Require AI systems above a capability threshold to be interpretable

For (31)

• 

  Gary Marcus

  Professor of Psychology and Neural Science

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  votes For and says:

  Algorithmic transparency. When a driverless car has an accident, or a consumer’s loan application has been denied, we should be able to ask what’s gone wrong. The big trouble with the black box algorithms that are currently in vogue is that [nobody] ... more AI Verified source (2024)

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  Cynthia Rudin

  Duke professor, interpretable ML advocate

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  votes For and says:

  You can't have accountability without transparency. Black box models are not transparent, and they don't mix well with human oversight. Either the human blindly trusts the model—or doesn't trust it at all. Unverified source (2026)

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  Elon Musk

  Founder of SpaceX, cofounder of Tesla, SolarCity & PayPal

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  votes For and says:

  I do think you want to actually have very good ways to look inside the mind of the AI. [...] Anthropic's done a good job of this actually, being able to look inside the mind of the AI. Unverified source (2026)

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  Uri Maoz

  Cognitive and computational neuroscientist; Associate Professor at Chapman University with appointments at UCLA and Caltech

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  votes For and says:

  The immediate danger is not that machines will act without human oversight; it is that human overseers have no idea what the machines are actually "thinking." State-of-the-art AI systems are essentially "black boxes." We know the inputs and outputs, ... more Unverified source (2026)

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• 

  Julius Adebayo

  CEO and co-founder of Guide Labs; MIT PhD in Computer Science (interpretability and algorithmic fairness); former Google Brain resident

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  votes For and says:

  The way we're currently training models is super primitive, and so democratizing inherent interpretability is actually going to be a long-term good thing for our role within the human race. As we're going after these models that are going to be super... more Unverified source (2026)

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  Narendra Modi

  Prime Minister of India

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  votes For and says:

  We need a glass box approach instead of a black box, where safety rules can be viewed and verified. Accountability will become clearer, and ethical behaviour in business will also be encouraged. Unverified source (2026)

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  Yoshua Bengio

  AI Pioneer, Turing Award winner

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  votes For and says:

  I'm now very confident that it is possible to build AI systems that don't have hidden goals, hidden agendas. [...] A Scientist AI would be trained to give truthful answers based on transparent, probabilistic reasoning. Unverified source (2026)

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  Chris Olah

  Anthropic co-founder, pioneer of mechanistic interpretability

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  votes For and says:

  It's crazy to use these models in high-stakes situations and not understand them. Unverified source (2026)

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• 

  Abraham C. Meltzer

  California judge and legal scholar

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  votes For and says:

  Black box AI systems "do not explain their predictions in a way that humans can understand." AI Verified source (2024)

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• 

  Rob Strayer

  EVP Policy, Information Technology Industry Council

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  votes For and says:

  Transparency is a key means by which to achieve that trust. [...] Transparency is an overarching concept [...]. Transparency requirements should be risk-based. AI Verified source (2023)

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• 

  Sam Gregory

  Executive Director, WITNESS

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  votes For and says:

  Transparency [...] is a critical area. [...] Embed human rights standards and a rights-based approach in the response to AI. [...] Place firm responsibility on stakeholders [...]. AI Verified source (2023)

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  Ramayya Krishnan

  Dean, Heinz College, Carnegie Mellon

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  votes For and says:

  Congress should require standardized documentation. Congress should require a model validation report. [...] provide the required assurance prior to deployment. AI Verified source (2023)

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• 

  Michael Bennet

  U.S. Senator from Colorado

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  votes For and says:

  AI systems should undergo regular public risk assessments to examine their safety, reliability, security, explainability, and efficacy. AI Verified source (2023)

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• 

  Suresh Venkatasubramanian

  Brown CS professor; former OSTP official

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  votes For and says:

  Congress should demand that these systems be explainable. How that plays out will be a matter for innovation. AI Verified source (2023)

