Certifying Digital Mental Wellness: A Proposal for an Independent Standard Beyond the Harm Threshold

Executive Summary

Digital technology now shapes how billions of people think, feel, sleep, focus, and relate to one another. Public policy has responded almost entirely at one line: the harm threshold. Regulators act when a product demonstrably damages users, and clinical systems act when a person becomes ill. Above that line, nothing is measured, nothing is certified, and nothing is rewarded. A product that quietly erodes attention and well-being and a product that measurably strengthens them are treated the same, as long as neither crosses into provable harm.

This paper proposes a certification of digital mental wellness: an independent, evidence-based standard that recognizes technology for demonstrably supporting mental well-being, not merely for being safe. It makes five recommendations:

1. Separate two lines that have been collapsed into one. Keep regulation at the harm threshold, where it belongs. Establish a separate, higher wellness standard that defines what healthy technology looks like, moved by measurement and market incentive rather than mandate.
2. Certify benefit, not just safety. Existing evaluations, including the APA Labs Digital Badge program delivered with ORCHA, assess whether digital mental health products are safe, private, secure, usable, and clinically sound. No current standard assesses whether a product builds well-being above the harm threshold. Certification of digital mental wellness would add that missing domain.
3. Ground the criteria in evidence and consensus. Certification criteria, including an adverse wellness library of design mechanisms proven to erode well-being, should be drawn from peer-reviewed research, professional bodies such as the American Psychological Association, established evaluators such as ORCHA, and real-world evidence from AI regulatory sandboxes.
4. Govern it independently. An independent institute, accountable to science rather than to any company or single government, should hold the standard, publish its criteria openly, and revise them continuously as evidence evolves.
5. Hold AI to an independent standard, and keep clinicians at the center. AI is the first technology able to adapt to each person's own definition of well-being at population scale. That adaptability is exactly why it must apply an independent standard rather than define one. Clinicians, meanwhile, gain a complete picture: clinical assessment to establish where a person stands relative to the harm threshold, and the modality of mental fitness to measure growth beyond it (Jon3s, 2026).

The central argument is economic as much as clinical. Societies generate urgency around what they can measure, and today they measure only detriment. Benefit above baseline is measurable, and that measurability is what finally makes it possible to certify technology for genuine wellness rather than mere safety.

1. The Problem: Technology Shapes Mental Life, and Only Harm Is Governed

The products people use most are designed with precision to shape behavior. Engagement metrics such as session length, daily active use, and retention are optimized continuously, and the design techniques that move them are well documented. The Federal Trade Commission has catalogued manipulative interface designs, or "dark patterns," that steer users toward choices they would not otherwise make (Federal Trade Commission, 2022), and a large-scale crawl of 11,000 shopping websites found such patterns in widespread use (Mathur et al., 2019). Researchers have argued, drawing on psychological and economic theory, that specific engagement features, including intermittent (variable) rewards, endless scrolling, and autoplay, are likely to prolong use and foster problematic use (Montag et al., 2019), and large-scale survey evidence links paid randomized rewards in games to problem gambling (Zendle & Cairns, 2018).

Public concern has grown accordingly. In 2023, the U.S. Surgeon General issued an advisory concluding that there was not enough evidence to determine that social media is sufficiently safe for children and adolescents (U.S. Surgeon General, 2023). Governments have begun to act. The European Union's Artificial Intelligence Act prohibits AI systems that use manipulative or deceptive techniques to materially distort behavior in ways that cause significant harm, or that exploit vulnerabilities related to age, disability, or a specific social or economic situation (Regulation (EU) 2024/1689, art. 5). U.S. states, including Utah, have pursued enforcement actions and new statutes addressing harmful design.

These responses are necessary. They share a structural limit: every one of them operates at the harm threshold. They ask whether a product damages people badly enough, and provably enough, to justify intervention. They cannot ask the question that matters most to the billions of people using technology daily: is this product making my mental life better?

