Hack the Hat is an interactive experience highlighting the frustrations of AI-driven recruitment. You will mentor Merlin Kepler, a wizard graduate, by modifying a CV to pass the test of a magical screening hat. This gamified project explores hidden biases in AI systems, encouraging reflection on the impact of automated decision-making in job recruitment.
In today’s digital age, AI is being used increasingly in recruitment, often leaving job applicants in the dark about why they were rejected. This artistic project, Hack the Hat, aims to shed light on the black box of these AI-driven decisions.
In Hack the Hat, the recruitment process is controlled by a magical AI screening hat. Players guide Merlin Kepler, who faces repeated rejections, by modifying his CV to see how changes in gender, age, experience and skills affect the AI’s decisions. The goal is to help Merlin pass the screening process and uncover the AI’s hidden biases and criteria. You are joined by two other contenders competing for the highest score. However, the real challenge is to see if collaboration, rather than competition, leads to better outcomes for everyone. The overall aim is to invite visitors to explore the biases in AI-driven recruitment and reflect on the broader implications of automated decision-making.
Hack the Hat, photo: Oleg Lesota
Hack the Hat, photo: Oleg Lesota
Bios
-
Anna Hausberger
AT
Anna Hausberger is a Master Student and student researcher at Johannes Kepler University Linz specializing in context-based recommender systems, multimodal data, and AI explainability.
-
Deepak Kumar
IN
Deepak Kumar is a PhD Student at Johannes Kepler University Linz. He focuses on fairness in recommender systems, particularly within the recruitment domain, and on developing parameter-efficient bias mitigation techniques.
-
Dominik Baumann
AT
Dominik Baumann is a mathematics master student at JKU. He is passionate about developing games in his free time.
-
Gerald Gruber
AT
Gerald Gruber is a student at the University of Applied Sciences Upper Austria, Campus Hagenberg, studying Digital Art. He is an artist, animator, and designer for games and shorts, and passionate about bringing stories and interactive experiences to life.
-
Ghazal Hosseini
IR
Ghazal Hosseini is a new media artist and engineer studying in the Interface Cultures master program at the University of Arts Linz. Her artistic work explores interactive storytelling, affective computing, machine perception, and immersive technologies.
-
Gustavo Escobedo
PE
Gustavo Escobedo is a PhD student at Johannes Kepler University Linz with a primary focus on Recommender Systems, Currently, he is working on Debiasing and Privacy-enhancing methods.
-
Markus Schedl
AT
Markus Schedl is a full professor at JKU and LIT, leading the Multimedia Mining and Search (MMS) and the Human-centered AI (HCAI) groups. His research interests include recommender systems, information retrieval, trustworthy AI, and multimedia.
-
Michael Preisach
AT
Michael Preisach is a system administrator and provides technical support in this project. He cares about the compute hardware, installs the software and configures the network. Besides that, he provides tools for integrating and deploying the software parts and makes use of a soldering iron when needed.
-
Parisa Ayati
IR
Parisa Ayati is a multidisciplinary artist from Iran who currently resides in Vienna. As a professional artist and designer, she is deeply passionate about movement, whether it takes the form of motion graphics or interactive installations.
-
Stefan Brandl
AT
Stefan Brandl is a student researcher at JKU, specializing in debiasing recommendation systems within the music domain. His work focuses on developing algorithms and methodologies to reduce bias in music recommendations, ensuring a more diverse and fair experience for users.
Credits
This project is supported by the State of Upper Austria.
