Machine Unlearning: Its nature, scope, and importance for a “delete culture”

Abstract

The article explores the cultural shift from recording to deleting information in the digital age and its implications on privacy, intellectual property (IP), and Large Language Models like ChatGPT. It begins by defining a 'delete culture' where information, in principle legal, is made unavailable or inaccessible because unacceptable or undesirable, especially but not only due to its potential to infringe on privacy or IP. Then it focuses on two strategies in this context: deletion, rendering the information unavailable; and blocking, making it inaccessible. The article argues that both strategies have significant implications, particularly in machine learning (ML) models like ChatGPT, where information is not easily made unavailable. However, the emerging concept of Machine Unlearning (MU) is highlighted as a potential solution. MU, still in its infancy, seeks to remove specific data points from ML models, effectively making them 'forget' specific information. If successful, MU could provide a feasible means to manage the overabundance of information and ensure rights such as privacy and IP in a delete culture. However, potential ethical risks, such as misuse, overuse, and underuse of MU, should be systematically studied to devise appropriate policies.

Keywords: ChatGPT, Delete Culture, Machine Learning, Machine Unlearning, Right to be Forgotten