11 citations · 38 across the 21 of their papers we have counts for
7 papers · 1 filter
Patient-Centred Explainability in IVF Outcome Prediction
Adarsa Sivaprasad, Ehud Reiter, David McLernon +3
This paper evaluates the user interface of an in vitro fertility (IVF) outcome prediction tool, focussing on its understandability for patients or potential patients. We analyse fo…
With Friends Like These, Who Needs Explanations? Evaluating User Understanding of Group Recommendations
Cedric Waterschoot, Raciel Yera Toledo, Nava Tintarev +1
Group Recommender Systems (GRS) employing social choice-based aggregation strategies have previously been explored in terms of perceived consensus, fairness, and satisfaction. At t…
Bridging the Transparency Gap: Exploring Multi-Stakeholder Preferences for Targeted Advertisement Explanations
Dina Zilbershtein, Francesco Barile, Daan Odijk +1
Limited transparency in targeted advertising on online content delivery platforms can breed mistrust for both viewers (of the content and ads) and advertisers. This user study (n=8…
Creating Healthy Friction: Determining Stakeholder Requirements of Job Recommendation Explanations
Roan Schellingerhout, Francesco Barile, Nava Tintarev
The increased use of information retrieval in recruitment, primarily through job recommender systems (JRSs), can have a large impact on job seekers, recruiters, and companies. As a…
A Co-design Study for Multi-Stakeholder Job Recommender System Explanations
Roan Schellingerhout, Francesco Barile, Nava Tintarev
Recent legislation proposals have significantly increased the demand for eXplainable Artificial Intelligence (XAI) in many businesses, especially in so-called `high-risk' domains,…
Disparate Impact Diminishes Consumer Trust Even for Advantaged Users
Tim Draws, Zoltán Szlávik, Benjamin Timmermans +3
Systems aiming to aid consumers in their decision-making (e.g., by implementing persuasive techniques) are more likely to be effective when consumers trust them. However, recent re…