Various stakeholders have called for human oversight of algorithmic processes, as a means
to mitigate the possibility for automated discrimination and other social harms. This is even …

There are increasing expectations that algorithms should behave in a manner that is socially
just. We consider the case of image tagging APIs and their interpretations of people images …

Many intelligent systems depend on black-box services for achieving goals. For example,
Decision Support Systems (DSS) incorporate image tagging services for translating the …

Abstract Image Tagging Algorithms (ITAs) are extensively used in our information
ecosystem, from facilitating the retrieval of images in social platforms to learning about users …

Image analysis algorithms have become an indispensable tool in our information
ecosystem, facilitating new forms of visual communication and information sharing. At the …

Data generation through crowdsourcing has become a common practice for building or
augmenting an Artificial Intelligence (AI) system. These systems often reflect the …

In this paper, we examine computational approaches for measuring the" fairness" of image
tagging systems, finding that they cluster into five distinct categories, each with its own …

Image analysis algorithms have been a boon to personalization in digital systems and are
now widely available via easy-to-use APIs. However, it is important to ensure that they …

Due to the widespread use of data-powered systems in our everyday lives, the notions of
bias and fairness gained significant attention among researchers and practitioners, in both …

Much attention has been on the behaviors of computer vision services when describing
images of people. Audits have revealed rampant biases that could lead to harm, when …