Summary of Ids For Ai Systems, by Alan Chan et al.
IDs for AI Systems
by Alan Chan, Noam Kolt, Peter Wills, Usman Anwar, Christian Schroeder de Witt, Nitarshan Rajkumar, Lewis Hammond, David Krueger, Lennart Heim, Markus Anderljung
First submitted to arxiv on: 17 Jun 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary As AI systems increasingly permeate our lives, it’s crucial to ensure that users can verify the safety certifications of these systems and access information about them. The proposed framework assigns unique identifiers (IDs) to AI system instances, such as chat sessions with Claude 3, making associated information accessible to parties seeking interaction. This framework characterizes IDs for AI systems, provides concrete examples, argues demand from key actors, analyzes incentives, explores implementation for deployers, and highlights limitations and risks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary AI is becoming more common in our daily lives. To make sure we can trust these systems, we need a way to identify them and get information about them. The idea is to give each AI system instance its own unique identifier (ID). This ID would provide access to important details about the system, making it easier for people to interact with it safely. |
Keywords
» Artificial intelligence » Claude
