Category: TDC Update

TDC’s Artificial Intelligence (AI) Policy Principles 

by Mary Grace Cooney

As AI is increasingly integrated into our lives and national infrastructure, The Digital Chamber (TDC) has built policy principles to ensure that these vital systems preserves innovation, resiliency, safety, and a responsible federal-state regulatory harmonization that provides clear direction and protections for relevant stakeholders in the AI ecosystem.  Specifically, the United States must refine regulations to leverage decentralized AI and AI development that supports open and democratic governance – technological remedies to many legacy AI roadblocks and concerns. 

TDC supports the following principles that we intend to use to guide our AI policy engagement: 

1. Mitigating Bias: Bias Audits Should Be Effective, Outcomes-Based, Transparent, and Public 

AI systems should be tested for fair and non-discriminatory outcomes across their full lifecycle, not certified only once at launch.  

TDC supports making bias-audit results available for regulator and public review, with the FTC and state attorneys general able to act where a consistent pattern of failed audits reveals discriminatory outputs. Bias audits should be tied to reasonable mitigation requirements, and at no point should mitigating bias be treated as the introduction thereof. Responsibility for biased outputs should generally rest with the deployer, the entity closest to the person affected, rather than falling equally on every upstream developer. The goal is a standard that measures results, rather than intent, as AI is definitionally incapable of producing ‘intent’ necessary for disparate-treatment claims. 

2. Model Safety: Safety Disclosure Should Scale with Use Case, Not Model Size 

Safety testing should be continuous and include:  

  • pre-deployment evaluation 
  • active monitoring,  
  • an established process for addressing failing systems in real time 

TDC supports disclosure requirements for safety testing results, calibrated to expected use case, user base, and associated risks, rather than model size alone. Systems deployed in healthcare, hiring, housing, or against a vulnerable population should meet a higher bar than a narrow tool with limited exposure, regardless of scale. Risk thresholds should reflect input from the people who bear the consequences of failure, and the workforce that identifies harm(s)deserves protections of its own. 

Further, catastrophic risks have received outsized attention compared to more common violations of user rights and well-being. Both catastrophic and quotidian risks must be addressed. 

3. Liability and Accountability: Accountability Should Follow Supply-Chain Role 

Liability should track function: developers and deployers should each be accountable for harms tied to their specific role, and content-neutral infrastructure providers in a decentralized AI operating system should not be shoehorned into one of these existing categories. 

  • Developers supply capability and are typically liable for defects in the underlying model (e.g., Meta is the developer of the Llama series). A party that modifies an existing model also takes on developer obligations where that modification expands the capability surface, alters the action space, or degrades safeguards; 
  • Deployers refine capability and put it into use. This covers parties that fine-tune a model to narrow it within the intended purposes and documented limitations, and the entity that chooses to place a system into service. Deployers sit closest to the affected person and carry the greatest share of responsibility for outcomes in use. A deployer that narrows a model should publish its intended-use documentation and test for drift within that window; 
  • End Users query or operate an AI system. Where the user and the affected person are the same, accuracy limits are disclosed, and a free and prompt remedy is available, liability should not run upstream for use outside the developer’s/deployer’s stated parameters. This limit does not apply where the affected person is not the operator, as in lending, hiring, housing, healthcare, and criminal justice. 

These categories describe function, not identity, and are not mutually exclusive. A power user self-hosting a model may be developer, deployer, and end user at once. Contractual allocation should not displace the factual distribution of control. 

Obligations also presuppose a party able to discharge them. Where a layer is permissionless and no entity controls access or output, assigning developer or deployer duties there accomplishes nothing or makes recentralization the only compliance path. Accountability should attach to parties exercising control, applied equally to concentrated and distributed infrastructure. 

This chain should also make room for a distinct category of content-neutral infrastructure providers, including decentralized compute, storage, data-availability, and validation networks that do not select or control the models running on them, who should not inherit developer or deployer liability absent knowing participation in a specific harm (see Principle 9). 

Each party should be able to explain the portion of the process it controls, and affected individuals should receive that explanation without requesting it or litigating for it. 

4. Governance and Oversight: Human Oversight Is the Floor; Direct Governance Can Exceed It 

Human oversight of consequential AI decisions – in lending, hiring, healthcare, housing, and criminal justice, among other high-risk domains – remains essential, as is government accountability. 

Where a community (like a blockchain-based AI DAO) holds governance rights, that direct governance can fulfill accountability requirements.  

Worker organizations and unions should be included as participants in setting oversight standards for AI directly impacting workers in a stakeholder model. Agentic AI should inherently carry identification metadata.  

Further, that identification should extend to verifiable tamper-evident action logs, so an autonomous agent’s decisions can be attributed to a responsible party after the fact rather than reconstructed through litigation (see Principle 13). Mechanisms that build oversight directly into execution, such as network-level alignment nodes, illustrate how decentralized systems can make governance a property of the infrastructure rather than an afterthought. 

5. Data Privacy and Sovereignty: Individuals Should Hold a Strong Claim to Their Own Data 

Meaningful, rather than purely symbolic or perfunctory, control over personal and session data is essential.  

Principled data sovereignty requires that people natively own their data. Privacy-preserving infrastructure, like decentralized identity and zero-knowledge methods, can help realize these protections.  

