English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The advent of Generative AI has marked a significant milestone in artificialintelligence, demonstrating remarkable capabilities in generating realisticimages, texts, and data patterns. However, these advancements come withheightened concerns over data privacy and copyright infringement, primarily dueto the reliance on vast datasets for model training. Traditional approacheslike differential privacy, machine unlearning, and data poisoning only offerfragmented solutions to these complex issues. Our paper delves into themultifaceted challenges of privacy and copyright protection within the datalifecycle. We advocate for integrated approaches that combines technicalinnovation with ethical foresight, holistically addressing these concerns byinvestigating and devising solutions that are informed by the lifecycleperspective. This work aims to catalyze a broader discussion and inspireconcerted efforts towards data privacy and copyright integrity in GenerativeAI.

Navigating Privacy and Copyright Challenges Across the Data Lifecycle of Generative AI