Open-source AI is more dangerous than closed-source AI

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Key insights

Many quotes discuss open-weight release specifically, so the disagreement often centers on whether public model weights should be judged differently from other forms of openness.
Both sides acknowledge dual-use potential; they differ mainly on whether broader access helps malicious actors more than it helps auditors, researchers, and defenders.
Several supportive and skeptical quotes alike treat model capability as a key variable, arguing that the case changes as models approach frontier performance or as safeguards differ.
Government and security-focused quotes on the supporting side often emphasize cyber, biological, fraud, or child-safety misuse, while open-source and enterprise voices on the opposing side emphasize inspection, standards, and operational defense.
A recurring fault line is control after release: one side treats irreversibility and unmonitorable local use as decisive, while the other treats transparency and shared remediation as the stronger security property.

Arguments for

Removable safeguards

Proponents say closed models can rely on provider-controlled safety layers that open-weight releases cannot enforce after download. Because weights can be run locally, fine-tuned, or modified, safeguards may be weak, easily stripped, or absent altogether, widening access to dangerous capabilities.

When the safety guardrails are stripped out of a capable model, it can be used at scale for harm in ways a single person could never manage manually. [...] The leading open-weight models are often not too far behind the best closed models. As they grow more powerful, the potentia…

Sirisha Rambhatla · Aug 25, 2026 · full quote
No safety system can eliminate every dual-use risk. Once model weights are public, no developer can guarantee control over every downstream modification or use. Model-level safeguards can raise the barrier to abuse, but they cannot provide absolute control.

Z.ai · Aug 16, 2026 · full quote
Because open-weight safeguards can often be removed, public release of such models may make it impossible to prevent a wide range of actors from accessing dangerous capabilities.

Spencer E. Amdur · Jul 11, 2026 · full quote
Open weights make that worry land harder, because you can't recall them. A closed model that misbehaves can be patched or pulled overnight. A set of weights on a hard drive is forever. And the safety training is the flimsiest layer in the stack. You can fine-tune the refusals off…

Om Bharatiya · Jul 10, 2026 · full quote
For closed-weight models, [misuse] risk is at least partially manageable. Input-output classifiers and safety fine-tuning can intercept most non-sophisticated actors before they get actionable guidance. [...] Open-weight models have no such layer. Once weights are downloaded, the…

Sophie Kim · Apr 11, 2026 · full quote
Whilst safeguards applied by responsible model developers can limit misuse of AI, these protections can often be bypassed (and in open‑weight models can be removed or are absent from the start). Publicly-available AI model weights can be modified, and safeguards removed entirely.

National Cyber Security Centre · Mar 2026 · full quote

Irreversible release

They argue that once weights are public, they cannot be recalled, patched in place, or reliably re-gated, so misuse creates a persistent risk. Unlike a closed deployment that can be pulled or updated, every retained copy of an open-weight model stays usable indefinitely and may operate without visibility or logging.

For models with dangerous capabilities – including highly cyber-capable models – open weight release therefore creates a persistent and irreversible risk of misuse.

AI Security Institute (AISI) · Jul 17, 2026 · full quote
You can’t patch a released, open-weight model. This is the property that breaks the assumptions of the prior model of responsible disclosure. Open-source software can be patched in place; a deployer updates and the hazard closes. An open-weight model cannot. A new version is a ne…

MLCommons · Jun 9, 2026 · full quote
When a frontier lab releases model weights publicly, the decision is irreversible in a way that no other software release is: the weights can be copied, fine-tuned, stripped of safety mitigations, and redistributed before any downstream harm is even detected.

Marisol Vega · Feb 19, 2026 · full quote
High-capability open source models are difficult to control. Gated or retracted access is not possible once a model has been released into the open domain, leaving the possibility of malicious application.

Independent International Scientific Panel on Artificial Intelligence · Jul 2026 · full quote
Not deploying high-risk systems with open weights: Avoiding open-weight release of a system can be a strong defence against many downstream risks that they pose.

UK AI Security Institute · Jul 22, 2026 · full quote
An attacker can run it locally without safety guardrails, fine-tune it against their specific targets, and operate with zero visibility to any provider or defender.