Regulators should treat these privacy-enhancing technologies, including trusted execution environments and confidential computing, secure multi-party computation, and federated approaches, as affirmative compliance pathways deserving of safe-harbor treatment, rather than viewing their use with suspicion. 

Reasonable limits on data brokers and concentrated data control can help enhance privacy where individual-level tools fall short. TDC also supports updated de-identification standards that account for AI-enabled re-identification risk. 

6. Redefining “Democratic AI”: Legitimacy Comes from Governance, Not Governments 

Democratic legitimacy is measured by how directly an AI stack’s power and governance is checked and how widely it is distributed, rather than by which government’s flag sits on a developer’s S1.  

TDC believes AI development should build toward open, auditable, and decentralized AI, governed by meaningful direct input from the people it affects.  Where that level of direct governance isn’t yet possible, legislative direction and generic guardrails can be a reasonable alternative. 

Widespread use of a technology is not the same as widespread control over it. A system available to everyone and governed by one company is not democratic. Democratic AI should embody the following qualities: 

  • Both control and usage are distributed. Many parties can run a system, but that is not the test. What matters is whether any single entity can unilaterally change the model, revoke access, or set the terms everyone else operates under. 
  • The stack is open and forkable. Weights, training data, and code are published under terms that permit modification and redistribution. ‘Open source’ is a necessary but insufficient quality for Democratic AI. 
  • Governance rights are enforceable. People affected by a system can change how it operates. 

Decentralization also carries a resilience and security dividend that policymakers should weigh directly: infrastructure with no single point of control or failure reduces systemic risk and concentrated dependency. Advancing this standard should include interoperability, data and model portability, and open protocols, so that no single incumbent can capture the AI stack through lock-in. 

7. Shared Societal Benefit: Democratizing AI Should Extend to Democratizing Its Gains 

AI-driven labor disruption calls for near-term investment in reskilling and a modernized safety net, tracking impact as it happens rather than after the fact. 

TDC believes that economic gains of AI should be widely distributed through consultation with civil society and affected populations. Workers and communities displaced by AI infrastructure should have a meaningful path to share the benefits of that infrastructure, rather than simply support for the disruption it causes.  

Democratizing AI should extend beyond its oversight to who benefits from the tech, which should itself be decided democratically. Concretely, this can be delivered through verifiable on-chain attribution and micropayments to the people who contribute data, compute, and storage, and through participation in the networks those contributions help run. Such mechanisms distribute gains by design rather than only redistributing them after the fact (see Principle 12). 

8. Verifiable AI: Cryptographic Proof Should Be a Recognized Path to Compliance 

Compliance should be something a regulator can check, rather than something a developer asserts. 

Audits, disclosures, and self-certification all ultimately ask the public to trust the party being regulated. TDC supports recognizing cryptographic verification, meaning proof of what model ran, on what data, and with what result, established through methods such as verifiable inference, provenance attestation, trusted execution environments, and zero-knowledge proofs, as a valid and, where available, preferred means of demonstrating compliance. A standard built on “verify, don’t just trust” lets oversight keep pace with systems too numerous and fast-moving to certify one at a time. 

9. Neutral Infrastructure: Content-Neutral Providers Should Have a Clear Safe Harbor 

Providing the pipes should not mean answering for the water. 

The compute, storage, data-availability, and validation networks that AI runs on are typically content-neutral: they do not choose, train, or control the models they carry. TDC supports a clear safe harbor establishing that operating such infrastructure does not, by itself, make a party a developer or deployer, absent known participation in a specific harm. Without this, the decentralized and distributed infrastructure that makes open AI possible cannot operate at scale in the United States. 

10. Digital Assets: Network-Incentive Tokens Deserve Regulatory Clarity 

Decentralized AI cannot run on infrastructure that has no lawful way to reward its participants. 

Decentralized networks coordinate and compensate their compute providers, storage providers, validators, and other contributors through functional tokens. TDC supports clear federal treatment confirming that tokens used to coordinate infrastructure and reward genuine network participation are not, by default, treated as securities, along with workable clarity for staking and other consensus mechanisms. Resolving this question, now under active debate in digital-asset market-structure legislation, is a precondition for a domestic decentralized-AI industry rather than a matter separate from AI policy. 

11. Open Models: Releasing Open-Weight AI Should Be Presumptively Protected 

Openness is both a safe and competitive strategy. 

Open-weight and open-source models let independent researchers inspect, test, and improve systems that would otherwise be opaque. TDC supports treating the release of open-weight models as presumptively protected, so that a developer is not automatically liable for every downstream use of an openly released model and we are cautious about blanket reporting or restriction regimes aimed at open release. Where safety concerns arise, verifiability (Principle 8) is the better answer than closure: open and verifiable is more accountable than closed and unexamined. 

12. Data Provenance: Contributors Should Be Traceable and Compensable 

If data is the raw material of AI, its providers should be visible in the record and able to share in the value. 

Verifiable data pipelines make it possible to record what data trained a model and to trace contributions back to their source. TDC supports on-chain, privacy-respecting data provenance together with mechanisms for attribution and compensation, including micropayments, to the creators and communities whose data trains AI systems. This advances content authenticity and consent while giving the shared-benefit commitment in Principle 7 a concrete mechanism. 

