Summary:
En novembre 2023, le Royaume-Uni a lancé l’Institut de Sécurité de l’IA (AISI) lors du Sommet sur la Sécurité de l’IA pour se concentrer sur la sécurité des systèmes d’IA avancés au bénéfice du public. Cette initiative vise à aborder les risques, à stimuler la recherche en matière de sécurité et à améliorer la collaboration internationale en matière de gouvernance de l’IA. Les efforts clés comprennent le développement d’évaluations pour les risques liés à l’IA, la conduite de recherches de base sur la sécurité et la facilitation des échanges d’informations avec divers acteurs. Les objectifs futurs incluent la mise en place de processus d’évaluation rigoureux pour les systèmes d’IA de prochaine génération et l’expansion des évaluations sur les impacts sociétaux et les risques liés à l’IA autonome.
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The Artificial Intelligence Safety Institute (AISI), launched during the AI Safety Summit in November 2023 by the UK’s Department for Science, Innovation, and Technology (DSIT), represents the world’s first state-supported body prioritizing public safety in advanced AI. Spearheaded by Secretary of State Michelle Donelan and Prime Minister Rishi Sunak, the organization unites experts across multiple fields to understand and govern the risks of advanced AI development. Since its inception, AISI has established itself as a global leader in this nascent sector, building a team with over 165 years of collective experience and forging partnerships with 22 organizations to advance government-led AI evaluations.
### Legal Context and Foundations
AISI’s establishment reflects mounting global concerns around advanced AI, such as those highlighted in the UK’s “National AI Strategy” and the European Union’s proposed Artificial Intelligence Act. These frameworks emphasize the necessity for pre-deployment safety evaluations, ethical oversight, and robust governance. AISI is tasked with conducting rigorous evaluations of AI systems for potentially harmful capabilities, providing the technical underpinnings for the eventual development of enforceable global standards.
One of AISI’s critical contributions includes developing evaluation standards in line with internationally recognized principles, such as the Organisation for Economic Co-operation and Development (OECD) AI Principles, which underscore the importance of safety, accountability, and human-centric AI systems. The organization’s confidentiality policies play a key dual role: protecting sensitive methodologies and meeting legal obligations related to data privacy and intellectual property laws, such as the UK’s Data Protection Act 2018.
### Core Functional Areas
AISI’s work focuses on three key domains: evaluation, foundational research, and information-sharing. For evaluations, AISI applies techniques such as automated capability assessments, red-teaming, and AI agent-specific testing. For instance, using red-teaming methodologies involves experts simulating potential abuses of AI systems, from cybercrime enablers to misuse in creating autonomous, harmful agents. This approach aligns with the precautionary principle, a foundation of European AI safety regulatory draft laws, by proactively addressing risks.
From an ethical standpoint, AISI emphasizes mitigating risks involving misuse and societal harm. For example, scenarios involving autonomous systems replicating themselves online echo concerns raised in Isaac Asimov’s “Three Laws of Robotics”—namely, the inability to ensure machines prioritize human welfare. AISI’s focus on grounding societal evaluations in realistic user behaviors also serves to publicly legitimize AI technologies, ensuring they do not inadvertently reinforce inequality or undermine trust.
### Industry Implications and Collaboration
The AI industry benefits substantially from AISI’s role as an independent evaluator. By setting standards and conducting impartial evaluations, AISI addresses public concerns over the misuse of AI and thereby fosters trust. This is critical in industries dealing with sensitive data, such as health care and national security. For instance, by identifying potential misuse of AI systems for cyber-offense capabilities, AISI assists organizations in deploying safeguards that can preempt large-scale harm.
AISI’s collaborative model, which includes leaders in advanced AI like OpenAI and DeepMind, encourages industry-government partnerships crucial for scalable safety mechanisms. The organization’s emphasis on societal considerations, such as AI’s impact on labor markets, ensures a balanced approach that does not stymie innovation.
Additionally, AISI’s role in bringing together multiple stakeholders—policymakers, academics, civil society, and international actors—enhances global cooperation on AI governance, an area highlighted as essential during the Bletchley Declaration of the AI Safety Summit. The emphasis on global information-sharing channels ensures that safety practices and breakthroughs are distributed equitably, minimizing risks from geopolitical AI development disparities.
### Conclusion
As AI systems grow increasingly autonomous and influential, the AISI’s proactive evaluations and research represent a critical safety net. While challenges persist, such as insufficient capacity to evaluate all AI models and the difficulty in forecasting emergent risks, the establishment of AISI demonstrates a significant step toward transparent, ethical, and globally coordinated AI safety efforts. By attacking foundational safety issues and establishing pivotal governance frameworks, AISI is effectively laying the groundwork for a safer, more accountable AI future.