Governments should fund open-source AI safety tools and red-teaming infrastructure as public goods.

public-interest-ai research-policy ai-governance ai-policy ai-regulation gov ai-safety open-source policy

Arguments for

Access beyond large firms

These quotes argue that safety tools should not remain inside the largest companies. Open, auditable, shared tools are presented as a way to let organizations of every size use safeguards that are transparent, verifiable, and available to any provider.

Safety tools cannot remain exclusive to the largest companies; they must be open, auditable, and collectively improved—serving as a common good for the benefit of society. This is how we will build trustworthy AI that truly protects our children, our teenagers, and all our fellow…

Anne Le Hénanff · Jun 2, 2026 · full quote
By building safety tools in the open, this partnership will help organizations of every size adopt AI more responsibly. It strengthens trust, supports Canadian leadership in safe AI, and helps ensure the safeguards people rely on are transparent, verifiable, and shared.

Evan Solomon · Jun 2, 2026 · full quote
AI safety should not be left to a handful of large companies making trade-offs behind closed doors. Partnering with ROOST lets our researchers work on harms with real public stakes, and commits us to putting what we build where any provider can use it.

Valérie Pisano · Jun 2, 2026 · full quote
The UK, through AISI, has developed the world’s most widely used government-backed evaluation tools. Inspect, InspectSandbox, InspectCyber, and our latest release, ControlArena, are now being used by governments, companies, and academics around the world. These open tools lower t…

Kanishka Narayan · Feb 10, 2026 · full quote

Evaluation as safety capacity

A second argument treats the ability to evaluate, govern, and red-team AI as part of safety itself. On this view, governments should fund third-party assessment, independent evaluations, secure testing environments, adversarial testing, forensic capabilities, and transparent evaluations so public institutions can oversee emerging risks.

The Commission will help establish an EU evaluation capacity to strengthen third-party assessment of AI capabilities and risks globally, supporting the regulatory function of the AI Office.

European Commission · Jul 7, 2026 · full quote
We must therefore treat the capacity to evaluate and govern AI as an integral part to safety itself, supported through shared tools, pooled expertise, and cooperation across regions.

Government of Pakistan · Jul 7, 2026 · full quote
There is hereby created an AI Safety Research Fund, to be administered by the BAIS and funded through annual General Appropriations. The fund shall support: (a) Independent safety and bias evaluations; (b) Grants for red-teaming and adversarial testing of AI systems; (c) Academic…

House of Representatives of the Philippines · Feb 4, 2026 · full quote
Build government AI–cyber capacity and translation infrastructure. Strengthen government capacity to evaluate, oversee, and respond to AI-enabled cyber risks by investing in technical staffing, institutional authority, and translation functions [...] expanding access to compute, …

Federation of American Scientists · Jan 2026 · full quote
To avoid losing visibility into cutting-edge AI cyberattack capabilities exactly when it matters most, I argue governments should fund independent threat-intelligence collection and sharing, develop AI-specific forensic capabilities, build the capacity to evaluate models on real-…

Jan Wehner · Jun 29, 2026 · full quote
Canada will invest $50 million to expand the capabilities of the Canadian AI Safety Institute to track emerging AI risks, advance technical research, and to conduct transparent evaluations of AI models.

Innovation, Science and Economic Development Canada · Jun 8, 2026 · full quote

Shared infrastructure and methods

Proponents say open-sourcing frameworks, methods, and supporting infrastructure creates a common technical foundation for collaboration. Shared platforms are described as helping researchers, labs, governments, and evaluators avoid starting from zero while improving transparency, reproducibility, and cross-border information-sharing.

By open-sourcing not only Inspect, but also our methods and infrastructure where we can, we hope to help researchers, organisations, and other evaluators stand up rigorous evaluation capability without starting from zero.

AI Security Institute (AISI) · Jun 18, 2026 · full quote
I created Inspect because I wanted to provide a strong technical foundation for governments, researchers, and labs to collaborate on testing and understanding frontier models. I am thrilled to have seen so many organisations adopt it, as well as to have accepted contributions fro…

JJ Allaire · Jun 18, 2026 · full quote
In collaboration with the Vector Institute, we created new extensions to Inspect AI—the leading framework for AI safety evaluation—that make testing more transparent, reproducible and easier to share across teams.