13. Agentic AI: Autonomous Agents Need Identity, Accountability, and Payment Rails by Design 

As agents begin to act and transact on their own, the accountability layer should be built in up front. 

Autonomous agents increasingly initiate actions and transactions with limited real-time human involvement. TDC supports requiring that agents carry verifiable, portable identity, maintain tamper-evident logs of their actions, and remain attributable to a responsible human or entity, with any agent-to-agent transaction rails designed so that accountability is verifiable rather than reconstructed after harm. Building these guarantees into the infrastructure is the most reliable way to keep an emerging agentic economy answerable to the people it affects. 

If you have any questions, please reach out to policy@digitalchamber.org.  

TDC Submits Response to HFSC Democrats’ Request for Information on AI  

by Mary Grace Cooney

By: Jean-Phillippe Beaudet

On August 14, The Digital Chamber submitted a response to House Financial Services Committee Democrats’ Request for Information on artificial intelligence in financial services and housing. The AI + Quantum Working Group answered more than 30 of the Committee’s questions on explainability, liability, third-party risk, capital markets, housing, data centers, and international development. 

Read our full response HERE. 

TDC’s response makes three arguments: 

First, existing law already covers most of what worries people about AI in finance. The Equal Credit Opportunity Act, the Fair Housing Act, the Fair Credit Reporting Act, and Dodd-Frank’s UDAAP provisions don’t carve out an exception for a decision a model made instead of a person. Congress’s first job is reviving and enforcing the rules already on the books, rather than building a parallel AI-specific regime. 

Second, compliance claims should be provable, rather than asserted by private companies. Tamper-evident action logs, cryptographic attestations, and verifiable model and data provenance records let a regulator or a court confirm which system acted, on what data, and whether the record was altered afterward. None of that replaces governance, testing, or supervision, but it strengthens self-certification with an authoritative audit trail. 

Third, liability should follow function and control, rather than a party’s position in the supply chain. A developer that sets a model’s behavior, and that a deployer can neither inspect nor alter, should answer to the consumer. We also asked Congress for the reverse protection: a safe harbor for content-neutral infrastructure. Compute, storage, and validation networks that carry AI without selecting or training the models running on them shouldn’t be treated as developers or deployers simply for existing, and that protection should apply whether the infrastructure is centralized or distributed. 

Data Centers, Front and Center 

We also weighed in on AI data centers. We asked the Federal Energy Regulatory Commission to assign the transmission and generation costs a large load causes to that load, instead of spreading them across every customer in the region. We asked Congress to give the Energy Information Administration authority to collect mandatory facility-level reporting on power and water use, because fragmentary data reporting obligations leave communities without the information they need to make informed decisions. And we pointed the Committee to decentralized AI architectures, workloads distributed across many smaller machines instead of concentrated in one location, as a way to ease grid pressure and democratize the AI stack. 

Committee Democrats will fold this response into future hearings and legislation on AI in financial services and housing. TDC’s position gives them a path that doesn’t force a choice between protecting consumers and letting the industry keep building: rules that already exist, evidence a regulator can check, and liability that lands on whoever actually controls the outcome. 

Read TDC’s full library of comment letters and reports at www.digitalchamber.org. Questions can be sent to policy@digitalchamber.org.

The Digital Chamber Launches Compute Working Group 

by Mary Grace Cooney

New Digital Power Network initiative will bring industry expertise to federal policy discussions on compute markets and infrastructure. 

WASHINGTON, D.C. — September 24, 2026 — The Digital Chamber (TDC), through its Digital Power Network (DPN), today announced the launch of a ComputeWorking Group to help shape policies affecting the supply, financing, and use of computing capacity. 

The group will bring together companies that build, power, finance, buy, sell, and operate compute capacity, connecting industry expertise directly with federal policy discussions around artificial intelligence, high-performance computing, energy, and data center infrastructure. 

The initiative builds on DPN’s leadership in Bitcoin mining and the deep operational experience its members have developed across energy-intensive digital infrastructure. As demand for compute accelerates, many of the same challenges around power, infrastructure, capital, and market design are increasingly converging. 

“Compute is quickly becoming one of the most valuable resources in the American economy, and the markets that finance and allocate it are still being built,” said Cody Carbone, CEO of The Digital Chamber. “Our members have spent years navigating complex challenges around power, capital, and infrastructure at scale. Our Compute Working Group brings that experience to Washington, so policymakers can get these markets right from the start and keep America at the forefront of the compute economy.” 

The group’s first project will inform TDC’s response to the Commodity Futures Trading Commission’s request for comment on compute derivatives, including computefutures. Participants will help explain how compute markets operate and assess how emerging financial products could support price discovery, manage risk, and facilitateinvestment. 

“Compute policy is already taking shape across financial markets, energy, and infrastructure,” said Zunera Mazhar, VP of Policy and Government Affairs at The Digital Chamber. “We’re focused on bringing the industry’s operational experience to these conversations, starting with derivatives and extending to the energy, infrastructure, procurement, and market standards that will shape how compute markets develop. This work gives policymakers practical insight into how these markets function and what is needed to support investment, innovation, and growth.” 

