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Aylin Caliskan My first name is pronounced as Eye-lin Assistant Professor Department of Computer Science Institute for Data, Democracy, and Politics George Washington University     SEH 4590   aylin@gwu.edu        @aylin_cim

My research interests lie in artificial intelligence (AI) ethics, AI bias, computer vision, natural language processing, and machine learning, with a strong interest in human centered computing. I study the impact of machine intelligence on society, especially threats to fairness, privacy, and democracy. I investigate the reasoning behind biased AI representations and decisions by developing explainability methods that uncover and quantify human-like biases learned by machines. Building these transparency enhancing algorithms involves the use of machine learning, natural language processing, and computer vision to interpret AI's co-evolution with society and gain insights on artificial and natural intelligence.

News

I look forward to teaching Machine Learning in Fall 2021. My paper on AI bias is published in Science. Semantics derived automatically from language corpora contain human-like biases. source code I am the moderator of Computer Science - Computers and Society on arXiv.

Research 2021

Akshat Pandey and Aylin Caliskan Disparate Impact of Artificial Intelligence Bias in Ridehailing Economy's Price Discrimination Algorithms AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AAAI/ACM AIES 2021) Wei Guo and Aylin Caliskan Detecting Emergent Intersectional Biases: Contextualized Word Embeddings Contain a Distribution of Human-like Biases AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AAAI/ACM AIES 2021) Ryan Steed and Aylin Caliskan Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases The 2021 ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT 2021) Ryan Steed and Aylin Caliskan A Set of Distinct Facial Traits Learned by Machines Is Not Predictive of Appearance Bias in the Wild AI and Ethics, 2021 Autumn Toney, Akshat Pandey, Wei Guo, David Broniatowski, and Aylin Caliskan Automatically Characterizing Targeted Information Operations Through Biases Present in Discourse on Twitter 15th IEEE International Conference on Semantic Computing (ICSC 2021)