Nina Grgić-Hlača

About

Welcome!

I am a PhD student at the Max Planck Institute for Software Systems and Max Planck Institute for Research on Collective Goods. I am co-advised by Krishna P. Gummadi and Christoph Engel.

My research interests include algorithmic fairness, human-centric machine learning and social computing.

I have an MA in Philosophy and Information Sciences from the Faculty of Humanities and Social Sciences, University of Zagreb, Croatia.

Publications

• Taking Advice from (Dis)Similar Machines: The Impact of Human-Machine Similarity on Machine-Assisted Decision-Making
  Nina Grgić-Hlača, Claude Castelluccia and Krishina P. Gummadi
  HCOMP, Online Virtual Conference, November 2022.
  [arXiv]


• Dimensions of Diversity in Human Perceptions of Algorithmic Fairness
  Nina Grgić-Hlača, Gabriel Lima, Adrian Weller and Elissa M. Redmiles
  EAAMO, Arlington, Virginia, October 2022.
  [arXiv]


• The Conflict Between Explainable and Accountable Decision-Making Algorithms
  Gabriel Lima, Nina Grgić-Hlača, Jin Keun Jeong and Meeyoung Cha
  FAccT, Seoul, South Korea, June 2022.
  [arXiv]


• ``Look! It's a Computer Program! It's an Algorithm! It's AI!'': Does Terminology Affect Human Perceptions and Evaluations of Algorithmic Decision-Making Systems?
  Markus Langer, Tim Hunsicker, Tina Feldkamp, Cornelius J König and and Nina Grgić-Hlača
  CHI, New Orleans, Louisiana, May 2022.
  [arXiv]


• Machine Advice with a Warning about Machine Limitations: Experimentally Testing the Solution Mandated by the Wisconsin Supreme Court
  Christoph Engel, Nina Grgić-Hlača
  Journal of Legal Analysis, 2021.
  [Publisher's version]


• Human Perceptions on Moral Responsibility of AI: A Case Study in AI-Assisted Bail Decision-Making
  Gabriel Lima, Nina Grgić-Hlača, and Meeyoung Cha
  CHI, Virtual, May 2021.
  [arXiv]


• Human Decision Making with Machine Assistance: An Experiment on Bailing and Jailing
  Nina Grgić-Hlača, Christoph Engel and Krishna P. Gummadi
  CSCW, Austin, Texas, November 2019.
  [PDF]


• A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices
  Till Speicher, Hoda Heidari, Nina Grgić-Hlača, Krishna P. Gummadi, Adish Singla, Adrian Weller, Muhammad Bilal Zafar
  KDD, London, United Kingdom, August 2018.
  [PDF]


• Human Perceptions of Fairness in Algorithmic Decision Making: A Case Study of Criminal Risk Prediction
  Nina Grgić-Hlača, Elissa M. Redmiles, Krishna P. Gummadi and Adrian Weller
  The Web Conf, Lyon, France, April 2018.
  [PDF] [code & data]


• Beyond Distributive Fairness in Algorithmic Decision Making: Feature Selection for Procedurally Fair Learning
  Nina Grgić-Hlača, Muhammad Bilal Zafar, Krishna P. Gummadi and Adrian Weller
  AAAI, New Orleans, Louisiana, February 2018.
  [PDF] [code & data]


• On Fairness, Diversity and Randomness in Algorithmic Decision Making
  Nina Grgić-Hlača, Muhammad Bilal Zafar, Krishna P. Gummadi and Adrian Weller
  FAT/ML Workshop @ KDD, Halifax, Canada, August 2017.
  [arXiv]


• The Case for Process Fairness in Learning: Feature Selection for Fair Decision Making
  Nina Grgić-Hlača, Muhammad Bilal Zafar, Krishna P. Gummadi and Adrian Weller
  Symposium on Machine Learning and the Law @ NeurIPS, Barcelona, Spain, December 2016.
  Notable Paper Award
  [PDF]