The working group will also explore:  

  • Compute markets and financial innovation: Policies that support transparent, liquid compute markets, including emerging derivatives, financing tools, and risk management products. 
  • Energy and infrastructure: Power availability, grid interconnection, data center development, and other infrastructure constraints affecting compute growth. 
  • Procurement and market access: Opportunities and barriers for companies seeking to provide compute capacity and services to the federal government. 
  • Standards and market integrity: Frameworks for measuring, verifying, and delivering compute services, including interoperability, performance standards, and emerging distributed compute models.  
  • Through this work, participating companies will help translate operational experience into recommendations for policymakers, bringing the perspectives of infrastructure developers, suppliers, and customers into decisions affecting the compute economy. 

About The Digital Chamber 

The Digital Chamber is a non-profit organization committed to promoting global blockchain adoption. We envision a fair and inclusive digital and financial ecosystem where everyone has the opportunity to participate. Access to digital assets is not merely a technological advancement but a fundamental human right, crucial for economic and social empowerment. Through targeted education, advocacy, and strategic collaborations with government and industry stakeholders, we drive innovation and shape policies that create a favorable environment for the blockchain technology ecosystem. 

The Digital Chamber’s umbrella includes: CryptoUK, Digital Power Network (DPN), TDC’s Digital State Network, and Treasury Council. 

Media Contact: Mary Grace Cooney, Mary_grace@digitalchamber.org; press@digitalchamber.org

From Policy Ask to Policy Win: FinCEN Recognizes Digital Identity for Customer Verification

by Mary Grace Cooney

The Financial Crimes Enforcement Network (FinCEN) and the federal banking agencies have issued new guidance confirming that banks and credit unions may use government-issued verifiable digital credentials—including state-issued mobile driver’s licenses—to verify customers under the Customer Identification Program Rule.

This is an important modernization of federal financial-crime compliance and a direct response to a regulatory clarification The Digital Chamber has repeatedly requested.

Why This Guidance Was Needed

Financial institutions increasingly serve customers through mobile applications and other digital channels, but identity-verification practices often remain rooted in physical documents. Customers may be asked to photograph and upload a driver’s license, transmit sensitive personal information, or rely on authentication methods that are vulnerable to forgery and identity theft.

Mobile driver’s licenses and other verifiable digital credentials offer a more secure alternative. They use cryptographic signatures, device binding, authentication factors, and other safeguards to help institutions determine whether a credential is authentic and belongs to the person presenting it.

Until now, however, regulatory uncertainty limited adoption. Financial institutions needed clear confirmation that these credentials could be used consistently with existing Bank Secrecy Act and Customer Identification Program obligations.

From an Ask to a Win

TDC made that clarification a specific policy priority.

In our comments on Bank Secrecy Act modernization, permitted payment stablecoin issuer requirements, and NIST’s mobile driver’s license implementation guidance, TDC urged regulators to recognize privacy-preserving digital identity and verifiable credentials as legitimate compliance tools.

In May, we publicly called on FinCEN to issue clear guidance explaining how financial institutions could use mobile driver’s licenses and other digital credentials to satisfy BSA and Customer Identification Program requirements. FinCEN has now answered that request.

The new FAQs confirm that an unexpired government-issued verifiable digital credential can qualify as “government-issued identification” under the documentary verification provisions of the Customer Identification Program Rule, provided it contains the required information and the institution has the technology, policies, and procedures necessary to use it.

The guidance also confirms that these credentials may be used when customers open accounts in person, remotely over the internet, or through another digital or virtual channel. In addition, electronic credentials issued by nongovernmental entities may also be used as a non-documentary verification method when the institution ensures an appropriate level of authentication.

Why It Matters

This guidance gives regulated institutions greater confidence to adopt stronger identity technology without waiting for Congress or regulators to rewrite the underlying rule.

Properly implemented, verifiable digital credentials can:

  • Make forged or altered identity documents easier to detect
  • Strengthen remote customer onboarding
  • Reduce dependence on easily copied physical documents
  • Prevent new fraud tactics made widely available by AI
  • Limit unnecessary collection and storage of sensitive information
  • Improve the customer experience while supporting effective compliance

The FAQs do not require institutions to accept digital credentials or create new supervisory expectations. Institutions must still form a reasonable belief that they know a customer’s true identity, address signs of fraud, and incorporate any credential into a compliant risk-based program.

That flexibility is a strength. It allows financial institutions to adopt better tools while preserving responsibility for effective identity verification.

This is how sustained policy engagement produces results: identify a barrier, develop a workable recommendation, place it consistently before the right agencies, and secure clear federal guidance.

TDC thanks FinCEN and the federal banking agencies for recognizing that modern technology can advance compliance, cybersecurity, innovation, and consumer privacy at the same time.

Read the new FinCEN FAQs

Decoding Digital Assets: Empowering Policymakers with Tax Facts 

by Simi Awe

Digital assets are transforming the global economy at lightning speed. Regulators and lawmakers are actively trying to understand these mechanics to establish tax rules of the road, most recently in market structure legislation awaiting the U.S. Senate’s consideration.  

To secure U.S. leadership in digital assets for generations to come, we must address the burdensome nature of the current tax code on companies and consumers, and find a path to tax parity with traditional assets. We must resolve technical ambiguities regarding the timing and sourcing of staking rewards and push back against disproportionate compliance burdens like reward bifurcation.  

Finally, we will ensure that new rules, such as de minimis exceptions, thoughtfully address real-world administrability concerns. By tackling these issues head-on during the upcoming markup and beyond, we will foster domestic capital formation and build a tax code that supports industry growth. 

