Our Foundations

Ethics

Across everything we build

• Accessibility as a Primary Requirement: Accessibility is the starting point, not a retrofit. Every product, piece of content, and service is developed to a neurodivergent-first design standard from inception.
• Ethical Interaction Design: We strictly prohibit the use of dark patterns, manipulation, or coercion across all engagements—including product design, community interaction, and research consent.
• Active Consent by Default: Our systems are built on an “Opt-In” model. Access or participation requires a conscious, deliberate action by the user; we do not enroll users in services or data sharing by default.
• Representative Decision-Making: Neurodivergent perspectives are integrated into the initial stages of the decision-making process for all initiatives that affect the neurodivergent community.

Technology — UMNTech

• Data Sovereignty: We prioritize local-first storage. We do not utilize passive telemetry, behavioral profiling, or the sale of user data.
• Technical Privacy (Zero-Knowledge): Our architecture is designed so that we are technically incapable of accessing your personal data. Privacy is a structural feature, not a toggle.
• Manual-Push Troubleshooting: Data never flows to us automatically. If you initiate a support session, you must manually “push” anonymized logs to us. You decide what is sent and when the connection closes.
• Integrity of Revenue: We do not utilize ad-supported models. We ensure the product remains the priority, not the monetization of the user.
• Operational Validation: Every technical commitment is a verified promise. Features are tested across multiple use cases before release to ensure they perform as stated. We maintain a rigorous quality assurance process and are committed to prompt remediation should a technical failure occur.

Community — UMNTogether

• Independent Infrastructure: UMNTogether operates on infrastructure managed by UnMasking Neurons. Your data is not subject to third-party “big tech” terms of service and is never used to train external AI models.
• Safety-First Moderation: Our moderation standards prioritize the safety and well-being of community members over enforced conformity.
• Anonymity by Default: We view community members as partners in discovery, not subjects. Research participation is anonymized by default; contributors must explicitly opt-in if they wish to be acknowledged by name in published findings.
• Agency and its Limits: Consent is voluntary and reversible. While we will update our internal records and future digital publications to reflect a change in anonymity or participation, we cannot modify data already distributed in physical formats or third-party archives prior to the request.

Science Institute

• Evidence-Based Rigor: Research claims are supported by a minimum of 4–5 independent, peer-reviewed sources. We acknowledge contradicting evidence and prioritize clarity over appearing to have absolute answers.
• Classification of Evidence: We clearly distinguish between peer-reviewed research and lived experience. Every article is classified so users can identify the nature of the evidence provided.
• Clinical Disclaimer: The Science Institute provides educational and research-based content; it does not provide clinical advice or replace professional assessment and support.
• Commitment to Accuracy: As science evolves, we update our content to reflect the most current understanding, maintaining a transparent record of significant changes.

Consulting & Advisory

• Accessibility as a Strategic Standard: Our primary advisory focus is the implementation of neurodivergent-first accessibility across internal and external digital environments. We move beyond basic compliance to ensure that your platforms are functionally usable, meeting legal standards while eliminating the barriers that exclude talent and customers.
• The Security of Clarity: We recognize that inaccessible communication is a systemic vulnerability. Ambiguity in policies and tools undermines organizational standards and leadership. By ensuring that your processes and digital tools are precise and unambiguous, we resolve accessibility failures while simultaneously hardening your operational security.
• Privileged Confidentiality: Client confidentiality is absolute. Information observed during an engagement is never utilized as research material or public content without explicit written authorization and comprehensive anonymization.
• Neutrality of Recommendation: UMN does not accept referral fees or commissions that would incentivize the recommendation of specific vendors. Our guidance is dictated solely by the client’s needs.

The organization

• Systemic Accountability: We prioritize sustainable, ethical outcomes over immediate convenience. We take responsibility for the long-term impact of our decisions.
• Commitment to Rectification: We are committed to transparency. Should we fall short of these standards, we will acknowledge the issue and implement the necessary corrections.
• Universal Application: These standards apply to UnMasking Neurons LLC and all operating divisions—including UMNTech, UMN Consulting & Advisory, the Science Institute, and UMNTogether.

Our Principles

Privacy-first

Data stays on device where possible. No ad-supported model. No passive telemetry. No selling or sharing user data. We are technically incapable of reading your data.

Curb-cut design

Built for neurodivergent users’ most demanding use cases. When you design for the edge case, everyone benefits.

Autonomy-first

No coercion. No dark patterns. No manipulation at any level — product, community, research consent. The default is always no. Opting in requires a conscious, deliberate action. You are never opted into anything on your behalf.