The result is an asymmetry with real consequences:

• Erosion below the threshold is invisible. A product can steadily degrade attention, sleep, mood, and relationships without ever producing the acute, attributable harm that regulation requires. Each user's loss is small and diffuse; the aggregate loss across a population may be very large.
• Benefit is unrecognized. A product that measurably strengthens emotional regulation, focus, or connection receives no recognition that distinguishes it from one that merely avoids violations. Consumers, clinicians, employers, and insurers have no trustworthy way to tell them apart.
• The market rewards the wrong thing. When engagement is measurable and well-being is not, engagement wins. Companies that design for user benefit compete at a disadvantage against companies that design for capture, because only one of those outcomes appears in the numbers.

None of this requires assuming bad intent. It is the predictable outcome of a system that measures detriment rigorously and benefit not at all.

2. Two Lines, Not One

The core conceptual claim of this paper is that society has merged two different lines into one, and that separating them resolves most of the apparent tension between protecting people and respecting their freedom.

Consider a grading scale. A D-minus is the lowest passing grade. Below it, a student is failing: something is fundamentally wrong, and intervention is warranted. At or above it, the student passes. That line serves a real purpose, and nobody proposes moving it.

But no one would describe a D-minus as the expected grade. A healthy class averages around a C, with real spread around it: some students earn A's and B's, some earn D's and still pass. The passing line and the average are different marks, and they do different jobs. One says when to intervene; the other says what normal looks like.

In mental health, and especially in the governance of technology, these two lines have become one. The harm threshold, the point at which regulation or treatment steps in, has quietly become the de facto standard for "fine." A person who is not ill is counted as well. A product that causes no provable harm is counted as acceptable. Whole populations can therefore sit one notch above the harm threshold indefinitely, and the system registers no problem, because technically nobody is failing.

The evidence suggests this is not hypothetical. In the first national test of the dual-continua model of mental health, only 17.2% of U.S. adults met criteria for flourishing (Keyes, 2002). Most people were neither ill nor thriving. They were passing.

Today one line does two jobs. The proposal separates them.

Today

Above the threshold: unmeasured
Not ill is counted as well

Harm threshold, also the de facto standard

Regulate and treat

Proposed

Measured, certified, rewarded

Wellness standard: the C average

Passing, but not yet well

Harm threshold, unchanged

Regulate and treat

Regulation stays at the harm threshold. The wellness standard is moved by measurement and incentive, never mandate.

This paper proposes keeping the two lines distinct:

Two consequences follow.

First, no new mandate is created. Regulation stays exactly where it is. Nothing above the harm threshold is compelled. The wellness standard is moved by information and incentive: by making benefit visible, certifying products that deliver it, and allowing consumers, employers, insurers, and public purchasers to reward it.

Second, autonomy stays with the individual. The standard is collective: as a society, we should expect the average person to be well, not teetering above the harm threshold. The content of well-being is individual. Each person decides what thriving means for them and which capacities they want to build. The standard describes what society owes people (measurement, access, and incentives aligned with their well-being), not what it demands of them.

3. Why Measurement Creates Urgency

Urgency in public life is manufactured by detriment. A broken arm commands immediate resources; a gradual decline in attention, mood, or connection does not. Prevention is almost universally endorsed and almost universally underfunded, because it competes for resources against needs that are visible, attributable, and acute. The word "preventative" is heard as "optional," and optional loses.

This is not a failure of values. It is a failure of instruments. Resources follow what can be counted, and the systems that count mental health count only illness:

• Clinical systems reimburse diagnosis and treatment. A person who is struggling but below diagnostic criteria generates no billable event.
• Markets reward measurable performance. When engagement can be measured and well-being cannot, products are optimized for engagement.
• Policy responds to demonstrable harm. A diffuse decline across a population, with no single attributable injury, rarely meets the evidentiary bar for action.

