, we can create a more diverse workforce that is better equipped to recognize and mitigate bias in AI models.
Representation matters, and by showcasing diverse role models in STEM fields, we can inspire young girls to pursue careers in these areas. Organizations like Data Science for All and AI bootcamps can help provide opportunities for underrepresented groups to explore STEM fields.
Bias in AI can manifest in many ways, from the data used to train models to the personal biases of the developers creating them. By acknowledging the existence of bias and actively working to address it, we can create more inclusive and accurate AI models.
Ensuring that a diverse group of women have a voice in the development and oversight of AI models is crucial to mitigating bias. By including a variety of perspectives in the process, we can create models that are more reflective of the diverse world we live in.
While completely eliminating bias from AI may be challenging, increasing diversity in STEM fields and AI development is a step in the right direction. By creating more inclusive and diverse teams, we can build more accurate and fair AI models that benefit everyone.