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  Christina Montgomery

  IBM Chief Privacy & Trust Officer

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  votes For and says:

  AI should augment humans, not replace them, it should be explainable, and fair and private and secure. AI Unverifiable source (2023)

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• 

  European Union

  Political and economic union

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  votes For and says:

  ensure that the AI system’s output is interpretable by the provider and the user. AI Unverifiable source (2023)

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  European Parliament

  EU legislative body

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  votes For and says:

  Citizens will have a right to launch complaints about AI systems and receive explanations about decisions based on high-risk AI systems that impact their rights. AI Verified source (2023)

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  Chuck Schumer

  U.S. Senate Majority Leader

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  votes For and says:

  Finally, explainability, one of the thorniest and most technically complicated issues we face, but perhaps the most important of all. Explainability is about transparency. When you ask an AI system a question and it gives you an answer, perhaps the a... more AI Verified source (2023)

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  Reporters Without Borders (RSF)

  Press freedom nonprofit

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  votes For and says:

  RSF, which has already called for the AI Act to includemeasures to protect the right to information, is convinced that that these models must be regulated. But some European countries, including France, are advocating self-regulation based on codes o... more AI Verified source (2023)

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  Anthropic

  AI safety research company

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  votes For and says:

  The definition, criteria, and safety measures for each ASL level are described in detail in the main document, but at a high level, ASL-2 measures represent our current safety and security standards and overlap significantly with our recent White Hou... more AI Verified source (2023)

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  Rohit Chopra

  CFPB Director; U.S. consumer regulator

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  votes For and says:

  We’ve also taken action to protect the public from black box credit models – in some cases so complex that the financial firms that rely on them can’t even explain the results. Companies are required to tell you why you were denied for credit – and u... more AI Verified source (2023)

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• 

  Consumer Financial Protection Bureau (CFPB)

  U.S. consumer finance regulator

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  votes For and says:

  Today, the Consumer Financial Protection Bureau (CFPB) confirmed that federal anti-discrimination law requires companies to explain to applicants the specific reasons for denying an application for credit or taking other adverse actions, even if the ... more AI Verified source (2022)

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  White House Office of Science and Technology Policy (OSTP)

  U.S. White House science office

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  votes For and says:

  You should know that an automated system is being used and understand how and why it contributes to outcomes that impact you. Designers, developers, and deployers of automated systems should provide generally accessible plain language documentation i... more AI Verified source (2022)

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  Dragoș Tudorache

  EU MEP; AI Act co-rapporteur

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  votes For and says:

  Then the second floor, you have the high-risk applications. And the commission is proposing in an annex, in fact – and I’ll explain why in an annex – identify several sectors where if you develop AI in those sectors, again, because the likelihood of ... more AI Verified source (2022)

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  UNESCO

  UN agency for education, science, culture

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  votes For and says:

  Governments should adopt a regulatory framework that sets out a procedure, particularly for public authorities, to carry out ethical impact assessments on AI systems to predict consequences, mitigate risks, avoid harmful consequences, facilitate citi... more AI Verified source (2021)

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  Lloyd J. Austin III

  U.S. Secretary of Defense

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  votes For and says:

  So we have established core principles for Responsible AI. Our development, deployment, and use of AI must always be responsible, equitable, traceable, reliable, and governable. We’re going to use AI for clearly defined purposes. We’re not going to... more AI Verified source (2021)

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  Information Commissioner's Office (ICO)

  UK data protection authority

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  votes For and says:

  Where an individual would expect an explanation from a human, they should instead expect an explanation from those accountable for an AI system. AI Verified source (2020)

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  Federal Trade Commission (FTC)

  US consumer protection agency

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  votes For and says:

  If you are using AI to make decisions about consumers in any context, consider how you would explain your decision to your customer if asked. AI Verified source (2020)

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  Alan F. T. Winfield

  Professor of Robot Ethics, UWE Bristol

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  votes For and says:

