Related papers: The Role of AI Safety Institutes in Contributing to International Standards for Frontier AI Safety

The Role of AI Safety Institutes in Contributing to International Standards for Frontier AI Safety

URL: http://arxiv.org/abs/2409.11314v1
Date: Tue, 17 Sep 2024 16:12:54 GMT
Title: The Role of AI Safety Institutes in Contributing to International Standards for Frontier AI Safety
Authors: Kristina Fort,
Abstract summary: We argue that the AI Safety Institutes (AISIs) are well-positioned to contribute to the international standard-setting processes for AI safety. We propose and evaluate three models for involvement: Seoul Declaration Signatories, US (and other Seoul Declaration Signatories) and China, and Globally Inclusive.
Score: 0.0
License: http://creativecommons.org/licenses/by/4.0/
Abstract: International standards are crucial for ensuring that frontier AI systems are developed and deployed safely around the world. Since the AI Safety Institutes (AISIs) possess in-house technical expertise, mandate for international engagement, and convening power in the national AI ecosystem while being a government institution, we argue that they are particularly well-positioned to contribute to the international standard-setting processes for AI safety. In this paper, we propose and evaluate three models for AISI involvement: 1. Seoul Declaration Signatories, 2. US (and other Seoul Declaration Signatories) and China, and 3. Globally Inclusive. Leveraging their diverse strengths, these models are not mutually exclusive. Rather, they offer a multi-track system solution in which the central role of AISIs guarantees coherence among the different tracks and consistency in their AI safety focus.

Related papers

Standardization Trends on Safety and Trustworthiness Technology for Advanced AI [0.0]
Recent AI technologies based on large language models and foundation models are approaching or surpassing artificial general intelligence. These advancements have raised concerns regarding the safety and trustworthiness of advanced AI. Efforts are being expended to develop internationally agreed-upon standards to ensure the safety and reliability of AI.
arXiv Detail & Related papers (2024-10-29T15:50:24Z)
Engineering Trustworthy AI: A Developer Guide for Empirical Risk Minimization [53.80919781981027]
Key requirements for trustworthy AI can be translated into design choices for the components of empirical risk minimization. We hope to provide actionable guidance for building AI systems that meet emerging standards for trustworthiness of AI.
arXiv Detail & Related papers (2024-10-25T07:53:32Z)
The potential functions of an international institution for AI safety. Insights from adjacent policy areas and recent trends [0.0]
The OECD, the G7, the G20, UNESCO, and the Council of Europe have already started developing frameworks for ethical and responsible AI governance. This chapter reflects on what functions an international AI safety institute could perform.
arXiv Detail & Related papers (2024-08-31T10:04:53Z)
Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress? [59.96471873997733]
We propose an empirical foundation for developing more meaningful safety metrics and define AI safety in a machine learning research context. We aim to provide a more rigorous framework for AI safety research, advancing the science of safety evaluations and clarifying the path towards measurable progress.
arXiv Detail & Related papers (2024-07-31T17:59:24Z)
AI Risk Management Should Incorporate Both Safety and Security [185.68738503122114]
We argue that stakeholders in AI risk management should be aware of the nuances, synergies, and interplay between safety and security. We introduce a unified reference framework to clarify the differences and interplay between AI safety and AI security.
arXiv Detail & Related papers (2024-05-29T21:00:47Z)
Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems [88.80306881112313]
We will introduce and define a family of approaches to AI safety, which we will refer to as guaranteed safe (GS) AI. The core feature of these approaches is that they aim to produce AI systems which are equipped with high-assurance quantitative safety guarantees. We outline a number of approaches for creating each of these three core components, describe the main technical challenges, and suggest a number of potential solutions to them.
arXiv Detail & Related papers (2024-05-10T17:38:32Z)
Taking control: Policies to address extinction risks from AI [0.0]
We argue that voluntary commitments from AI companies would be an inappropriate and insufficient response. We describe three policy proposals that would meaningfully address the threats from advanced AI.
arXiv Detail & Related papers (2023-10-31T15:53:14Z)
International Institutions for Advanced AI [47.449762587672986]
International institutions may have an important role to play in ensuring advanced AI systems benefit humanity. This paper identifies a set of governance functions that could be performed at an international level to address these challenges. It groups these functions into four institutional models that exhibit internal synergies and have precedents in existing organizations.
arXiv Detail & Related papers (2023-07-10T16:55:55Z)
Artificial Intelligence Security Competition (AISC) [52.20676747225118]
The Artificial Intelligence Security Competition (AISC) was organized by the Zhongguancun Laboratory, China Industrial Control Systems Cyber Emergency Response Team, Institute for Artificial Intelligence, Tsinghua University, and RealAI. The competition consists of three tracks, including Deepfake Security Competition, Autonomous Driving Security Competition, and Face Recognition Security Competition. This report will introduce the competition rules of these three tracks and the solutions of top-ranking teams in each track.
arXiv Detail & Related papers (2022-12-07T02:45:27Z)

This list is automatically generated from the titles and abstracts of the papers in this site.