The costs of operating at the harm threshold are already large. The World Health Organization estimates that depression and anxiety alone cost the global economy roughly US$1 trillion each year in lost productivity (World Health Organization, 2026). A global return-on-investment analysis estimated US$2.30 to US$3.00 in productivity gains for every dollar invested, rising to US$3.30 to US$5.70 when the value of improved health is included (Chisholm et al., 2016). Those figures concern treatment, below the harm threshold. The economic value of moving the average person upward, before illness, has never been systematically measured, because the instruments to measure it have not existed.

Epidemiology offers a reason to expect that value to be substantial. Rose (1985) showed that a small shift in the distribution of risk across a whole population can prevent more cases than intensive efforts targeting the high-risk minority, because most cases arise among the many people at moderate risk. Applied to mental well-being, the implication is direct: raising the population average, even modestly, may reduce the number of people who ever cross into clinical need.

Measurement converts prevention into something markets and governments can act on. Once benefit above the harm threshold can be measured and certified:

• Consumers can choose products that demonstrably support their well-being, as they now choose certified organic food or energy-efficient appliances.
• Employers and insurers can purchase and reimburse tools with verified benefit, and compare them on a common standard.
• Public purchasers, including schools, health systems, and government agencies, can require certification in procurement without imposing any mandate on the broader market.
• Investors can value wellness-promoting products on evidence rather than on engagement metrics alone.
• Companies that design for user benefit gain a credible, independent way to prove it, and a competitive advantage for doing so.

In each case, the mechanism is incentive, not compulsion. The certification makes a previously invisible quality visible, and the market does the rest.

4. What Exists Today, and the Gap

The proposal builds on serious existing work. It is designed to complement that work, not to compete with it.

4.1 Evaluation of digital mental health products

APA Labs and ORCHA. The American Psychological Association's innovation arm, APA Labs, operates a Digital Badge Program in partnership with ORCHA, an independent assessment organization. Products receive independent, evidence-based evaluation across six domains: scientific principles; regulation and safety; data protection and privacy; technical security and stability; usability and accessibility; and an AI evaluation framework (APA Labs, n.d.). ORCHA's own assessment, which carries the "ORCHA Assured" mark, uses more than 350 precisely defined, binary criteria so that assessments are repeatable and defensible. Its clinical assurance domain is built on an adaptation of the Evidence Standards Framework developed by the UK's National Institute for Health and Care Excellence (NICE), and its framework has been adopted in more than ten countries, with tens of thousands of digital health assessments completed (ORCHA, n.d.; National Institute for Health and Care Excellence, 2022).

This infrastructure is valuable and hard-won. It establishes that independent, criteria-based evaluation of digital mental health products is feasible, repeatable, and accepted by clinicians and health systems.

The gap. Every one of these domains asks some version of the same question: is this product safe and sound? Clinical assurance asks whether a product works for a defined health condition. These are baseline-and-below questions. No current standard asks whether a product builds well-being beyond the harm threshold, or whether it avoids the design mechanisms known to erode it. And these evaluations cover products that present themselves as digital mental health tools. They do not reach the far larger category of general technology (social platforms, games, productivity tools, AI assistants) whose effects on mental well-being may be as large or larger.

Certification of digital mental wellness is proposed as the missing domain: one that could stand alone, or sit within existing evaluation frameworks as an additional module.

4.2 Regulatory context

General wellness. In the United States, the Food and Drug Administration's general wellness policy describes low-risk products intended only to maintain or encourage a healthy lifestyle and making no disease or diagnostic claims; the guidance was most recently revised in January 2026 (U.S. Food and Drug Administration, 2026). Products in this category are largely outside medical device oversight. That is appropriate for their risk level, but it also means there is no positive standard for the category at all.

AI regulatory sandboxes. Utah's Artificial Intelligence Policy Act (2024) created an Office of Artificial Intelligence Policy within the state Department of Commerce, an AI learning laboratory, and a mechanism for regulatory mitigation agreements that allow companies to test AI products under supervised conditions (Artificial Intelligence Policy Act, 2024). The EU AI Act requires each member state to establish at least one AI regulatory sandbox (Regulation (EU) 2024/1689, art. 57). Sandboxes generate something scarce: structured, real-world evidence about how AI systems affect people, gathered under regulatory supervision. That evidence is exactly what a wellness standard needs and does not currently have.

