Taxonomy and Future Directions in AI Safety for Large Language Models
A recent article on arXiv introduces an innovative framework aimed at comprehending AI Safety, outlining its features through three lenses: Trustworthy AI, Responsible AI, and Safe AI. This research offers a thorough examination of existing studies and developments, emphasizing significant challenges and strategies for mitigation, particularly regarding Large Language Models (LLMs). The swift rise of Generative AI has expanded the scope of AI Safety to encompass issues related to public safety and national security. This framework is designed to facilitate the secure implementation and utilization of AI technologies.
Key facts
- Paper proposes a novel architectural framework for AI Safety.
- Framework defines AI Safety from three perspectives: Trustworthy AI, Responsible AI, and Safe AI.
- Review covers current research and advancements in AI safety.
- Focuses on Large Language Models (LLMs) as state-of-the-art examples.
- Highlights key challenges and mitigation approaches.
- Rapid proliferation of Generative AI has broadened AI Safety scope.
- AI Safety now addresses public safety and national security.
- Paper is available on arXiv with ID 2408.12935.
Entities
Institutions
- arXiv