Travis Lanham · Jun 25, 2026 · full quote

Near-frontier misuse access

Supporters contend that leading open-weight models are now close enough to frontier closed systems that cyber and other dual-use risks are becoming practical for a far wider set of actors. Because these models can also be run more cheaply, harmful use may arrive before they fully catch up to the frontier.

Open-weight models are approaching the capabilities of frontier closed-weight models, yet they are often released without the safety evaluations that accompany closed models, and their safeguards are either weak or can be easily removed.

SaferAI · Aug 2, 2026 · full quote
According to common benchmarks, open weight models are estimated to be 3 to 12 months behind the frontier (varying across capabilities). Developers of frontier closed models have recently designated these closed models as ‘High’ risk for cyber and biological misuse, and added saf…

The 2026 Singapore Consensus on Global AI Safety Research Priorities · Jul 2026 · full quote
Open-weight models – models of which the core parameters are made available for others to run and adapt – are an important medium-term issue. Evidence suggests they may lag the most advanced closed models by only four to eight months, and that their safeguards are often easy to r…

Bank of England · Jul 1, 2026 · full quote
Because they can also be run more cheaply than proprietary models, the point at which open-weight models become dangerous and practical to use may arrive before they fully catch up with frontier models.

Financial Policy Committee · Jul 15, 2026 · full quote
Don't be surprised if these capabilities are soon in the hands of ransomware crews, intelligence agencies and a "lone operator renting compute by the hour."

Alexander Leslie · Jul 28, 2026 · full quote
Open-weight releases such as Kimi K2.5 are already benchmarked on par with frontier closed models on cybersecurity tasks. Safeguards on open-weight models can also be removed through fine-tuning, a well-established procedure.

CERT-EU · Jul 2026 · full quote

Observed exploitability

This side also points to studies and field reports indicating that simple attacks can sharply raise harmful-response rates on safeguarded open-weight models, and that low-compute models can support fraud, disinformation, and offensive security tasks on consumer hardware. To them, this suggests the misuse path is already practical rather than hypothetical.

In this paper, we show that open-weight safeguards are susceptible to simpler strategies that, despite being well known, have not been systematically evaluated against these safeguards. Specifically, we evaluate two low-cost attacks--abliteration and prefilling--that do not rely …

Kevin Kuo · May 26, 2026 · full quote
We then simulate the computational resources needed for an actor to launch a series of digital societal harm campaigns - such as disinformation botnets, sexual extortion schemes, voice-cloning fraud, and others - using low-compute open-source models and find nearly all studied ca…

Prateek Puri · Jan 29, 2026 · full quote
Hackers are already talking in Russian-language forums about how easy it is to jailbreak GLM-5.2 for hacking tasks.

Jason Baker · Jun 25, 2026 · full quote
The adoption of CyberStrikeAI is poised to accelerate, representing a concerning evolution in the proliferation of AI-augmented offensive security tools.

Will Thomas · Mar 3, 2026 · full quote
Everybody can download and operate their own state-of-the-art model and use it for great things and terrible things.

Noam Schwartz · May 31, 2026 · full quote
The 71pp open-weight span is therefore not an artifact of quantization or scale: the same low/high codification grouping appears across model families and deployment surfaces, attenuated in absolute level (highest closed-model cell 40.4% vs. open-weight 85.7%) but identical in st…

Zacharie Bugaud · Jun 1, 2026 · full quote

Arguments against

Transparency and scrutiny

Opponents argue that openness lets researchers, users, and defenders inspect models, test assumptions, discover flaws, and share fixes instead of relying solely on a vendor's claims. In this view, broad scrutiny hardens systems over time and makes training choices and weaknesses more visible.

As policymakers and regulators work through questions of AI safety, the distinction that matters is not open versus closed, but transparent and secure versus opaque and unexamined. Open models and open tooling should be recognized as defensive assets that enable transparency, ind…

The Linux Foundation · Jul 27, 2026 · full quote
Safe open-weight models are public goods, as they put AI development and safety work in many hands and make training choices inspectable.