Advancing Tax Clarity

TDC has worked with the House Ways and Means Committee throughout the current legislative effort to help understand the technology and what kind of tax framework makes sense for consumers and the industry. 

  • In May, we outlined key pillars for a digital asset tax framework in a letter to the committee and reinforced those priorities in a formal statement for the record for June’s hearing. We have also shared technical analysis with legislators on the digital asset taxation legislative package. 
  • Direct Advocacy: Beyond formal submissions, we met directly with the vast majority of Ways and Means offices to advocate for comprehensive, bipartisan solutions conducting over 70 meetings that span more than 50 hours of direct engagement. 
  • Educational Roundtables: We have hosted 7 educational roundtables as part of our ongoing series, providing staffers with the insights needed to navigate this evolving landscape and creating a safe space for deeper questions about the causes and effects of the current U.S. tax structure. 
  • Bicameral Focus: Alongside these House engagements, our advocacy and education efforts in the Senate remain highly active. 

Whether through one-on-one briefings, educational roundtables, or technical documents on high-impact issues like staking, TDC provides lawmakers with an open line to industry experts so they can understand the technology they regulate. Our commitment and engagement ensures that every policy maker can make sound decisions for their constituents and the industry. 

What’s Next  

With the House Ways and Means Committee expected to mark up a digital asset tax package this September, we must maintain engagement to replace ambiguity with statutory certainty to boost tax compliance, protect retail investors, and secure U.S. leadership. 

TDC’s Wins on Bank Secrecy Act Modernization 

by Neil Humphrey

The Digital Chamber is directly impacting the rules taking shape in agencies implementing the GENIUS Act.

On June 22, FinCEN and the federal banking regulators proposed new Customer Identification Program (CIP) requirements for permitted payment stablecoin issuers (PPSIs). The proposal is the latest in a series of rulemakings implementing the GENIUS Act and would establish how stablecoin issuers identify and verify customers.

TDC directly impacted how the proposal has improved, as several provisions reflect policy recommendations from our earlier comments to FinCEN, OFAC, OCC, FDIC, and NCUA.

For example, TDC submitted extensive comments in June responding to FinCEN’s initial PPSI AML/CFT rulemaking and its broader BSA modernization proposal. A central theme of those submissions was that financial-crime obligations should follow the activities an entity actually performs.

  • TDC argued that a stablecoin issuer should have BSA obligations when it directly serves a customer — for example, through issuance, redemption, custody, exchange, or transfer services — but should not be responsible for every downstream transaction simply because it issued the stablecoin being used.
  • We also strongly urged FinCEN to preserve the distinction between financial intermediaries and technology providers. Developers, non-custodial software providers, node operators, APIs, and other neutral infrastructure should not be treated as financial institutions when they don’t accept or transmit value, nor exercise custody or control over customer assets.
  • Finally, TDC encouraged FinCEN to modernize compliance by embracing privacy-preserving digital identity, verifiable credentials, blockchain analytics, AI, and other emerging Regulatory Technology tools.

Wins for Privacy and Safety

The new CIP proposal reflects significant movement toward that framework.

Most importantly, the Agencies propose limiting CIP information collection to primary-market customers who interact directly with the issuer, rather than attempting to impose CIP on secondary-market users. The proposal recognizes that issuers generally lack the customer information needed to identify downstream users and accordingly narrows the proposed customer definition.

The proposal also contains vital protections for developers and decentralized infrastructure. Its definition of “digital asset service provider” excludes distributed-ledger protocols, developers of self-custodial software interfaces, validators and distributed-ledger operators, and certain peer-to-peer liquidity activity.

The proposal recognizes the potential of digital identity, including verifiable credentials such as state-issued mobile IDs and privacy-preserving credentials, and proposes a flexible, risk-based approach to their use.

These principles directly align with what TDC has been advocating for: regulating financial activity without inadvertently regulating the underlying technology and allowing regulated companies to use better technology to achieve stronger compliance outcomes.

Building on the Progress

TDC’s latest response asks agencies to provide greater clarity around account relationships, redemption-only customers, embedded-finance arrangements and third-party reliance, while expanding regulatory certainty for digital identity, blockchain analytics, ecosystem monitoring, AI-enabled compliance, cybersecurity tools, and other innovative compliance technologies.

There is still work to do before the rules are finalized, but we are encouraged by the latest updates and improvements. TDC’s engagement is inserting industry expertise into workable federal policy. The latest proposal demonstrates the value of sustained, technically detailed advocacy — and provides an important foundation for the next phase of GENIUS Act implementation.

Quantum-Proofing Bitcoin: Why BIP-360 and BIP-361 Can’t Wait

by Nicole Rankin

By: Ava Amelio

The Quantum Threat: And Why It Is Growing 

Bitcoin’s security rests on a simple promise: only the owner of a private key can spend the coins tied to it. A cryptographically relevant quantum computer, or CRQC, could break that promise by working backward from an exposed public key to the private key behind it. New research from Google Quantum AI cut the estimated hardware needed to pull this off by roughly 20x, down to fewer than 10,000 physical qubits.1 The same research puts nearly 7 million BTC, close to a third of the supply, in addresses where the public key is already out in the open and ready to attack.2 Two Bitcoin Improvement Proposals, BIP-360 and BIP-361, lay out how the network closes that gap. 

