Table 2.

Different bias mitigation methodologies proposed by the papers reviewed in this study.

Algorithm family	Sub-category	References	Mitigation method
NLP	Image Processing	Smith and Ricanek, 2020	Corpus Level Constraints
	Dialogue Systems	Liu et al., 2020	Adversarial Learning
	Voice Processing	Cramer et al., 2018	Checklists + Representative Data
	NA	Courtland, 2018	Algorithm Auditing
	Language Processing	Jia et al., 2020	Corpus Level Constraints + Posterior Regularization
	Language Processing	Bender and Friedman, 2018	Data Statements
	Word Embeddings	Prost et al., 2019	Scrubbing, Debaising and Strong Debiasing
	Word Embeddings	Wang et al., 2020	Double-Hard Debiasing
	Word Embeddings	Lu et al., 2020	Counterfactual Data Augmentation
	Word Embeddings	Maudslay et al., 2019	Counterfactual Data Augmentation
	Word Embeddings	Zhao et al., 2018	Gender Neutral Word Embedding
	Word Embeddings	Wang Z. et al., 2019	Representative Data
	Abusive Language Detection	Singh and Hofenbitzer, 2019	Equalized Odds processing
	NA	Courtland, 2018	Auditing Algorithms
	NA	Hitti et al., 2019	Gender Bias Taxonomy
	Advertising	Farnad et al., 2020	Greedy Algorithm
Automated facial analysis	Facial Recognition Task	Wang T. et al., 2019	Adversarial Debiasing
	Face Attribute Recognition	Kärkkäinen and Joo, 2019	Representative Data
	Gender Classification	Wu et al., 2020	Representative Data (Racial + LGBTQIA+)
	Facial Processing Technology	Dass et al., 2020	Representative Data + Human Annotated Data
	Automated Face Analysis	Das et al., 2018	Multi-task Convolution Neural Network
	Facial Classification Task	Molina et al., 2020	Data Augmentation
	Facial Recognition Task	Morales et al., 2020	Adversarial Regularizer
	Facial Recognition Task	Dhar et al., 2020	Adversarial Debiasing
	Automated Face Analysis	Katell et al., 2020	Algorithmic Equity Toolkit
Recommender system	NA	Baeza-Yates, 2020	Explore and Exploit Paradigm
	Music Recommender	Melchiorre et al., 2021	Resampling and Rebalancing Data
	Job Recommender	Geyik et al., 2019	Greedy Algorithm
	Job Recommender	Barnabò et al., 2019	Greedy Set Cover and Linear Programming
	Job Recommender	Vasudevan and Kenthapadi, 2020	Annotated Data + LiFT Framework
Object classification	NA	Chakraborty et al., 2020	Removing and Relabeling Data + FAIR_FLASH
	Collected Inference	Zhao et al., 2017	Langarian Relaxation
	Classification	Feldman and Peake, 2021	Disparate Impact Remover + Adversarial Debiasing + Calibrated Equalized Odds