KeepA(n)I – A Methodological Approach for Identifying Social Stereotypes in Artificial Intelligence Applications

Given the potential of algorithmic systems to influence the social world, by amplifying or abating bias and potential discrimination, KeepA(n)I will develop a structured, methodological approach to aid developers and machine learning practitioners to detect social bias at the input datasets and output data of the application. KeepA(n)I is envisioned as a human-in-the-loop approach, methodically exposing social stereotypes and reducing the negative impact or even enhancing people’s access to opportunities and resources when interacting with both high and low risk AI applications.