Thinking Machines Lab · Jul 31, 2026 · full quote
Openness also delivers genuine transparency, because when the model is yours to inspect, you can see exactly what sits inside it, [...] and turn your best and brightest loose to hunt the very security flaws the cyber-hawks rightly fear. A sealed model offers no such window and as…

Jordan Schachtel · Jul 6, 2026 · full quote
Open source does not eliminate risk. It changes how risk is managed. It allows more researchers, developers, and defenders to examine systems, test assumptions, surface weaknesses, and harden code under real-world conditions. [...] If frontier models are increasingly capable of f…

Rob Thomas · 2026 · full quote
Open-source AI allows the public to audit and verify algorithms, [...] It is also more secure because any attacks or exploits can be identified and remediated.

Travis Oliphant · Feb 21, 2025 · full quote
Open source provides an opportunity for many people to examine those technologies, to test them in a variety of settings and to provide fixes [...]

Dr Moez Draief · Nov 8, 2023 · full quote

Defensive access

They say open models are already being tuned and used as defensive assets, and that defenders need rapid, broad access to strong tools when confronting AI-enabled attacks. Restricting open access, they argue, would weaken cyber defense and make response dependent on a few closed providers.

The alliance used its launch to urge regulators to treat open models as ‘defensive assets, not liabilities,’ warning that blanket restrictions would weaken cyber defenses and concentrate power in a handful of closed AI providers.

Open Secure AI Alliance · Jul 28, 2026 · full quote
When a frontier model is attacking you and moving laterally inside your infrastructure, defenders need wide access to near-frontier tools within hours or even minutes, rather than being pointed toward a closed-door platform.

Thomas Wolf · Jul 22, 2026 · full quote
Shared access to open-source AI systems is important for protection in a world where AI can be used to hack into electronic systems, like voting systems and benefits infrastructure.

Matt Lane · Aug 10, 2026 · full quote
Open models, a valuable defense tool, are today being tuned, evaluated, and run in production to actively improve the security of enterprises.

Bartley Richardson · Jul 27, 2026 · full quote
Open development produces stronger defense.

Justin Boitano · Jul 27, 2026 · full quote
Open-source AI is more than a catalyst for commercial innovation. It is a strategic advantage for the U.S. military, enabling American companies to push the technology forward while giving the DOD a foundation it can inspect, secure, adapt and deploy faster than any adversary.

Patrick McSpadden · Jul 16, 2026 · full quote

Not uniquely risky

Another line of argument is that misuse risk comes from model power and deployment choices, not from openness alone. On this view, open-weight systems are not inherently less secure than closed ones, and advanced AI requires safeguards wherever it is used.

Open-weight systems are not inherently less secure than closed systems.

John Villasenor · Aug 10, 2026 · full quote
Open models, like any powerful technology, can be misused — including through attempts to weaken safeguards or repurpose capabilities for cyber attacks — but those risks are not unique to open systems, and they must be managed wherever advanced AI is deployed.

NVIDIA · Jul 27, 2026 · full quote
From a business perspective, the difference between open and closed is a little bit overblown. From a security perspective, the difference between open and closed models is, for some intents and purposes, overblown. The most important thing is how powerful a model is. If a model …

Dario Amodei · 2025 · full quote
If safeguards are properly followed, businesses, including banks, should have enough guarantees to essentially run any model, regardless of where they come from.

Marco Argenti · Sep 8, 2026 · full quote
Study of 34 AI models from 10 global providers finds open-source AI models are not less safe, reasoning models are hardest to exploit and smaller models are the most vulnerable.

TELUS Digital · May 26, 2026 · full quote
China’s open models are no more dangerous than any other open source software a company may use.

Lucas Atkins · Jul 22, 2026 · full quote

Centralization as danger

Critics of the statement argue that concentrating advanced AI inside a small number of proprietary systems creates its own security, accountability, and power risks. Broad availability and inspectable models, they say, provide checks and balances, support competition, and reduce dependence on black-box gatekeepers.

One of the ways to achieve both individual empowerment and checks and balances is to make sure you put the technology in everybody's hands. I’m personally more worried about centralization than I am about any of the specific risks others are talking about.

Mark Zuckerberg · Aug 10, 2026 · full quote
I see the danger of this concentration of power through proprietary AI systems as a much bigger danger than everything else. What works against this is people who think that for reasons of security, we should keep AI systems under lock and key because it’s too dangerous to put it…

Yann LeCun · 2024 · full quote
With the right choices, open weight AI can expand opportunity, strengthen competition, extend American technological leadership, mitigate risk, and ensure that the benefits of this extraordinary technology are shared broadly across our economy.