National Research Council Canada · May 21, 2026 · full quote
The government industrial research organizations, they could share their current evaluation tools or methods, evidence through the common platforms.

Xinchen Hua Lu · Jul 7, 2026 · full quote
The Canadian and Korean AI Safety Institutes have signed a memorandum of understanding to strengthen international cooperation on artificial intelligence safety. Through this collaboration, the institutes will exchange information on AI technologies, risks, methodologies, tools a…

Government of Canada · Jul 8, 2026 · full quote
Publicly available evaluation frameworks provide an important foundation [...] CAISI has open-sourced our improvements [...] with the UK AI Security Institute through red teaming.

Technical Staff at the Center for AI Standards and Innovation · Jan 17, 2025 · full quote

Public funding fills gaps

Several quotes argue that important safety capabilities may be undersupplied by private actors alone, especially when profit incentives diverge from public good needs or open solutions remain scarce. From this perspective, governments have a crucial role in providing sustained funding for safety research and for maintaining shared software security infrastructure over time.

Corporate AI often prioritizes profit over public good, and critical capabilities (safety, security, equitable access) may never be developed privately.

Bruce Schneier · 2026 · full quote
The safety problems that matter most are often the ones no one has been able to solve in the open. Safety guardrails for youth resilience is a clear example: the need is global, but the tools are scarce.

Camille François · Jun 2, 2026 · full quote
Governments should fund sustained safety research to strengthen these safeguards over time and enable information-sharing of best practices between companies.

IDAIS-London Statement · Apr 17, 2026 · full quote
I don’t think it’s going to kill us. At the same time, I do think it’s important for the federal government to seriously fund AI safety research. We need to know a lot more about how the models work.

Robert D. Atkinson · Apr 17, 2026 · full quote
The challenge is especially acute for open source software, since it’s a public good. Open source software underpins every software service we rely upon, including across critical infrastructure and the Federal government. A string of recent incidents have highlighted the need fo…

Jack Cable · Jun 4, 2026 · full quote

Open-model security needs

Another line of support focuses on open-weight and open-source AI ecosystems as needing distinct security and monitoring tools. These quotes call for model-integrity checks, ecosystem monitoring, vulnerability reduction, and best-practice guidance to address risks such as unsafe deployment, malicious modification, supply-chain compromise, and other threats in open ecosystems.

Safety for open-weight models whose capabilities are nearing frontier closed models requires unique tools for open-weight model safety and ecosystem monitoring. [...] Accelerated public and private investment in research is required to keep pace with commercially driven growth in…

The 2026 Singapore Consensus on Global AI Safety Research Priorities · Jul 2026 · full quote
For organizations deploying open-weight models, a critical question emerges: how do you know the model you downloaded is safe to run? We believe defensive security tools should be widely available. AMS represents our contribution to a safer AI ecosystem—one where developers every…

Glen Messenger · Apr 27, 2026 · full quote
The Committee directs NIST to conduct a multi-stakeholder process to examine security risks associated with open-source artificial intelligence models such as model integrity, malicious modification, supply chain compromise, and data leakage. As part of this process, NIST shall i…

House Committee on Appropriations · May 2026 · full quote
PESOSE supports the creation of managing organizations for these ecosystems, ensuring strong governance, distributed development, and broad user communities across academia, industry, and government. PESOSE also supports enhancements to the safety, security, and privacy of Open-S…

National Science Foundation · Feb 19, 2026 · full quote

Insights

Several quotes define evaluation capacity itself as a safety function, linking third-party assessment, governance, and red-teaming to the ability to test models (13863, 13551, 13633, 14082).
Open-source is described not only as releasing code but also as sharing methods, infrastructure, extensions, and common platforms so others need not start from zero (14185, 12194, 14157, 13347).
A recurring concern is concentration: multiple quotes say safety tools should not remain inside a few large companies and should be usable by organizations of every size or any provider (14498, 14477, 14788).
Open-weight and open-source ecosystems are singled out as needing distinct integrity, monitoring, and vulnerability-mitigation tools, not just general AI safety research (14142, 11684, 14158, 14355).
The quotes often pair technical tool-building with institution-building, such as safety institutes, exchanges, managing organizations, and central technical authorities (14494, 14355, 15058, 14159).

