Where is the accountability for AI ethics gatekeepers?

Elite institutions, the self-appointed arbiters of ethics are guilty of racism and unethical behavior but have zero accountability. In July 2020, MIT took a frequently cited and widely used dataset offline when two researchers found that the '80 Million Tiny Images' dataset used racist, misogynistic terms to describe images of Black and Asian people. According to The Register, Vinay Prabhu, a data scientist of Indian origin working at a startup in California, and Abeba Birhane, an Ethiopian PhD candidate at University College Dublin, who made the discovery that thousands of images in the MIT database were "labeled with racist slurs for Black and Asian people, and derogatory terms used to describe women." This problematic dataset was created back in 2008 and if left unchecked, it would have continued to spawn biased algorithms and introduce prejudice into AI models that used it as training dataset. This incident also highlights a pervasive tendency in this space to put the onus of solving ethical problems created by questionable technologies back on the marginalized groups negatively impacted by them. IBM's recent decision to exit the Facial Recognition industry, followed by similar measures by other tech giants, was in no small part due to the foundational work of Timnit Gebru, Joy Buolamwini, and other Black women scholars.