Privacy explanations – A means to end-user trust

Author:

Brunotte WasjaORCID,Specht Alexander,Chazette Larissa,Schneider Kurt

Publisher

Elsevier BV

Subject

Hardware and Architecture,Information Systems,Software

Reference123 articles.

1. Uneasy Access: Privacy for Women in a Free Society;Allen,1988

2. To trust or not to trust an explanation: using LEAF to evaluate local linear XAI methods;Amparore;PeerJ Comput. Sci.,2021

3. How internet users’ privacy concerns have evolved since 2002;Anton;IEEE Secur. Priv.,2010

4. Challenges in applying explainability methods to improve the fairness of NLP models;Balkir,2022

5. Explicating the privacy paradox: A qualitative inquiry of online shopping consumers;Bandara;J. Retail. Consum. Serv.,2020

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1. Attribute-Centric and Synthetic Data Based Privacy Preserving Methods: A Systematic Review;Journal of Cybersecurity and Privacy;2023-09-11

2. Explanations on Demand - a Technique for Eliciting the Actual Need for Explanations;2023 IEEE 31st International Requirements Engineering Conference Workshops (REW);2023-09

3. Designing End-User Personas for Explainability Requirements Using Mixed Methods Research;2023 IEEE 31st International Requirements Engineering Conference Workshops (REW);2023-09

4. A Means to what End? Evaluating the Explainability of Software Systems using Goal-Oriented Heuristics;Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering;2023-06-14

5. Linking Personality and Trust in Intelligent Virtual Assistants;Multimodal Technologies and Interaction;2023-05-25

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