Open Weights and American AI Leadership · Jul 24, 2026 · full quote
Open-source AI fosters innovation, improves security, and lowers costs—critical benefits for businesses, researchers, and everyday users around the world.

Mozilla · 2025 · full quote
But the real danger lies in centralized, black-box systems that resist open auditing.

Himanshu Tyagi · 2025 · full quote
Bria is proud to sign on to “Open Weights and American AI Leadership,” a coalition statement on why open, inspectable models matter for a healthy, competitive AI ecosystem.

Bria AI · Aug 2026 · full quote

Middle ground

Risk-based release decisions

Several quotes argue against blanket rules and instead call for testing models before release, setting different bars based on dangerous capabilities, and pairing openness with focused safeguards. In this view, both open and closed systems require scrutiny, but open-weight release may demand a different threshold when misuse potential is high.

The right way to do this is if a model, before it is released in open weights or in other ways, a model should be tested. Can it be used by people? Are we sure we’re not going to lose control of it? Does it have the capabilities or intentions that could be dangerous for people? I…

Yoshua Bengio · Mar 12, 2026 · full quote
Like policymakers, we want a safe, secure AI ecosystem, and view openness as an important part of achieving it. We support policies that preserve the ability to develop, distribute, and use open weight models subject to focused, risk-based safeguards and well-targeted tools for a…

GitLab · Jul 29, 2026 · full quote
Higher security: Closed models have more safeguards. However, they also make certain safety measures harder, such as red teaming and mechanistic interpretability. Lower security: Open-weight systems are harder to monitor and regulate and can easily be fine-tuned to remove safegua…

Government of the United Kingdom · Jun 2026 · full quote
While respecting security, data protection and intellectual property rights, we encourage member economies to support open-source models and projects that employ strong security assurance through development and deployment.

APEC · Jul 24, 2026 · full quote
It is unquestionably both. We can use the frontier models but also open weight models to prove a solution which gives defenders powerful capabilities and on their terms.

Jaya Baloo · Jun 22, 2026 · full quote

Attacker-defender tradeoffs

Some quotes say restrictions are precautionary only if they slow harmful actors more than defenders, noting that well-resourced attackers may still obtain substitutes while smaller defenders may not. They also argue that current evidence is not yet sufficient to establish greater marginal societal risk from open models, and that restrictions without governed alternatives may displace rather than reduce risk.

Restricting access to a dual-use AI model is precautionary only if it delays harmful actors more than defenders. That condition varies across actors: a state agency or organized criminal group may obtain a substitute through theft, distillation, intermediated access, independent …

Daniel Commey · Jul 24, 2026 · full quote
These studies, on their own, are insufficient evidence to demonstrate increased marginal societal risk from open foundation models.

Stanford Center for Research on Foundation Models · 2024 · full quote
The governance of open-weight artificial intelligence (AI) models has been framed as a binary choice: openness as risk, restriction as safety. This paper challenges that framing, arguing that access restrictions, without governed alternatives, may displace risks rather than reduc…

Vinicius Santana Gomes · Apr 19, 2026 · full quote
Publishing source code does not create those weaknesses, but it can modestly reduce attacker uncertainty and speed up analysis (an effect that may increase with AI assistance), especially where maintenance is weak and fixes are slow.

Government Digital Service · May 14, 2026 · full quote

Participants broadly agree that advanced AI can be misused and that safeguards matter. They disagree over whether security is better served by retaining provider control over powerful models or by enabling broad inspection, adaptation, and defensive use. Some quotes therefore move toward case-by-case release thresholds and targeted safeguards rather than a single rule for all models.

Cast your vote:

Results (112 votes):

Total (112 votes)

For 54 (48%) Abstain 3 (3%) Against 55 (49%)

For (50)

George Balston
Strategic Adviser to the Alan Turing Institute and co-founder of AVERI; former UK government researcher, data scientist, and technical lead focused on AI, privacy, and government technology.