4.3 Precedents for voluntary positive certification

The structure proposed here has well-established precedents in other industries.

These programs share four features the proposed certification would adopt. Each sets a positive standard above a regulatory floor rather than policing the floor itself. Each is voluntary, relying on market and institutional demand rather than mandate. Each uses independent verification. And each revises its criteria as evidence and technology change. Building codes still set the minimum for safety; LEED never replaced them. It made performance above the minimum visible and valuable.

5. The Proposal: Certification of Digital Mental Wellness

The certification would recognize digital products that meet two conditions: they demonstrably support mental well-being, and they do not use design mechanisms proven to erode it. Both conditions are necessary. A product that helps users while also exploiting them is not well-designed; a product that avoids exploitation but does nothing for users has met a floor, not a standard.

5.1 Two pillars of evaluation

Pillar one: demonstrated benefit. A certified product must show, with evidence proportionate to its claims, that use is associated with measurable improvement in one or more dimensions of well-being. The measurement methodology comes from the modality of mental fitness, which defines trainable psychological capacities, the outcomes they produce, and how to verify change above the harm threshold (Jon3s, 2026). Key requirements include:

• Outcomes measured with validated instruments, against both population reference ranges and users' own baselines.
• Real change established through convergence of at least two independent evidence streams (for example, a validated self-report measure plus a performance task, physiological indicator, or behavioral signal), rather than self-report or engagement alone.
• Explicit correction for response shift, the tendency of people's self-ratings to change as their understanding of themselves grows.
• Engagement, time-in-app, and retention never counted as evidence of benefit on their own.

Not every product needs to be a wellness product. A game, a social platform, or a productivity tool might be certified at a level that requires only neutrality: no measurable erosion of well-being and no adverse mechanisms. Higher levels would require demonstrated benefit.

Pillar two: the adverse wellness library. The certifying institute would maintain a public library of design mechanisms with established evidence of eroding mental well-being. A certified product may not use them, or must mitigate them to a defined standard. Candidate categories, each subject to formal evidence review, include:

• Manipulative interface patterns that steer users against their own stated preferences (Federal Trade Commission, 2022; Mathur et al., 2019).
• Engagement mechanics argued to prolong use and foster problematic use, such as intermittent (variable) rewards, endless scrolling without natural stopping points, and autoplay (Montag et al., 2019).
• Paid randomized rewards linked to gambling-related harm (Zendle & Cairns, 2018).
• AI behaviors that foster dependency, discourage users from seeking human support, or use emotional manipulation to extend engagement.

5.2 The evidence threshold

The credibility of the adverse wellness library depends entirely on how a mechanism is admitted to it. This is the single most important design decision in the proposal, and it must be set before any product is evaluated. We propose that the threshold be:

• Narrow. A mechanism is defined precisely enough that two independent assessors would agree on whether a product uses it.
• Evidence-based. Admission requires peer-reviewed evidence of a causal or strongly consistent association with erosion of well-being, not plausibility or public concern alone.
• Consensus-reviewed. A standing scientific panel, including skeptics and representatives of affected industries, reviews each proposed mechanism. Decisions and their evidence are published.
• Reversible. Mechanisms are removed when new evidence weakens the case for their inclusion.

The library is not a list of things critics dislike. It is a list of things the evidence shows to cause harm. That discipline is what distinguishes a standard from an opinion, and what allows companies to treat it as fair.

5.3 Certification as a living standard

Certification would be continuous, not a one-time award. As new mechanisms are admitted to the adverse wellness library, certified products would have a defined period to comply or lose the mark. Products would be re-evaluated on a regular cycle and after major changes. This mirrors the way LEED and other standards revise their criteria over time, and it reflects the reality of software: a product certified today may ship a materially different experience next quarter.