Ripple philosophy

None of us move through the world in a bubble. Our decisions, our actions — they touch the people around us, and sometimes people we’ll never even know. Those are ripples. At UnMasking Neurons, we take responsibility for ours. Every decision we make, we ask what it creates beyond the immediate moment — and we do our best to make sure the answer is something worth sending out into the world.

Privacy

Our commitment

Every wing of UnMasking Neurons is built on the same principle: Your agency is the default. We have designed our architecture so that we are technically incapable of accessing, reading, or utilizing your personal information without your active, manual participation. You maintain absolute sovereignty over your data—across every product and every client engagement.

Across every wing

Technology — UMNTech Your data never leaves your device by default. All AI processing happens on-device. No passive telemetry. No behavioral profiling. If you opt into cloud backup, your data is encrypted on your device before it is transmitted. The server receives only ciphertext it cannot decrypt.

Community — UMNTogether Community data lives on self-hosted infrastructure we own and operate. It is not sold, shared with advertisers, or used to train external models. You own your participation.

Science Institute Research data is anonymized by design. No personally identifiable information is collected or retained. Findings are published in aggregate only.

Consulting & Advisory Client engagements are governed by a Data Processing Agreement. No client data is retained after an engagement closes. Assessment findings are delivered directly to the client and stored nowhere else. Our own infrastructure — the same infrastructure that supports our consulting practice — is zero-knowledge by design.

The technical reality

Layer	How we implement it
Data collection	Minimal by design. No passive telemetry. No behavioral profiling.
On-device processing	AI analysis runs locally. No data sent to cloud for processing.
Encryption at rest	AES-256 encryption on device storage.
Encryption in transit	TLS 1.2/1.3 for all network communication.
Zero-knowledge sync	Client-side encryption before any data leaves the device. Server receives only ciphertext.
Key management	Encryption keys are derived locally from user credentials. We have no “backdoor” or recovery mechanism; if a user loses their credentials, the data remains ciphertext and is irrecoverable by UnMasking Neurons.
Infrastructure	Hetzner, Germany. GDPR-compliant. Annual TÜV Rheinland audit. No third-party data sharing.
Access control	UnMasking Neurons nor their DBAs have access to user data. Zero-knowledge is enforced by technical architecture, not policy.

When data is shared — and only when you choose

Improving the app — optional and opt-in If you choose to contribute anonymized usage data to help improve UMNTech apps, you can opt in at any time. This is never on by default. You can withdraw at any time. No personally identifiable information is included.

Technical support — your logs, your decision If you contact us for technical support and want to share diagnostic logs to help resolve an issue, you initiate that sharing explicitly. We do not have background access to your logs. You choose what to send, when to send it, and the data is used only to resolve your specific issue.

Institutional, educational and clinical deployments

• Provider-Led Support: If a UMNTech app is provided through a school, medical practice, or support program, sharing diagnostic data is still a choice. If a provider is assisting you with technical troubleshooting, you may choose to “push” logs to facilitate that support.
• Structural Privacy: Regardless of who provides the app, our underlying architecture remains zero-knowledge. Your providers and administrators cannot access your personal data through our systems. We are technically incapable of bypassing your local encryption, ensuring your clinical or educational privacy is enforced by code, not just policy.
• Managed Feature Sets: In some institutional settings, administrators may disable certain optional data-sharing features to comply with local privacy regulations (such as FERPA or HIPAA). In these cases, the data is simply never collected; it is not rerouted to the institution.

Children’s data

Children cannot opt in to data sharing. Period. If a UMNTech app is used by a child, all optional data sharing features are disabled regardless of device or account settings. A parent or guardian cannot opt a child in on their behalf. The only data that exists for a child user is what stays on the device.

In all cases: your choice, your control, your data.

Why European infrastructure

Our backup and sync infrastructure is hosted on Hetzner, a German provider operating under EU jurisdiction. This is a deliberate choice. EU law provides stronger statutory protections against compelled disclosure than U.S. law. And because we use zero-knowledge encryption, the physical location of the server is a secondary protection on top of an architectural one. A subpoena returns an encrypted blob no one can read.

For institutional and enterprise partners

Organizations considering UnMasking Neurons products or consulting services can request:

• Data Processing Agreements for EU/GDPR compliance
• HIPAA-adjacent architecture review and BAA upon request
• SOC 2-aligned security documentation
• Open-source code review for security teams (under NDA)

Questions

privacy@unmaskingneurons.com

Research Standards

Article Classification System

Every article published under the Science Institute carries one of three classifications — visible at the top of the article, before the reader begins. No exceptions.

