Lobo, Jesus L.Gil-Lopez, SergioDel Ser, Javier2023Lobo , J L , Gil-Lopez , S & Del Ser , J 2023 , The Right to Be Forgotten in Artificial Intelligence : Issues, Approaches, Limitations and Challenges . in Proceedings - 2023 IEEE Conference on Artificial Intelligence, CAI 2023 . Proceedings - 2023 IEEE Conference on Artificial Intelligence, CAI 2023 , Institute of Electrical and Electronics Engineers Inc. , pp. 179-180 , 2023 IEEE Conference on Artificial Intelligence, CAI 2023 , Santa Clara , United States , 5/06/23 . https://doi.org/10.1109/CAI54212.2023.00085conference9798350339840Publisher Copyright: © 2023 IEEE.The Right To Be Forgotten is widely conceived as a fundamental principle of the human being. It has become a subject of capital importance in domains where sensitive information is collected from individuals, requiring the provision of monitoring, governance and audit tools to control where such information is used. Artificial Intelligence models are not an exception to this statement: since they are learned from data, this fundamental right should allow individuals to have their personal information erased from AI-based systems. However, the application of this right is not straightforward: what does erasing mean in the context of a model learned from data? Is it just a matter of removing the concerned data and retraining the models? This manuscript provides a brief overview of these and more issues, proposing a desiderata for technical advances noted in this direction, and outlining research directions for prospective studies.2enginfo:eu-repo/semantics/restrictedAccessconference output10.1109/CAI54212.2023.00085AI ethicsdata governancedata privacyright to be forgottentrustworthy AIComputer Science ApplicationsComputer Vision and Pattern RecognitionModeling and SimulationArtificial IntelligenceSDG 16 - Peace, Justice and Strong Institutionshttp://www.scopus.com/inward/record.url?scp=85168687622&partnerID=8YFLogxK