4 questions to ask when evaluating AI prototypes for bias • TechCrunch

It's true there has been progress around data protection in the U.S. thanks to the passing of several laws, such as the California Consumer Privacy Act (CCPA), and nonbinding documents, such as the Blueprint for an AI Bill of Rights. Yet, there currently aren't any standard regulations that dictate how technology companies should mitigate AI bias and discrimination. As a result, many companies are falling behind in building ethical, privacy-first tools. Nearly 80% of data scientists in the U.S. are male and 66% are white, which shows an inherent lack of diversity and demographic representation in the development of automated decision-making tools, often leading to skewed data results. Significant improvements in design review processes are needed to ensure technology companies take all people into account when creating and modifying their products.