While biases in AI have long been a topic of conversation for data science experts, this year in particular has brought conversations around racial bias to the forefront and sparked a call to action for industry experts to find tech-based solutions to existing challenges around D&I within data. In this presentation at the ML Conference, Getty Images’ senior data scientist Dan Gifford will share three key avenues to consider to confront bias in AI and use tech to create change.
Dan will cover some of the work he’s doing to lead change within Getty Images, as well as important updates to best practices within data science that can lead to stronger machine learning and computer vision. He will also address the importance of building ethical training and validation sets that take the contextual nuances of 2020, like wearing masks, into consideration. Additionally, Dan will talk through the importance of creating a strong, consistent pipeline for output accuracy, changing our perspectives on using open source datasets for training purposes, and identifying ways to retag existing datasets. As an industry, inconsistencies and inaccuracies in datasets are holding us back and creating a cyclical pattern of biases that are amplified in new products and nascent technologies. It’s crucial that we begin to adopt best practices now that not only prevent harmful biases from being coded into datasets and foundational technology, but that address systemic challenges as well.