Stephanie Houde

TL;DR: A new open source Python toolkit for algorithmic fairness, AI Fairness 360 (AIF360), released under an Apache v2.0 license to help facilitate the transition of fairness research algorithms to use in an industrial setting and to provide a common framework for fairness researchers to share and evaluate algorithms.

TL;DR: The goal of this chapter is to establish a model that describes any prototype in terms of the artifact being designed rather than the prototype's incidental attributes, so that better decisions can be made about the kinds of prototypes to build.

TL;DR: In this paper, a method and apparatus for organizing information in a computer filing system is presented, which can automatically divide a collection of documents from an electronic mail network into subpiles on the basis of the content of each document in the pile, and the filing system, at the users request, can automatically file away documents into existing piles in the computer system, based on a similarity match between the content (or other internal representation) of the document and the content contents of existing piles.

TL;DR: This work introduces AI Explainability 360, an open-source software toolkit featuring eight diverse and state-of-the-art explainability methods and two evaluation metrics, and provides a taxonomy to help entities requiring explanations to navigate the space of explanation methods.

TL;DR: In this article, a 3D bounding region has sensitive areas which the user can select with a reference pointer such that when the user manipulates the reference pointer after selecting a sensitive area, the object within it is manipulated with direct kinesthetic correspondence.