In the provided material, supporters consistently depict open-source AI safety tools and red-teaming infrastructure as shared public infrastructure rather than proprietary extras. Their case combines government oversight, wider access to auditable safeguards, and sustained funding for risks tied to open-source and open-weight ecosystems. No direct counterargument appears in the quoted material, so the emphasis here is on what kinds of public capacity should be built and shared.

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For (40)

Advanced Research and Invention Agency (ARIA)
United Kingdom public R&D agency sponsoring AI-safety research and open-source coordination infrastructure.

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votes For and says:

To kickstart Phase 1 of this programme, we will be funding teams to develop open-source coordination infrastructure and perform fundamental research that moves us from empirical to theory-driven guarantees in agentic coordination.
AI Verified source (Jul 18, 2026)

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Andrew Charlton
Australian Assistant Minister for Science, Technology and the Digital Economy

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votes For and says:

The Government has built in response: an Australian AI Safety Institute, up and running, staffed with world-class expertise, and already inside the engine rooms of frontier AI, testing the most powerful models on the planet.
AI Verified source (Jul 7, 2026)

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European Commission
EU's executive body

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The Commission will help establish an EU evaluation capacity to strengthen third-party assessment of AI capabilities and risks globally, supporting the regulatory function of the AI Office.
AI Verified source (Jul 7, 2026)

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Government of Pakistan
National government of Pakistan, speaking through its delegation at the UN Global Dialogue on AI Governance in July 2026.

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We must therefore treat the capacity to evaluate and govern AI as an integral part to safety itself, supported through shared tools, pooled expertise, and cooperation across regions.
AI Verified source (Jul 7, 2026)

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Xinchen Hua Lu
UN AI panel member and researcher at CSIRO Australia.

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The government industrial research organizations, they could share their current evaluation tools or methods, evidence through the common platforms.
AI Verified source (Jul 7, 2026)

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The 2026 Singapore Consensus on Global AI Safety Research Priorities
July 2026 international consensus report on AI safety research priorities produced by over 100 contributors from 13 countries.

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votes For and says:

Safety for open-weight models whose capabilities are nearing frontier closed models requires unique tools for open-weight model safety and ecosystem monitoring. [...] Accelerated public and private investment in research is required to keep pace with...
more AI Verified source (Jul 2026)

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Jan Wehner
AI governance researcher at the Institute for AI Policy and Strategy, writing on AI safety and cybersecurity.

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To avoid losing visibility into cutting-edge AI cyberattack capabilities exactly when it matters most, I argue governments should fund independent threat-intelligence collection and sharing, develop AI-specific forensic capabilities, build the capaci...
more AI Verified source (Jun 29, 2026)

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AI Security Institute (AISI)
UK government AI safety institute

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votes For and says:

By open-sourcing not only Inspect, but also our methods and infrastructure where we can, we hope to help researchers, organisations, and other evaluators stand up rigorous evaluation capability without starting from zero.
AI Verified source (Jun 18, 2026)

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The AI Security Institute
UK government research organisation focused on AI safety and security

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By open-sourcing not only Inspect, but also our methods and infrastructure where we can, we hope to help researchers, organisations, and other evaluators stand up rigorous evaluation capability without starting from zero. We hope that the Engineering...
more AI Verified source (Jun 18, 2026)

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Mischa Spiegelmock
Technical staff member at METR working on frontier model evaluations

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Absolutely central to METR's evaluations is Inspect, which we've built our own open source cloud eval platform on top of, along with actively contributing to the Inspect codebase to run larger and more complex evaluations.
AI Verified source (Jun 18, 2026)

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JJ Allaire
Founder and Executive Chairman of Posit; creator of Inspect

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I created Inspect because I wanted to provide a strong technical foundation for governments, researchers, and labs to collaborate on testing and understanding frontier models. I am thrilled to have seen so many organisations adopt it, as well as to h...
more AI Verified source (Jun 18, 2026)

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Innovation, Science and Economic Development Canada
Government of Canada department responsible for innovation, science, and economic development.

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Canada will invest $50 million to expand the capabilities of the Canadian AI Safety Institute to track emerging AI risks, advance technical research, and to conduct transparent evaluations of AI models.
AI Verified source (Jun 8, 2026)

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Jack Cable
CEO and co-founder of Corridor; former CISA Secure by Design initiative lead and cybersecurity expert.

