Algorithmic Auditing, Computational Social Science
Aniko has been assistant professor at the Vienna University of Economics and Business, and faculty member of the Complexity Science Hub since September 2018. She received her PhD from the College of Computer & Information Science at Northeastern University, where she was part of the Lazer Lab and the Algorithmic Auditing Group.
Aniko’s main interest lies in computational social sciences. She is focusing on the co-evolution of online systems and their users. Broadly, her work investigates a variety of content serving websites such as search engines, online stores, job search sites, or freelance marketplaces. In this quickly changing online ecosystem, companies track every move of their users and feed the collected data into Big Data algorithms in order to match them with the most interesting, most relevant content. Since these algorithms learn on human data they are likely to pick up on social biases and unintentionally reinforce them. In her PhD work, Aniko created a methodology called “algorithmic auditing”, which tries to uncover the potential negative impacts of large online systems. Examples of such audits include examining the filter bubble effect on GoogleSearch, online price discrimination or detecting inequalities in online labor markets.