Machine Unlearning: its nature, scope, and importance for a "delete
  culture"
Luciano Floridi
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: deleting, to make information unavailable; and
blocking, to make it inaccessible. The article argues that both strategies have
significant implications, particularly for machine learning (ML) models where
information is not easily made unavailable. However, the emerging research area
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' completely specific information. If successful, MU could
provide a feasible means to manage the overabundance of information and ensure
a better protection of privacy and IP. However, potential ethical risks, such
as misuse, overuse, and underuse of MU, should be systematically studied to
devise appropriate policies.