  Robots should be fitted with an "ethical black box" to keep track of their decisions and enable them to explain their actions when accidents happen. AI Verified source (2017)

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  AI Now Institute

  NYU institute on AI policy

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  votes For and says:

  1 — Core public agencies, such as those responsible for criminal justice, healthcare, welfare, and education (e.g “high stakes” domains) should no longer use ‘black box’ AI and algorithmic systems. This includes the unreviewed or unvalidated use of p... more AI Verified source (2017)

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  Frank Pasquale

  Law professor, algorithmic accountability expert

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  votes For and says:

  Some of the black boxes of reputation, search, and finance simply need to be pried open. AI Verified source (2015)

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Abstain (0)

Against (12)

• 

  Dario Amodei

  CEO at Anthropic

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  votes Against and says:

  Many of the risks and worries associated with generative AI are ultimately consequences of this opacity, and would be much easier to address if the models were interpretable. [...] governments can use light-touch rules to encourage the development o... more Verified source

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  James Broughel

  Economist focused on regulation

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  votes Against and says:

  We should strive to make AI systems interpretable where possible, but not at the cost of the benefits they deliver. AI Unverifiable source (2024)

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  MIT Lincoln Laboratory

  MIT research lab for national security

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  votes Against and says:

  As autonomous systems and artificial intelligence (AI) become increasingly common in daily life, new methods are emerging to help humans check that these systems are behaving as expected. One method, called formal specifications, uses mathematical fo... more AI Verified source (2023)

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  Max W. Shen

  AI researcher; trust and interpretability

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  votes Against and says:

  The problem of human trust in artificial intelligence is one of the most fundamental problems in applied machine learning. Our processes for evaluating AI trustworthiness have substantial ramifications for ML's impact on science, health, and humanity... more AI Verified source (2022)

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  Brookings Institution

  U.S. public policy think tank

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  votes Against and says:

  Explainable AI (XAI) is often offered as the answer to the black box problem and is broadly defined as “machine learning techniques that make it possible for human users to understand, appropriately trust, and effectively manage AI.” Around the world... more AI Verified source (2021)

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  Bruce Schneier

  Security technologist and author

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  votes Against and says:

  Forcing an AI to produce a human-understandable explanation is an additional constraint, and it could affect the quality of its decisions. AI Verified source (2021)

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  U.S. Chamber of Commerce (C_TEC)

  Largest U.S. business federation

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  votes Against and says:

  [C_TEC urged NIST to avoid defining premature requirements] relating to aspirational standards for AI that have not matured or are not developed yet, including concepts such as "explainability," "auditability," "robust accuracy," and "error-free algo... more AI Verified source (2021)

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  Scott Robbins

  AI ethics researcher

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  votes Against and says:

  [...] principles requiring that AI be explicable are misguided. We should be deciding which decisions require explanations. Automation is still an option; AI Verified source (2019)

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  Roman V. Yampolskiy

  AI safety researcher, Louisville professor

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  votes Against and says:

  Advanced AIs would not be able to accurately explain some of their decisions. AI Verified source (2019)

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  Pedro Domingos

  Professor of computer science at UW and author of 'The Master Algorithm'

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  votes Against and says:

  But it’s potentially disastrous, because there’s often a tradeoff between accuracy and explainability. AI Verified source (2018)

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  Geoffrey Hinton

  Godfather of Deep Learning

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  votes Against and says:

  GH: I’m an expert on trying to get the technology to work, not an expert on social policy. One place where I do have technical expertise that’s relevant is [whether] regulators should insist that you can explain how your AI system works. I think that... more AI Verified source (2017)

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  Peter Norvig

  Computer scientist, AI researcher

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  votes Against and says:

  You can ask a human, but, you know, what cognitive psychologists have discovered is that when you ask a human you’re not really getting at the decision process. They make a decision first, and then you ask, and then they generate an explanation and t... more AI Verified source (2017)

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