Why This Matters Now More Than Ever  

Bitcoin has no CEO who can push a patch. Every rule change needs miners, node operators, and users to separately choose to adopt it – a process that took years even for widely-supported upgrades like SegWit and Taproot. That slow clock is exactly why the runway needs to open now: the hardware estimates keep shrinking, but the migration path doesn’t get any shorter. A quantum attacker also doesn’t need to hit every wallet at once. One exposed key is enough, and nothing stops the attacker from sitting on stolen funds for months before moving them, timing the theft to avoid drawing notice from chain watchers.3 

  • BIP-360 introduces a new output type, Pay-to-Merkle-Root (P2MR), so newly minted coins never expose a raw public key in the first place. 
  • BIP-361 sets a public deadline for moving already-exposed coins to quantum-resistant addresses, after which the network stops honoring spends from the old, vulnerable signature types. 
  • Together, they cover both the coins Bitcoin hasn’t minted yet and the coins already sitting in the open. 

TDC’s View 

We recommend implementing both BIP-360 and BIP-361. Bitcoin’s coordination problem is also its risk-distribution problem: no central authority can force anyone to upgrade, so the burden of acting falls unevenly. Well-capitalized exchanges and miners can migrate on their own timeline. Retail holders and dormant accounts, including an estimated 1.7 million BTC in wallets whose owners are lost, dead, or simply gone, cannot act at all, no matter how much warning they get. Waiting for a crisis to force the industry’s hand doesn’t spread that exposure more fairly; instead, it leaves ordinary and absent holders exposed while everyone with the resources to move fast does exactly that. A public timeline is what makes the migration workable instead of a scramble, and it’s the best option the network has to protect the self-custody promise that makes Bitcoin worth defending. 

What Happens Next 

BIP-360 and BIP-361 are proposals, not settled code. They still need the community to build consensus, wallets and exchanges to support the new address types, and node operators to adopt the rules that enforce them. We will continue to track the process and keep members briefed as it moves through review, pressing the industry to treat this as a planning problem to solve now, rather than an emergency to manage later. 

TDC Responds to the FTC’s Proposed AI Accuracy Policy

by Neil Humphrey

By Jean-Philippe Beaudet

On July 29, The Digital Chamber’s AI and Quantum Working Group submitted comments to the Federal Trade Commission on its proposed policy statement addressing artificial intelligence accuracy. 

The Proposed Statement treats bias mitigation as potentially deceptive. This premise does not match how AI systems are built, tested, or deployed. Model outputs, instead, reflect the models’ training data and choices of their human designers.  

Our members already run model validation, bias testing, and remediation to meet federal and state law, contractual terms, and enterprise risk standards. Ensuring facial recognition systems supplied to government agencies can recognize all phenotypical indicators equally (they work on both black and white faces) requires fine-tuning models based on expected population demographics, for instance. A policy that casts that work as suspect would put them in conflict with obligations other agencies already impose. 

We advised the Commission that: 

  • There is no universal neutral baseline. Every model output reflects the data and the choices that produced it. Across platforms, countries, and over time, we can see that untreated models, trained on historically biased data, reproduce those biases. The empirical record on lending, hiring, healthcare, and pricing models supports this. 
  • Treating mitigation as deception reverses the logic of Section 5. Consumers expecting neutral, objective outputs would not be served by FTC actions that mandate inaccurate model outputs. Section 5 protects consumers from deceptive practices, unfair competition, and operations that could violate their civil rights protections – like reducing the quality of their response based on their gender. There is a greater risk in presenting an unmitigated system as an objective score than in treating these outputs. 
    • For example, researchers in the world-renowned Nature journal recently found that, “when generating and evaluating resumes, [a leading LLM] assumes that women are younger and less experienced, rating older male applicants as of higher quality.”  
    • As AI is used both to prepare job documents and to review them, this tendency offers a prime example of the risks of unmitigated bias in AI workforce applications.  
  • The Proposed Statement cannot be read apart from the rollback of disparate-impact liability. Disparate impact is a legal concept that refers to a policy or practice that looks fair and nominally treats everyone equally but harms a protected group more than others in practice. In a disparate impact claim, you do not need to prove intention; you only need to show that the final result is unfair. Because AI has neither personhood nor intention, disparate impact treatment is often the only viable route for challenging algorithmic discrimination. 
  • Section 5 should reach material misrepresentations, not mitigation itself. The Commission can pursue firms that misrepresent what their systems do without treating responsible testing as presumptively deceptive. 
  • A reasonable federal floor beats broad preemption. TDC supports harmonization between a coherent national regulatory floor that balances innovation with consumer protections and coordinated state regulation. Industry concerns about regulatory fragmentation can and should be addressed through tiered, multi-state alignment on specific legislative remedies. 

Read the full comment letter here. 

If you have any questions, please reach out to policy@digitalchamber.org. 

Built to Scale: A Blueprint for State-level Blockchain and Emerging Technology Legislation 

by Neil Humphrey

As Congress and federal regulators continue to seek consensus on modernizing rules and developing the right guardrails for digital assets, AI, and blockchain, states across the U.S. are not waiting to adopt their own rules. Across the country, policymakers are developing legislation around these emerging technologies as they understand embracing the potential will attract businesses, create high-paying jobs, and create solutions to make government more efficient, transparent, and profitable.  