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votes For and says:

Open-weight models introduce new and unique risks – they provide near-frontier capabilities which could be used for criminal purposes, are widely available to anyone who intends harm, and are easier to misuse. [...] Major frontier AI companies such a...
more AI Verified source (Sep 18, 2026)

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Sirisha Rambhatla
Professor of management science and engineering at the University of Waterloo; director of its Critical Machine Learning Lab.

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votes For and says:

When the safety guardrails are stripped out of a capable model, it can be used at scale for harm in ways a single person could never manage manually. [...] The leading open-weight models are often not too far behind the best closed models. As they gr...
more AI Verified source (Aug 25, 2026)

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Z.ai
Chinese artificial intelligence company behind the GLM family of language models.

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votes For and says:

No safety system can eliminate every dual-use risk. Once model weights are public, no developer can guarantee control over every downstream modification or use. Model-level safeguards can raise the barrier to abuse, but they cannot provide absolute c...
more AI Verified source (Aug 16, 2026)

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Danny Jenkins

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votes For and says:

That assumption is unrealistic in the world of AI-driven automation and open-source agent ecosystems.
AI Verified source (Aug 5, 2026)

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Rebecca Bellan
Senior reporter at TechCrunch covering AI business, policy, and emerging trends.

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votes For and says:

But the safeguards in place for closed models don’t work at all on open-weight models, which are designed to run on any infrastructure with any set of safeguards — or lack thereof.
AI Verified source (Aug 4, 2026)

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Le Monde
French daily newspaper; editorial board

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votes For and says:

So-called "open-weight" models, whose parameters can be downloaded and modified, were thought to be more likely to escape the protections put in place by their creators.
AI Verified source (Aug 4, 2026)

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SaferAI
Nonprofit organization researching and promoting responsible frontier AI risk management and safety governance.

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votes For and says:

Open-weight models are approaching the capabilities of frontier closed-weight models, yet they are often released without the safety evaluations that accompany closed models, and their safeguards are either weak or can be easily removed.
AI Verified source (Aug 2, 2026)

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Frank Teruel
Chief Operating Officer at Arkose Labs, commenting on AI-enabled cyber threats.

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votes For and says:

Frontier labs can put classifiers in front of these capabilities, but open-weight models a few months behind cannot, and the copies already downloaded never will.
AI Verified source (Jul 28, 2026)

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Alexander Leslie
Senior adviser at Recorded Future, commenting on AI-enabled cyber threats.

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votes For and says:

Don't be surprised if these capabilities are soon in the hands of ransomware crews, intelligence agencies and a "lone operator renting compute by the hour."
AI Verified source (Jul 28, 2026)

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Rob T. Lee
Chief AI Officer at the SANS Institute and cybersecurity expert.

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votes For and says:

Stripping guardrails from an open-source AI model is trivial for anyone who wants both.
AI Verified source (Jul 28, 2026)

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Against (54)

Marco Argenti
Chief Information Officer of Goldman Sachs, speaking publicly on safeguards for open-weight AI models.

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votes Against and says:

If safeguards are properly followed, businesses, including banks, should have enough guarantees to essentially run any model, regardless of where they come from.
AI Verified source (Sep 8, 2026)

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John Villasenor
UCLA professor; Brookings senior fellow

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votes Against and says:

Open-weight systems are not inherently less secure than closed systems.
AI Verified source (Aug 10, 2026)

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Matt Lane
Senior Policy Counsel, Fight for Future

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votes Against and says:

Shared access to open-source AI systems is important for protection in a world where AI can be used to hack into electronic systems, like voting systems and benefits infrastructure.
AI Verified source (Aug 10, 2026)

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Mark Zuckerberg
Meta CEO; Facebook co-founder

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votes Against and says:

One of the ways to achieve both individual empowerment and checks and balances is to make sure you put the technology in everybody's hands. I’m personally more worried about centralization than I am about any of the specific risks others are talking ...
more AI Verified source (Aug 10, 2026)

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Cohesity
Data-security and data-management software company.

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votes Against and says:

We're proud to co-sign the Open Weights and American AI Leadership letter alongside 230+ companies, helping enterprises use open AI safely.
AI Verified source (Aug 2026)

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DataRobot
Enterprise AI platform company.

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votes Against and says:

DataRobot gives customers the flexibility to run open-weight models on their own terms, which is why we're proud to sign this letter championing an open AI ecosystem.
AI Verified source (Aug 2026)

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Resemble AI
AI company developing voice-generation and deepfake-detection models.