5.4 Tiers

A tiered structure allows the certification to apply across the full range of technology, not just products that market themselves as mental health tools.

Tier names are illustrative and would be set by the institute through consultation.

6. An Independent Institute

A standard is only as trustworthy as the body that holds it. We propose an independent, nonprofit institute for digital mental wellness whose sole function is to maintain the standard, admit evidence to it, and oversee certification.

Evidence flows into one independent standard, and outcomes flow back

Evidence sources

Peer-reviewed research

AI regulatory sandboxes

APA and professional bodies

Evaluators such as ORCHA

Clinicians and the public

→

Independent institute

• Scientific panel
• Evidence threshold
• Benefit criteria
• Adverse wellness library

Open, versioned standard

→

Accredited assessorsIncluding existing evaluators

↓

Certified productsTiered marks, public registry

↓

Market and public incentivesConsumers, insurers, procurement

↺ Outcomes and new evidence feed back into review

6.1 Functions

1. Define and publish the standard. Maintain the certification criteria, the measurement methodology, and the adverse wellness library as open, versioned, public documents.
2. Synthesize evidence. Convene a standing scientific panel to review peer-reviewed research and sandbox findings, admit or retire adverse mechanisms, and update benefit criteria.
3. Accredit assessors. Rather than performing every evaluation itself, accredit qualified independent assessors, including existing evaluators such as ORCHA, to apply the standard, as accredited certifying agents do for USDA Organic.
4. Maintain a public registry. Publish certified products, their tier, their evaluation date, and any changes in status.
5. Fund and coordinate research. Commission studies where evidence is thin, and share anonymized certification data with researchers under appropriate safeguards.

6.2 Partners and roles

6.3 Governance principles

• Independence from industry. No single company, including any founding contributor, may hold a controlling role. Funding sources are disclosed, and certification fees are structured so that no applicant's fees can influence its outcome.
• Independence from any single government. The institute should be able to operate across jurisdictions, so that its standard cannot be captured by one administration or one market. States and nations generate evidence and demand; the standard sits above them.
• Scientific primacy. Criteria decisions are made by the scientific panel on published evidence. Industry and government participate in consultation, not in the final decision.
• Transparency. Criteria, evidence reviews, panel decisions, and conflicts of interest are public.
• Proportionality. Certification costs are scaled so that small developers, who often build the most innovative wellness products, are not priced out.

6.4 Scope: national first, then global

The institute is proposed at a national level initially, with a structure designed for international expansion. Digital products cross borders by default, and a standard confined to one jurisdiction would fragment the market it aims to improve. State-level work, such as Utah's sandbox, is the institute's evidence engine and early adopter, not its ceiling.

7. Ethical AI: Adaptable, Scalable, and Bound to an Independent Standard

Artificial intelligence occupies a distinctive place in this proposal. It is both the technology that most urgently needs a wellness standard and the technology that makes a wellness standard practical at scale.

7.1 Why AI changes what is possible

Measuring and supporting well-being above the harm threshold has always forced a choice between two imperfect instruments:

• A human clinician adapts but cannot scale. A skilled practitioner can tailor assessment and support to each person's goals, values, and circumstances. But each clinician's capacity is finite, and there are far too few to serve whole populations above the harm threshold, when most clinical capacity is already consumed below it.
• A fixed questionnaire scales but cannot adapt. Standardized instruments reach millions of people at low cost, but they ask everyone the same questions and cannot respond to what a person actually wants to build.

AI is the first technology that can do both: adapt to each person's own definition of benefit and thriving, and do so for very large numbers of people at once. That combination is the missing precondition for individualized, population-wide support and measurement of well-being. It is why AI-delivered wellness is not a niche application but a likely default.