But there is a risk: 50 states can also create 50 vastly different rules from state to state. Disjointed legislating can lead to fragmentation and, unintentionally, more uncertainty for innovators in their state. 

The Digital Chamber State Network is sharing model state legislation to help expand best practices at the state regulatory level, designed as an iterative, adaptable tool that can serve as a starting point for policymakers to build informed legislation rather than start from scratch.  

These models provide a constructive foundation that states can adapt to their own needs while promoting greater consistency across the country on the emerging technology issues defining this generation. 

The Digital Chamber’s model legislation page houses our initial library of bills and addresses several of the most important state-level legislative issues, including: 

  • Blockchain & Digital Asset Task Forces to create a structured, informed pathway for states beginning to explore these issues. 
  • Stablecoins & GENIUS Act Comparability to help states think through regulation alongside the emerging federal framework. 
  • Digital Asset Strategic Reserve Funds with clear standards around structure, custody, and eligible assets. 
  • Digital Identity focused on secure identity infrastructure and potential government applications. 
  • Virtual Currency & Money Transmission to promote greater consistency across state licensing regimes. 
  • AI and Deepfake Transparency to adapt a fully transparent and independent way to prove which images and videos are real and which are AI-generated, increasing trust. 

As we continue working with groups at the state level to educate policymakers on the potential of emerging technology, we remain committed to building bipartisan consensus on key issues and bolstering states’ roles in using blockchain’s potential to grow wealth, jobs, and add security and transparency to government to build a brighter economic future for all Americans.  

For the full suite of model bills, visit our website: state.digitalchamber.org/model-legislation. 


Stablecoins Aren’t Emptying Community Banks, Wall Street Might

by Neil Humphrey

There are renewed efforts from certain banking lobbies to reopen what was a closed issue reached through bipartisan compromise on stablecoin rewards in the Clarity Act. Opponents warn that rewards on stablecoins will prompt Americans to withdraw trillions of dollars from community banks, lending will collapse, and Main Street will pay the price. 

In the year since the GENIUS Act, we have seen the opposite effect. Stablecoin adoption has surged while bank deposits have grown. Academic research finds that reasonable stablecoin rewards help banks compete by paying depositors more without reducing aggregate lending. As discussed below, academic research from Cornell, the White House, and Galaxy Research all found that the rise of U.S. dollar-denominated stablecoins also increases deposits in U.S. financial institutions of all sizes.  Stablecoins also do not mechanically remove dollars from banks: GENIUS requires permitted payment stablecoins to hold qualifying reserves, including bank deposits, while substantial stablecoin demand comes from foreign users whose dollars were never held at U.S. community banks. 

Meanwhile, the largest banks are building tokenized deposits that can compete directly for deposits now held by community banks. A dollar converted into a stablecoin may remain in or return to the banking system through reserves. A dollar moved from a community bank into a money-center bank’s tokenized deposit is more direct: the smaller bank loses the deposit, and the larger bank gains it. The debate should therefore focus on evidence and competition, not the most alarming hypothetical which has virtually zero empirical support. 

Background on CLARITY Act Stablecoin Rewards Text 

The current version of the Clarity Act, which the Senate will consider in mid-September, substantially restricts stablecoin yield. Specifically, Section 10404 provides a “Prohibiting Interest and Yield on Payment Stablecoins,” and bars a covered party from directly or indirectly paying interest or yield to a U.S. customer solely for holding payment stablecoins or on a stablecoin balance in a manner “economically or functionally equivalent” to interest on an interest-bearing bank deposit.1 

Clarity tightens regulation on digital asset service providers and affiliates, addressing the purported intermediary “loophole” identified by banking organizations while preserving transaction-based rewards that are not equivalent to deposit interest. This bipartisan compromise, led by Senators Alsobrooks and Tillis after months of negotiations, allowed all stakeholders to participate and provide input. Banks, credit cards, and payment platforms routinely use transaction-based rewards. Stablecoins should not uniquely be prevented from competing the same way. 

The Overwhelming Weight of Academic Authority Rebuts Deposit Flight Narrative  

In an attempt to further restrict how Americans can use their stablecoins, banking groups routinely assert that $6.6 trillion in deposits could be at risk if stablecoin holders receive yield or rewards “drain deposits” and constrict community lending. That is not an empirical forecast of actual deposit flight, but is instead the number of total U.S. domestic deposits.2 The number of domestic deposits at U.S. banking institutions would need to go to zero for that number to be relevant.    