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The challenge is especially acute for open source software, since it’s a public good. Open source software underpins every software service we rely upon, including across critical infrastructure and the Federal government. A string of recent incident...
more AI Verified source (Jun 4, 2026)

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Camille François
President and CEO of Robust Open Online Safety Tools (ROOST)

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The safety problems that matter most are often the ones no one has been able to solve in the open. Safety guardrails for youth resilience is a clear example: the need is global, but the tools are scarce.
AI Verified source (Jun 2, 2026)

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Anne Le Hénanff
French Minister for Artificial Intelligence and Digital Affairs.

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votes For and says:

Safety tools cannot remain exclusive to the largest companies; they must be open, auditable, and collectively improved—serving as a common good for the benefit of society. This is how we will build trustworthy AI that truly protects our children, our...
more AI Verified source (Jun 2, 2026)

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Evan Solomon
Canada's Minister of Artificial Intelligence and Digital Innovation; Liberal MP for Toronto Centre

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By building safety tools in the open, this partnership will help organizations of every size adopt AI more responsibly. It strengthens trust, supports Canadian leadership in safe AI, and helps ensure the safeguards people rely on are transparent, ver...
more AI Verified source (Jun 2, 2026)

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G7 Digital and Technology Ministerial Declaration
Collective ministerial declaration of the Group of Seven on digital and technology policy, including international AI governance.

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Such discussions may also contribute to enhance the French Presidency’s Meta-detector for AI-generated content, an open source tool that aggregates multiple synthetic content detectors, enabling cross-referenced assessments.
AI Verified source (Jun 1, 2026)

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National Research Council Canada
Canada's federal research and development organization.

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In collaboration with the Vector Institute, we created new extensions to Inspect AI—the leading framework for AI safety evaluation—that make testing more transparent, reproducible and easier to share across teams.
AI Verified source (May 21, 2026)

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Glen Messenger
Google Kubernetes Engine contributor writing on open-source LLM safety tooling

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For organizations deploying open-weight models, a critical question emerges: how do you know the model you downloaded is safe to run? We believe defensive security tools should be widely available. AMS represents our contribution to a safer AI ecosys...
more AI Verified source (Apr 27, 2026)

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IDAIS-London Statement
Named 2026 consensus statement of the International Dialogues on AI Safety (IDAIS) London meeting, addressing AI-enabled cyber and biological risks.

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Governments should fund sustained safety research to strengthen these safeguards over time and enable information-sharing of best practices between companies.
AI Verified source (Apr 17, 2026)

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Robert D. Atkinson
Innovation economist; ITIF president

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I don’t think it’s going to kill us. At the same time, I do think it’s important for the federal government to seriously fund AI safety research. We need to know a lot more about how the models work.
AI Verified source (Apr 17, 2026)

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National Science Foundation
United States federal agency that funds research and publishes official science explainers.

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PESOSE supports enhancements to the safety, security, and privacy of Open-Source Ecosystems (OSE) by addressing significant vulnerabilities, both technical and socio-technical, to improve the resistance of the ecosystem against threats.
Unverifiable source (Mar 9, 2026) 1 of 2

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Government of the United Kingdom
United Kingdom central government

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Some £27 million will now be made available through the fund, supporting research efforts to ensure AI systems work as they’re supposed to, with £5.6 million coming from OpenAI, and additional support from Microsoft and others.
AI Verified source (Feb 19, 2026)

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House of Representatives of the Philippines
Lower chamber of the Congress of the Philippines.

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There is hereby created an AI Safety Research Fund, to be administered by the BAIS and funded through annual General Appropriations. The fund shall support: (a) Independent safety and bias evaluations; (b) Grants for red-teaming and adversarial testi...
more AI Verified source (Feb 4, 2026)

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Federation of American Scientists
US science policy nonprofit

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Build government AI–cyber capacity and translation infrastructure. Strengthen government capacity to evaluate, oversee, and respond to AI-enabled cyber risks by investing in technical staffing, institutional authority, and translation functions [...]...
more AI Verified source (Jan 2026)

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Adam Beaumont
UK AI Security Institute director

