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	Towards Fairness in Practice: A Practitioner-Oriented Rubric for Evaluating Fair ML Toolkits (ACM SIGCHI) View
	Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits (ACM FAccT Conference) View
	Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits (ACM FAccT Conference) View
	The Landscape and Gaps in Open Source Fairness Toolkits (ACM SIGCHI) View
	ESEC/FSE 2020 Presentation on Fairness (Sumon Biswas) View
	GO FAIR - FAIR made easy (GO FAIR Initiative) View
	A Moral Framework for Understanding Fair ML through Economic Models of Equality of Opportunity (Hoda Heidari) View
	White-box Fairness Testing through Adversarial Sampling (ICSE) View
	3 5 2 5 Fairness and Reciprocity 8 09 (Jason Wells) View
	Towards Understanding Perceptual Differences between Genuine and Face-Swapped Videos (ACM SIGCHI) View