-
Chapter and Conference Paper
Results of the Workshop on Algorithmic Affordances in Recommender Interfaces
Algorithmic affordances are defined as user interaction mechanisms that allow users tangible control over AI algorithms, such as recommender systems. Designing such algorithmic affordances, including assessing th...
-
Chapter and Conference Paper
Assessing the Utility of an Interaction Qualities Framework in Systematizing the Evaluation of User Control
The user’s experience with a recommender system is significantly shaped by the dynamics of user-algorithm interactions. These interactions are often evaluated using interaction qualities, such as controllability,...
-
Chapter and Conference Paper
Design Ideas for Recommender Systems in Flexible Education: How Algorithmic Affordances May Address Ethical Concerns
In flexible education, recommender systems that support course selection, are considered a viable means to help students in making informed course selections, especially where curricula offer greater flexibili...
-
Chapter and Conference Paper
Recognizing the Algorithmic Literacy of Users in XAI - An Example-Based Approach
Recommender systems are widely used in today’s society, but many of them do not meet users’ needs and therefore fail to reach their full potential. Without careful consideration, such systems can interfere wit...
-
Chapter and Conference Paper
Why Designers Must Contribute to Responsible AI
In this paper, we argue that the creation of Responsible AI over the past four decades has predominantly relied on two approaches: contextual and technical. While both are indispensable, we contend that a thir...
-
Chapter and Conference Paper
Exploring Categorizations of Algorithmic Affordances in Graphical User Interfaces of Recommender Systems
This exploratory study investigates the rationale behind categorizing algorithmic controls, or algorithmic affordances, in the graphical user interfaces (GUIs) of recommender systems. Seven professionals from ind...
-
Chapter and Conference Paper
Overcoming Privacy-Related Challenges for Game Developers
Design and development practitioners such as those in game development often have difficulty comprehending and adhering to the European General Data Protection Regulation (GDPR), especially when designing in a...
-
Chapter and Conference Paper
Algorithmic Affordances in Recommender Interfaces
Recommenders play a significant role in our daily lives, making decisions for users on a regular basis. Their widespread adoption necessitates a thorough examination of how users interact with recommenders and...
-
Chapter and Conference Paper
Towards a Practice-Led Research Agenda for User Interface Design of Recommender Systems
The design of recommender systems’ graphical user interfaces (GUIs) is critical for a user's experience with these systems. However, most research into recommenders focuses on algorithms, overlooking the desig...