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[...] biosecurity red‑teaming [...] revealed [...] vulnerabilities. We’ve expanded the world’s most widely used government-backed evaluation tools. These open tools [...] make safety science accessible at scale.
AI Verified source (Dec 22, 2025)

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Ian Hogarth
UK AI Safety Institute chair

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[...] we are open sourcing our Inspect platform. [...] having a shared, accessible approach to evaluations. [...] a building block for AI Safety Institutes, research organisations, and academia.
AI Verified source (May 10, 2024)

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Michelle Donelan
British Conservative politician

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I have cleared [...] Inspect [...] to be open sourced. [...] to make AI safe. [...] safe AI will improve lives tangibly.
AI Verified source (May 10, 2024)

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Infocomm Media Development Authority (IMDA)
Singapore digital regulator

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[...] open-source community to develop AI testing tools to enable responsible AI. [...] bring benchmarking, red- teaming, and testing baselines together. [...] manage LLM deployment risks via benchmarking and red teaming.
AI Verified source (2024)

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Government of Canada
Federal government of Canada

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The Canadian and Korean AI Safety Institutes have signed a memorandum of understanding to strengthen international cooperation on artificial intelligence safety. Through this collaboration, the institutes will exchange information on AI technologies,...
more Unverifiable source (Jul 8, 2026)

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Carsten Wildberger
German Federal Minister for Digital Transformation and Government Modernization.

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We welcome the growing international community of public-sector institutions dedicated to AI security, and we intend our joint work to contribute to, and draw from, that wider effort.
Unverifiable source (Jun 30, 2026)

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Valérie Pisano
President and CEO of Mila – Quebec Artificial Intelligence Institute.

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AI safety should not be left to a handful of large companies making trade-offs behind closed doors. Partnering with ROOST lets our researchers work on harms with real public stakes, and commits us to putting what we build where any provider can use i...
more Unverifiable source (Jun 2, 2026)

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House Committee on Appropriations
U.S. House Appropriations Committee

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The Committee directs NIST to conduct a multi-stakeholder process to examine security risks associated with open-source artificial intelligence models such as model integrity, malicious modification, supply chain compromise, and data leakage. As part...
more Unverifiable source (May 2026)

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Kanishka Narayan
UK Minister for AI and Online Safety; Parliamentary Under-Secretary of State, Department for Science, Innovation and Technology

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votes For and says:

The UK, through AISI, has developed the world’s most widely used government-backed evaluation tools. Inspect, InspectSandbox, InspectCyber, and our latest release, ControlArena, are now being used by governments, companies, and academics around the w...
more Unverifiable source (Feb 10, 2026)

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Craig Burkhardt
Deputy Director of the U.S. National Institute of Standards and Technology.

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We are inviting technically capable organizations to join the NIST AI Consortium to address the challenges associated with the development and deployment of AI. To encourage more extraordinary AI technological innovations, NIST is seeking to expand i...
more Unverifiable source (May 29, 2026)

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Government of Singapore
National government of Singapore, publishing the National AI Strategy and AI governance policy.

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Singapore launched the AI Verify Foundation in 2023 to harness the collective contributions of the global open-source community to develop AI testing tools. This includes Project Moonshot, an open-source tool to bring benchmarking and red teaming tog...
more Unverifiable source (May 21, 2026)

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Mia Glaese
Vice President of Research at OpenAI.

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As AI systems become more capable and more autonomous, alignment has to keep pace. The hardest problems won’t be solved by any one organisation working in isolation—we need independent teams testing different assumptions and approaches.
Unverifiable source (Feb 19, 2026)

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David Lammy
UK Deputy Prime Minister and Secretary of State for Foreign, Commonwealth and Development Affairs

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AI offers us huge opportunities, but we will always be clear-eyed on the need to ensure safety is baked into it from the outset.
Unverifiable source (Feb 19, 2026)

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Bruce Schneier
Security technologist and author

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Corporate AI often prioritizes profit over public good, and critical capabilities (safety, security, equitable access) may never be developed privately.
Disputed source (2026)

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Technical Staff at the Center for AI Standards and Innovation
NIST CAISI technical staff collective

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Publicly available evaluation frameworks provide an important foundation [...] CAISI has open-sourced our improvements [...] with the UK AI Security Institute through red teaming.
Disputed source (Jan 17, 2025)

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