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votes Against and says:

Releasing these in the open is what keeps us in the research conversation rather than adjacent to it. That research has directly led to our leading multimodal Deepfake Detection Model.
AI Verified source (Aug 2026)

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Bria AI
Generative-AI company offering visual-model tools with licensed training data.

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votes Against and says:

Bria is proud to sign on to “Open Weights and American AI Leadership,” a coalition statement on why open, inspectable models matter for a healthy, competitive AI ecosystem.
AI Verified source (Aug 2026)

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Thinking Machines Lab
AI research and product company publishing work on safe open-weight model releases.

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votes Against and says:

Safe open-weight models are public goods, as they put AI development and safety work in many hands and make training choices inspectable.
AI Verified source (Jul 31, 2026)

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GitLab
DevSecOps software company; signatory to the Open Weights and American AI Leadership letter.

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votes Against and says:

Like policymakers, we want a safe, secure AI ecosystem, and view openness as an important part of achieving it. We support policies that preserve the ability to develop, distribute, and use open weight models subject to focused, risk-based safeguards...
more AI Verified source (Jul 29, 2026)

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Bill Staples
Chief Executive Officer of GitLab, a DevSecOps software company.

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votes Against and says:

Like policymakers, we want a safe, secure AI ecosystem, and view openness as an important part of achieving it.
AI Verified source (Jul 29, 2026)

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Open Secure AI Alliance
Industry alliance launched in July 2026 to develop open tools and practices for AI safety and security.

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votes Against and says:

The alliance used its launch to urge regulators to treat open models as ‘defensive assets, not liabilities,’ warning that blanket restrictions would weaken cyber defenses and concentrate power in a handful of closed AI providers.
AI Verified source (Jul 28, 2026)

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Chris Wright
Chief Technology Officer and Senior Vice President of Global Engineering at Red Hat.

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votes Against and says:

This initiative focuses on developing open tools and techniques to safeguard the AI stack—from open weight models to agent harnesses—to help drive safety, transparency, and broad scientific scrutiny. Open source models and frameworks act as vital def...
more AI Verified source (Jul 27, 2026)

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Bartley Richardson
Senior Director of Engineering at CrowdStrike, working on AI security.

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votes Against and says:

Open models, a valuable defense tool, are today being tuned, evaluated, and run in production to actively improve the security of enterprises.
AI Verified source (Jul 27, 2026)

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Genspark
AI company developing an agentic AI workspace.

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votes Against and says:

But closing the ecosystem is not the answer. Openness is what lets a community find vulnerabilities, build safeguards, and improve models over time, rather than concentrating that work behind a few closed systems.
AI Verified source (Jul 27, 2026)

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Chris Wright
Chief Technology Officer and Senior Vice President of Global Engineering at Red Hat.

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votes Against and says:

This initiative focuses on developing open tools and techniques to safeguard the AI stack—from open weight models to agent harnesses—to help drive safety, transparency, and broad scientific scrutiny. Open source models and frameworks act as vital def...
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Bartley Richardson

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votes Against and says:

Open models, a valuable defense tool, are today being tuned, evaluated, and run in production to actively improve the security of enterprises.
AI Verified source (Jul 27, 2026)

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The Linux Foundation
Nonprofit consortium supporting open-source technology ecosystems

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votes Against and says:

As policymakers and regulators work through questions of AI safety, the distinction that matters is not open versus closed, but transparent and secure versus opaque and unexamined. Open models and open tooling should be recognized as defensive assets...
more AI Verified source (Jul 27, 2026)

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Justin Boitano
Vice President of Enterprise AI at NVIDIA.

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votes Against and says:

Open development produces stronger defense.
AI Verified source (Jul 27, 2026)

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Jim Zemlin
Executive Director of the Linux Foundation.

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votes Against and says:

Open source became the backbone of modern computing because it let everyone see, improve, and secure the technology they rely on. The Open Source Software Foundation is a great example of this dynamic, building standards and tools for the benefit of ...
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More h/open-source votes

Democratic middle powers should jointly develop frontier AI and share its benefits globally

Require frontier AI labs to conduct nearly all R&D publicly but keep the weights closed

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