@inproceedings{fidilio2024opportunities,
  abstract  = {The increasing use of artificial intelligence systems (especially those based on black-box algorithms) in decision models that affect humans is leading to an increase in demand for explainable AI (XAI) and models aligned with human values and norms. Recently, symbolic reasoning approaches, such as Answer Set Programming (ASP), have re-emerged as an alternative solution to create transparent and interpretable models more easily auditable. However, this explainability may expose private information (with ethical and legal implications). Although it is possible to manipulate the justifications (to hide sensitive information), ASP forgetting techniques are gaining relevance because they allow to remove such information from the models as well, thus allowing to audit them without compromising the users' privacy and comply with GDPR data minimization principle. On the other hand, black box models cannot provide such explanations, so to ensure privacy preservation a naive approach is to learn Machine Learning (ML) models using a dataset from which sensitive attributes are removed, but this solution may affect accuracy. In this paper we present Privacy-ML, a complex scheme that is trained with sensitive information but then does not require such information when performing classification (improving the accuracy of naive approaches). Additionally, we have identified that a Privacy-ML based on Inductive Logic Programming can also be used by a malicious agent in combination with forgetting to obfuscate their deceptive profiling practices in such a way that it cannot be directly detected by someone reading the explanations it produces or by auditing the model.},
  address   = {Cham},
  author    = {Arias, Joaqu{\'i}n
               and Degli-Esposti, Sara
               and Hern{\'a}ndez-P{\'e}rez, Jose Walter
               and Fidilio-Allende, Luciana
               and Ossowski, Sascha},
  booktitle = {Value Engineering in Artificial Intelligence},
  doi       = {10.1007/978-3-031-85463-7_14},
  editor    = {Osman, Nardine
               and Steels, Luc},
  isbn      = {978-3-031-85463-7},
  pages     = {225--239},
  publisher = {Springer Nature Switzerland},
  title     = {Opportunities and Challenges of the Use of Forgetting in Symbolic XAI},
  year      = {2025}
}