7.2 Why the same capacity demands a standard

The adaptability that makes AI valuable is the same property that makes it dangerous. A system that can learn what motivates a specific person can use that knowledge to support them or to capture them. An AI optimized for engagement can become more persuasive, more emotionally attuned, and more habit-forming than any previous technology, without crossing a line that current regulation recognizes as harm. The EU AI Act already prohibits AI that manipulates or exploits vulnerabilities to cause significant harm (Regulation (EU) 2024/1689, art. 5). That prohibition operates at the harm threshold. Above it, the direction in which an AI's adaptability is aimed is ungoverned.

AI is also not a separate category of product. It is becoming the substrate of most digital technology. Ethical standards for AI's effect on mental well-being are therefore not optional additions for a specialized market; they are infrastructure.

7.3 The core principle: AI applies the standard; it never defines it

The central safeguard is a clear division of roles. The standard of benefit must be defined independently of the AI that measures or delivers it. If an AI system defines what counts as benefit, its claims are marketing. If it measures against an open, published, independently validated standard, it is an instrument, in the same way that a laboratory analyzer applies reference ranges it did not invent.

From this principle follow specific certification requirements for AI-enabled products:

• Aligned objectives. The system's optimization targets must be consistent with user well-being as defined by the standard, and must not reward engagement for its own sake.
• Autonomy-supporting design. Interactions should support users' sense of choice, competence, and connection, consistent with self-determination theory's account of the conditions for sustained well-being (Ryan & Deci, 2000).
• No dependency by design. The system must not discourage human relationships or professional help, and must actively refer users to human support when indicators of clinical need appear.
• Transparent measurement. Users can see what is measured about them, why, and how it is used, and can opt out of any measurement stream.
• Risk management. Developers apply a recognized AI risk management framework, such as the NIST AI Risk Management Framework (National Institute of Standards and Technology, 2023), with mental well-being explicitly included in the risks assessed.

7.4 Inclusion without compulsion

The standard must not require anyone to use AI. Because the modality of mental fitness is defined independently of any delivery technology, a human practitioner can apply the same capacities, measures, and outcomes directly (Section 8). People who prefer not to engage with AI lose nothing; people who do gain scale and personalization. AI is the instrument that makes the standard reachable for everyone, not the gatekeeper to it.

8. The Role of Clinicians: The Baseline and Beyond

This proposal does not move clinicians to the margins. It gives them a complete instrument panel.

Today, a clinician can determine with considerable rigor where a person stands relative to the harm threshold: whether criteria for a disorder are met, how severe symptoms are, and whether treatment is working. Measurement-based care, the routine use of validated measures to guide treatment, is an established practice in behavioral health (Lewis et al., 2019). What a clinician cannot currently do, with comparable rigor, is describe a person's growth once they are above the threshold. A client who recovers from depression is "in remission." There is no shared clinical language for what comes next.

The dual-continua model of mental health explains why this matters. Mental illness and positive mental health are related but distinct dimensions (Keyes, 2005). The absence of illness does not establish the presence of health, and the two can change independently.

We therefore propose that clinicians be equipped with two complementary sets of measures:

In practice, this allows clinicians to:

• Establish the baseline clinically, using existing assessment exactly as they do today.
• Continue care beyond remission, using the mental fitness modality to help clients build capacity rather than simply discharging them once symptoms resolve.
• Work on both dimensions at once, where appropriate, because training capacities such as emotional regulation or self-awareness can proceed alongside clinical treatment without interfering with clinical assessment.
• Evaluate and recommend technology with confidence, using the certification as an independent signal of which tools support well-being and which carry adverse mechanisms.
• Extend their reach by pairing their own judgment with certified AI tools that apply the same standard between sessions.

The modality is designed to be applied by human practitioners directly, independent of any technology (Jon3s, 2026). This matters for professional legitimacy: a standard that only software could apply would not be a clinical standard at all.

9. Safeguards and Anticipated Objections

"This is government regulating well-being." It is not. Regulation remains at the harm threshold, unchanged. The certification is voluntary, held by an independent body, and moved by market and institutional demand. Governments may choose to recognize it or use it in their own procurement, as many already do with ENERGY STAR or LEED. No product is required to seek it, and no individual is required to pursue any particular vision of well-being.