Classification	Description
RESEARCH-BACKED	Claims are supported by peer-reviewed sources. All sources cited. Minimum 4-5 independent peer-reviewed sources per key claim. Contradicting evidence acknowledged where it exists.
LIVED EXPERIENCE	Personal or community narrative. Clearly labeled as such. Not presented as representative of all neurodivergents. Named as the source when used — never dressed up as research.
MIXED	Research-backed framework with lived experience illustration. Both clearly distinguished within the article. Research claims cited. Lived experience sections labeled.

The classification is not a quality ranking. Lived experience is valuable and has a place in the Science Institute. The classification is about honesty — the reader always knows what kind of evidence they’re engaging with.

Source Standards

Source	Types of trusted source
Peer-reviewed journal	Published in PubMed, Frontiers, Nature, ScienceDirect, Philosophical Transactions, Journal of Autism and Developmental Disorders, or equivalent peer-reviewed publication. Highest credibility. Preferred for all science claims.
Books by credentialed researchers	Published by academic or established trade press. Author holds relevant academic credentials. Example: Baron-Cohen’s The Pattern Seekers (Basic Books). Secondary to peer-reviewed journals.
Established research organizations	NIH, CDC, WHO, academic research centers (e.g. Cambridge Autism Research Centre). Used for prevalence data and established clinical definitions.
Original first-person sources	Heather David and UMNTogether community members — clearly identified as lived experience, not research. Used to illustrate, identify questions, and provide community perspective. Never used as proof of a scientific claim.

What does NOT qualify

• Popular science articles, blogs, or listicles — even if they cite real research. Go to the original source.
• Self-reported statistics without a traceable peer-reviewed source
• Social media content, even from credentialed individuals
• AI-generated summaries of research — always verify against the original paper
• Single-source claims — every key argument needs independent confirmation

Minimum source standard per key claim

• 4-5 independent peer-reviewed sources confirming the same finding. Independence matters — sources that all cite the same original paper are not independent confirmation. Where fewer than 4 sources exist, the article acknowledges the limitation explicitly.
• When contradicting evidence exists — and it often does — it is acknowledged. A finding with 4 confirming sources and 1 contradicting source is stronger when the contradiction is named than when it is hidden.
• We verify the primary data source for every citation to ensure that multiple references represent distinct sets of findings, rather than a single study echoed across multiple publications.

How Lived Experience Is Used

Lived experience is not anecdote dressed up as evidence. It is a legitimate and valuable source of knowledge — but only when it is honest about what it is and what it isn’t.

What lived experience can do in UMN research

• Identify questions worth researching — “I experience X, is there research on this?” is a valid starting point
• Illustrate what peer-reviewed findings look like in practice — giving research a human face
• Surface patterns that formal research hasn’t yet studied — pointing toward what needs investigation
• Represent the community perspective on research findings — how this lands for the people it describes

What lived experience cannot do

• Serve as proof of a scientific claim
• Stand in for peer-reviewed evidence where peer-reviewed evidence exists
• Be presented as representative of all neurodivergents — one person’s experience is one person’s experience
• Override established peer-reviewed findings. While lived experience can point to gaps in current research, it is not used to negate statistically significant, replicated scientific data within our Science Institute publications.

Use of Heather David as a source

Heather David is the founder of UMN, a data protection engineer with 20 years of IT experience, and a person with clinician-acknowledged AuADHD patterns. Her lived experience is a primary source for UMN’s founding story, product design decisions, and the questions the Science Institute was built to investigate.

When Heather’s experience is referenced in an article, it is:

• Named explicitly — “based on the founder’s lived experience” not presented anonymously
• Classified appropriately — articles drawing primarily on her experience are classified LIVED EXPERIENCE or MIXED
• Not conflated with research findings — her experience illustrates; the research confirms or refutes

Heather carries clinician-acknowledged patterns consistent with AuADHD without a formal adult diagnosis. This is explicitly framed in all references — the diagnostic system wasn’t built to find people like her, and she is far from alone in that. This framing is itself supported by research on adult ND underdiagnosis, particularly in women.

Use of family members as sources

Heather’s children have formal diagnoses and their experiences have informed her understanding of ND minds from multiple angles — as a parent, as someone who recognized her own patterns through theirs, and as an advocate who fought the systems designed to serve them.

When family experience is referenced:

• It is never identified by name or in ways that would identify specific individuals
• It is used only with consent — explicit, informed, and ongoing
• It is classified as LIVED EXPERIENCE
• It is used to illustrate, not to prove

Science Standards Followed

UMN holds itself to current science communication standards. The Science Institute is not a clinical research institution — it communicates and contextualizes research. These standards govern how that communication happens.