What is relevant is what empirically happens in our banking system when somebody replaces a fiat dollar with a stablecoin dollar. Galaxy Research analyzed likely stablecoin funding sources, and concluded only roughly 30% to 40% of incremental stablecoin funding is likely to come from U.S. bank deposits. $100 of new stablecoin issuance generates approximately $32 of additional U.S. credit, producing about $400 billion in additional credit through 2030.3 That is fundamentally different from assuming every dollar entering a stablecoin is a one-to-one dollar disappearing from a bank because the majority of stablecoin funding is likely to come from offshore demand, physical currency, money-market funds, and other sources.4 

Professor Lin William Cong’s Cornell-affiliated research reaches a similar conclusion. Stablecoins do not mechanically drain deposits. A competitive outside option can instead cause banks to raise deposit rates to retain customers, attracting deposits and increasing lending.5 Bank Policy Institute’s public commentary characterized Professor Cong’s research as evidence that yield-bearing stablecoins could destroy deposits. Professor Cong rejected that interpretation, explaining that the model expressly contains a “competition-dominant” region in which greater stablecoin attractiveness raises deposit rates, deposits, lending, and consumer welfare.6 

Recent history reinforces the difference between deposit reallocation and credit destruction. During the 2022-23 tightening cycle, deposits moved from rate-insensitive institutions toward rate-responsive digital banks. Those receiving banks expanded lending while aggregate credit supply remained broadly stable. 

Finally, the White House commissioned a study into the issue conducted by the White House Council of Economic Advisers, which tested the banking industry’s argument directly and released its findings in April 2026.7 Its baseline estimate found that eliminating stablecoin yield would increase total bank lending by only $2.1 billion, or 0.02%, while imposing approximately $800 million in welfare costs. Community banks would receive only about $500 million of additional lending, roughly 0.026%.  

Even after stacking highly adverse assumptions, there is little-to-no evidence for the claim that permitting stablecoins to earn yield like any other asset has a negative effect on community bank deposits. All available empirical studies instead found that adoption of U.S. dollar stablecoins actually increases deposits across the banking system.  

The Bigger Community-Bank Threat: Tokenized Deposits 

The banking industry’s position also contains an important inconsistency. The nation’s largest banks are currently building digital products to compete for deposits currently held at community banks. 

In June 2026, The Clearing House announced a bank-led on-chain money initiative backed by major financial institutions to enable 24/7 clearing and settlement of tokenized commercial-bank deposits across blockchain networks.8 The Digital Chamber strongly supports banks using blockchain technology, including tokenized deposits, and The Clearing House says its network is intended to be accessible to banks of all sizes. But community banks still need the technology, compliance resources, integrations, and customer reach to compete. Large banks already operate tokenized-deposit platforms and possess obvious advantages in deploying them at scale. 

The distinction matters. When a consumer purchases a stablecoin, the deposit liability may shift to the issuer’s banking relationships, and aggregate deposits depend on how reserves are allocated. Restricting stablecoin rewards while permitting large banks to compete through interest-bearing tokenized deposits therefore does not protect community banks from digital competition. It simply determines who wins it. 


notes:
[1] Digital Asset Market Clarity Act, H.R. 3633, 119th Cong. § 10404(b)-(c) (Lummis Substitute, EHF26654, July 22, 2026) (prohibiting covered parties from paying interest or yield solely in connection with holding payment stablecoins or in a manner economically or functionally equivalent to interest or yield on an interest-bearing bank deposit, while permitting rewards and incentives based on bona fide activities or transactions that are not economically or functionally equivalent to such deposit interest).

[2] American Bankers Association, Bank Policy Institute, Consumer Bankers Association, Financial Services Forum & Independent Community Bankers of America, Closing the Payment of Interest Loophole for Stablecoins  (Aug. 12, 2025) (arguing that stablecoins could produce as much as $6.6 trillion in deposit outflows if interest or yield is available).

[3] Thaddeus Pinakiewicz, Stablecoins, the GENIUS Act, and the Evolving Structure of Dollar Finance, Galaxy Research (May 7, 2026).

[4] See also Lin William Cong, Stablecoins and Banking: Deposit Dynamics, Financial Stability, and Regulatory Design (Dec. 7, 2025, appendix added Jan. 30, 2026). The paper concludes that existing evidence does not show meaningful aggregate deposit outflows attributable to stablecoin adoption and that, under realistic yield conditions, stablecoin competition can encourage more competitive deposit pricing and more efficient liquidity allocation.

[5] Cong, supra note 4. Cong’s model treats stablecoins as a competitive outside option. As their attractiveness increases, banks can respond by increasing deposit rates, thereby attracting deposits and expanding lending and intermediation. Under Cong’s updated calibration, moderate stablecoin yields of approximately 4% to 6% can increase deposit-market competition and expand credit intermediation. Contraction emerges only above roughly 6%, materially above returns available from the short-duration assets backing regulated stablecoins and therefore difficult to sustain economically.
[6] Cong, supra note 4, app. at 32-36. Responding to commentary criticizing the paper, Cong expressly rejects the characterization that meaningful stablecoin adoption necessarily reduces deposits and lending. He explains that the model contains a competition-dominant region in which increased stablecoin attractiveness increases deposit rates, deposits, lending, and consumer welfare.

[7] Council of Economic Advisers, Effects of Stablecoin Yield Prohibition on Bank Lending (Apr. 8, 2026).

[8] The Clearing House, Major Financial Institutions Unveil Bank-Led On-Chain Money Initiative (June 5, 2026) (announcing a bank-led initiative for on-chain clearing and settlement of tokenized commercial bank deposits, including 24/7 settlement and connectivity between blockchain networks and traditional payment rails). See also J.P. Morgan, Deposit Tokens: A Foundation for Stable Digital Money (2026); Citigroup, Citi Achieves Industry First: Integrating Citi Token Services with 24/7 USD Clearing for Real-Time Cross-Border Payments and Liquidity Management (Sept. 29, 2025).