Preprints

  • Aylin Caliskan
    Bias in Natural Language Processing
    Policy Brief, 2020
  • Autumn Toney and Aylin Caliskan
    ValNorm Quantifies Semantics to Reveal Consistent Valence Biases Across Languages and Over Centuries
    Manuscript, 2020
  • Aylin Caliskan and Molly Lewis
    Social biases in word embeddings and their relation to human cognition
    Book Chapter Preprint, 2020
  • Peer-reviewed Publications

  • 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)
  • Aylin Caliskan and Begum Kaplan
    If I Tap It, Will They Come? An Introductory Analysis of Fairness in a Large-Scale Ride Hailing Dataset
    Academy of Marketing Science 44th Annual Conference (AMS 2020)
  • Edwin Dauber, Aylin Caliskan, Richard Harang, Gregory Shearer, Michael Weisman, Frederica Nelson, and Rachel Greenstadt.
    Git Blame Who?: Stylistic Authorship Attribution of Small, Incomplete Source Code Fragments
    The 19th Privacy Enhancing Technologies Symposium (PETS 2019)
  • Aylin Caliskan, Fabian Yamaguchi, Edwin Dauber, Richard Harang, Konrad Rieck, Rachel Greenstadt, and Arvind Narayanan.
    When Coding Style Survives Compilation: De-anonymizing Programmers from Executable Binaries
    The Network and Distributed System Security Symposium (NDSS 2018) - Source code
  • Aylin Caliskan, Joanna J. Bryson, and Arvind Narayanan.
    Semantics derived automatically from language corpora contain human-like biases
    Science 2017 - Source code and data
  • Aylin Caliskan, Joanna J. Bryson, and Arvind Narayanan.
    A Story of Discrimination and Unfairness
    9th Hot Topics in Privacy Enhancing Technologies (HotPETS 2016)
    • Best Talk Award
  • Aylin Caliskan-Islam, Richard Harang, Andrew Liu, Arvind Narayanan, Clare Voss, Fabian Yamaguchi, and Rachel Greenstadt.
    De-anonymizing Programmers via Code Stylometry
    24th Usenix Security Symposium (Usenix 2015) - Source code
  • Aylin Caliskan-Islam, Jonathan Walsh, and Rachel Greenstadt.
    Privacy Detective: Detecting Private Information and Collective Privacy Behavior in a Large Social Network
    Workshop on Privacy in the Electronic Society (WPES 2014)
  • Sadia Afroz, Aylin Caliskan-Islam, Ariel Stolerman, Rachel Greenstadt, and Damon McCoy.
    Doppelgänger Finder: Taking Stylometry To The Underground
    35th IEEE Symposium on Security Privacy (Oakland SP 2014)
  • Alex Kantchelian, Sadia Afroz, Ling Huang, Aylin Caliskan Islam, Brad Miller, Michael Carl Tschantz, Rachel Greenstadt, Anthony Joseph and J.D. Tygar.
    Approaches to Adversarial Drift
    6th ACM Workshop on Artificial Intelligence and Security (AISec 2013)
  • Sadia Afroz, Aylin Caliskan Islam, Jordan Santell, Aaron Chapin, Rachel Greenstadt.
    How Privacy Flaws Affect Consumer Perception
    The 3rd workshop on Socio-Technical Aspects in Security and Trust (STAST 2013)
  • Ariel Stolerman, Aylin Caliskan and Rachel Greenstadt.
    From Language to Family and Back: Native Language and Language Family Identification from English Text
    The 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop, NAACL HLT SRW 2013
  • Andrew McDonald, Sadia Afroz, Aylin Caliskan, Ariel Stolerman and Rachel Greenstadt.
    Use Fewer Instances of the Letter "i": Toward Writing Style Anonymization
    The 12th Privacy Enhancing Technologies Symposium (PETS 2012)
    • Andreas Pfitzmann PETS Best Student Paper Award 2012.
  • Aylin Caliskan and Rachel Greenstadt.
    Translate once, translate twice, translate thrice and attribute: Identifying authors and machine translation tools in translated text
    6th IEEE International Conference on Semantic Computing (ICSC 2012)
  • Other Publications

  • David Broniatowski, Aylin Caliskan, Valerie Reyna, and Reva Schwartz
    Comments in response to the National Institute of Standards and Technology Request for Information on Developing a Federal AI Standards Engagement Plan [Docket Number: [190312229–9229–01]]

    National Institute of Standards and Technology (NIST) White Paper, June 2019.
  • Aylin Caliskan-Islam.
    How do we decide how much to reveal? (Hint: Our privacy behavior might be socially constructed.)

    Special Issue on Security, Privacy, and Human Behavior, ACM Computer Society, February 2015
  • Technical Report: Arunkumar Byravan, Aylin Caliskan, Jonas Cleveland, Daniel Gilles, Jaimeen Kapadia, Theparit Peerasathien, Bharath Sankaran, Alex Tozzo.
    ENVOY: Exploration and Navigation Vehicle for geolOgY
    University of Pennsylvania's Entry in NASA/NIA RASC-AL, 2011