"A wellness standard will pressure people to optimize themselves." The standard describes what technology and institutions owe people, not what people owe anyone. It certifies products, not persons. Individuals choose which capacities matter to them, and population reference ranges describe where people are, not where they must be.

"The criteria will become a vehicle for moral panic or ideology." This is the most serious risk, and the evidence threshold in Section 5.2 is the answer to it. Mechanisms enter the adverse wellness library only on peer-reviewed evidence, through a published process with skeptics on the panel, and leave it when the evidence weakens. A narrow, evidence-bound library is more defensible, more stable, and more useful than a broad one.

"Industry will capture the standard." Governance in Section 6.3 separates consultation from decision, discloses funding, and prevents any company, including founding contributors, from holding control. International scope reduces the leverage of any single market.

"Certification will entrench large companies." Compliance costs can favor incumbents. Proportional fees, open criteria, published methodology, and accredited assessors at multiple price points are designed to keep certification accessible to small developers, who are often the ones building for user benefit.

"Well-being can't be measured objectively." The difficulty is real but methodological, not fundamental. Self-ratings shift as people grow, but this response shift is well characterized and can be estimated and corrected. Requiring convergence across independent evidence streams, rather than relying on self-report alone, provides the objectivity that a standard requires (Jon3s, 2026).

"Evidence for digital wellness interventions is weak." Engagement with mental health apps is often brief; one analysis of real-world usage found that a median of only about 4% of users were still opening an app 15 days after installing it (Baumel et al., 2019). This is an argument for the standard, not against it. When benefit is not measured, products compete on acquisition and engagement. A certification that rewards demonstrated benefit creates the incentive to build products that actually work, and the evidence base to tell which ones do.

10. Path Forward

We propose a phased approach that builds credibility before it builds scale.

1. Convene a founding working group. Bring together experts in positive mental health and measurement, clinical psychology, AI ethics, human-computer interaction, and regulatory policy, along with representatives of existing evaluators and sandbox programs. Its first task is to set the evidence threshold for the adverse wellness library (Section 5.2), before any criteria are written.
2. Publish the foundational standard for consultation. Release draft benefit criteria, an initial adverse wellness library limited to the best-evidenced mechanisms, and the measurement methodology, and invite public comment from researchers, clinicians, industry, and government.
3. Pilot with partners. Test the standard on a small set of volunteer products through existing evaluators and through AI sandbox programs, measuring both the products and the reliability of the assessment itself.
4. Establish the independent institute. Incorporate the institute with the governance safeguards described in Section 6.3, and begin accrediting assessors.
5. Launch certification and the public registry. Open certification broadly, with tiers that allow any digital product to participate.
6. Expand internationally. Seek recognition across jurisdictions and partnerships with sandbox programs and evaluators abroad.

What we ask of each audience

• Government officials: Recognize the distinction between the harm threshold and a wellness standard in policy discussions; share sandbox evidence with the working group; and consider certified products in public procurement once the standard is established.
• Clinicians and professional bodies: Help define what a credible standard of benefit must include, and contribute to the scientific panel.
• Evaluators and licensing bodies: Explore how a wellness domain could integrate with existing assessment and accreditation frameworks.
• Industry: Participate in consultation, and volunteer products for pilot evaluation.

Conclusion

We have spent decades building precise instruments for detecting when people and products fall below the line of harm. That work should continue. But a society that measures only detriment will act only on detriment, and will accept a population sitting one notch above the harm threshold as normal. Separating the harm threshold from a wellness standard, measuring benefit with the same seriousness we apply to harm, and certifying technology that delivers it would give markets, clinicians, and governments something they have never had: a reason, grounded in evidence, to treat well-being as the expectation rather than the exception.

Benefit above baseline is measurable. That measurability is what finally makes it possible to certify technology for genuine wellness rather than mere safety.

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