Type of Literature	Descripton
Current literature	Sources are checked for currency. Older foundational papers are valid where the science hasn’t changed. Where newer research contradicts older findings, the newer research is prioritized and the contradiction is noted.
Multiple independent sources	Minimum 4-5 independent peer-reviewed sources per key claim. Independence means each source reached its findings through its own methodology, not by citing the same original paper.
Contradicting evidence	Acknowledged explicitly. A nuanced finding with known contradictions is more credible than a simple finding with contradictions hidden. Where contradicting evidence exists, the article states it.
Correlation vs causation	Clearly distinguished. “ADHD is associated with X” is not the same as “ADHD causes X.” The language in every article reflects this distinction.
Emerging vs established	Findings described as emerging when they come from limited or recent studies. Established findings described as established when replicated across multiple large independent studies.
Sample bias acknowledgment	Where research was conducted primarily on specific populations (e.g. young white boys, specific countries), this is noted. The Science Institute exists partly because this bias has distorted the field.
Not clinical advice	Nothing published by UMN constitutes medical, psychological, or diagnostic advice. Readers are always directed to qualified professionals for individual assessment and support.

What UMN Is Not

Being clear about what UMN is not is as important as being clear about what it is. This section belongs on the How We Research page explicitly.

What we’re not	Descripton
Not a clinical practice	UMN does not diagnose, treat, or provide clinical care. Nothing on this site replaces a qualified clinician. If you are seeking assessment or support, a professional who understands neurodivergence is the right path.
Not providing medical advice	Nothing on this site is medical advice. Research communication about what studies show is not the same as clinical recommendation for any individual.
Not a peer-reviewed research institution	UMN communicates, contextualizes, and advocates based on research. The Science Institute aspires to conduct original community-consented research as it grows — but that research will be clearly distinguished from communication work and held to full academic ethics standards.
Not speaking for all neurodivergents	No single organization, researcher, or platform can speak for the full diversity of neurodivergent experience. UMN speaks from and for its community, with the explicit commitment to expand whose voices are represented over time.
Not infallible	We maintain a public record of significant revisions to previously published content to ensure transparency as the science evolves

Community Research Ethics

When UMNTogether community members contribute to research — through surveys, shared experience, or participation in community-consented studies — these commitments apply without exception.

• Contributors, not subjects — community members who share their experience are contributors to the research, not research subjects. That distinction is not semantic. It changes the power relationship.
• Consent is explicit and specific — not buried in terms of service. Opting into research participation requires a conscious, deliberate action. The default is always no.
• Findings go back to community first — the people whose experience made the research possible see the findings before they are published anywhere else.
• No individual is identifiable — community experience is aggregated and anonymized. No finding is presented in a way that could identify a specific individual.
• Contribution is always voluntary. You may withdraw consent at any time prior to publication. Once findings are published, UMN will remove your contribution from its own platforms upon request, but we cannot modify data already distributed in physical formats or third-party archives prior to the request.
• Plain language summaries — every research finding is communicated in accessible language for the community, not just in academic format for specialists.

The Founder

Who I am

My name is Heather David. I founded UnMasking Neurons because I spent a lifetime looking for what it offers — and it didn’t exist.

The diagnosis gap

I carry the patterns and lived experience of AuADHD and being 2e. The formal diagnostic system wasn’t built to find people like me — but a clinician who worked with my kids looked at me and recognized the same patterns. That moment of recognition meant more than any paperwork could have.

Being 2e means remarkable strengths sitting alongside real challenges — in the same wiring, at the same time. Neither cancels the other out. That’s not a limitation. It’s the full picture — and for most of my life, the world only wanted to see half of it.

Taking the harder route

I’ve spent my life taking the harder route when something needed doing and nothing adequate existed. Fighting to be heard by family, by doctors, by employers. Fighting just as hard for my kids — refusing to accept what I was handed as the final answer, because I knew from living it that there was more to the story than what anyone was willing to put in the paperwork.

The wiring behind the work

In the data security world, what some see as success came from being the person in the room who notices what others walk past. The same wiring that makes the world harder to navigate is what made me good at the work. I’ve never been able to separate the two — and I’ve stopped trying.

Why UMN exist

I believe none of us move through the world in a bubble. Every decision, every action, every word touches the people around us — and sometimes people we’ll never know. Like a pebble dropped in a pond, the ripples span out far beyond where we can see. At UMN, we take responsibility for ours.

The gap for neurodivergents is real and it runs deep. In looking for support, for tools that actually fit, for research that asks the right questions — the resources are limited, misunderstood, or built around the wrong premise entirely. Society is ready to point to every challenge. The full picture — the strengths, the potential, the other side of the coin — gets far less attention. The research that does exist often reaches only as far as the person saying it. The further it gets from the source, the quieter it becomes.

I built UMN to change that. Not to be someone — but to make sure that the people who needed what I needed don’t have to keep looking for something that should already exist.

— Heather David, Founder