A Survey of Machine Unlearning
Griffith University · VinUniversity · +3 more institutions
Abstract
Today, computer systems hold large amounts of personal data. Yet while such an abundance of data allows breakthroughs in AI, and especially machine learning, its existence can be a threat to user privacy, and it can weaken the bonds of trust between humans and AI. Recent regulations now require that, on request, private information about a user must be removed both from computer systems and from machine learning models—this legislation is more colloquially called “the right to be forgotten.” While removing data from back-end databases should be straightforward, it is not sufficient in the AI context as machine learning models often “remember” the old data. Contemporary adversarial attacks on trained models…
Citation impact
- FWCI
- 102.63
- Percentile
- 100%
- References
- 117
Authors
7Topics & keywords
- Computer science
- Artificial intelligence
- Data science