Build AI That Heals.
Not One That Harms.
Healthcare and public sector leaders partner with Haven AI Collective to build ethical, scalable AI systems their communities can trust—with measurable outcomes and reduced risk.
A complimentary 30-minute conversation to understand your priorities and share how to approach ethical, scalable AI.
“For three decades, I watched organizations race to make technology faster and more efficient (for a select few.) But very few stopped to ask: are we making it wiser for all? That gap breaks trust and leaves communities behind.”
— Brenda Rodgers
Why Responsible AI matters now more than ever
People are stuck. Progress is stalled.
Skill gaps, siloed efforts, and unclear governance leave teams stranded in pilot mode—waiting for clarity that never comes.
Risk is rising—quietly
Without monitoring and guardrails, small failures
become public harm.
Trust hangs in the balance.
When impacted communities and frontline staff don’t shape the process, systems don’t close gaps—they widen them.
Culture is tired of being disrupted.
Without co-design, transformation feels done to
people—not built with them.
70%
of digital transformation initiatives fail to meet their goals, with cultural and organizational barriers cited as the dominant obstacle rather than technical limitations
McKinsey, BCG
89%
of AI algorithms show bias when tested for fairness across demographic groups
Meta-analysis, 2021
18%
of AI practitioners are women, dropping to 3% for women of color
WEF, 2022
55%
of organizations have experienced at least one AI-related incident, yet fewer than half have formal processes to manage or mitigate AI risk
IBM Global AI Adoption Index, 2023
These failures aren’t inevitable.
They’re the result of treating ethics and equity as add-ons instead of infrastructure.
Haven’s Ethical AI Transformation (HEAT) Blueprint
HEAT assesses Human impact, Ethical governance, AI operations, and Trust & accountability—pinpointing what to fix first and why.
You’ll receive a leadership-ready findings report with prioritized actions—not a theoretical scorecard.
What you get:
Assessment of current AI readiness and capabilities, delivered as:
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Current-state scorecard
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Risk & harm hotspots
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Prioritized roadmap
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30/60/90-day action plan
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Check-in calls for questions and course correction
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Email support post-delivery
Delivery: 5 business days depending on organizational complexity
What happens after: You’ll know exactly where you stand, what creates risk or harm, and the three highest-leverage actions to move forward responsibly.
What Makes Haven AI Collective Different
We Center Voices Usually Excluded
As a woman-led consultancy founded by a person with lifelong hearing disability, we bring lived experience of systemic exclusion to every engagement. We don’t just advocate for vulnerable populations—we ensure they shape your AI strategy.
We're Activist-Implementers, Not Academic Observers
We don’t stop at documenting harm—we design systems that prevent it. Your transformation produces measurable equity outcomes, not just prettier performative decks.
We Build Coalitions, Not Dependency
Our goal is to make your team capable of ethical AI leadership without us. We enable and empower skills, not create consulting annuities.
Our Approach
Haven operates across four integrated domains: Consulting transforms governance, workflows, and decision-making from the inside. Education builds workforce capacity for ethical AI. Advocacy shifts industry standards and policy. Media changes how leaders talk about technology and equity.
Each domain strengthens the others, creating sustainable change that outlasts any single engagement.
The Story Behind Haven AI Collective
Meet Brenda Rodgers
About Brenda Rodgers, Founder
I’ve spent my life navigating two worlds: the hearing and the silent.
Growing up with lifelong hearing loss taught me what many leaders learn too late: systems either include or exclude, often without realizing it—and the people designing them rarely feel the consequences.
For 30 years, I’ve led transformation where failure means real harm: Microsoft during DOJ antitrust negotiations. UCSF Health modernizing systems for vulnerable patients. Community health networks during the pandemic, where people’s lives depended on technology working.
The pattern I saw everywhere: Technology fails when it ignores the people using it and the communities affected by it.
The gap I bridge is turning ethics and equity into an operating capability—embedded in
how AI is governed, built, and scaled.
I don’t help organizations talk about ethical AI. I help them build it.
Who This is For
This work is for organizations already using—or actively planning—AI systems that affect people’s lives, rights, or access to care.
Leaders who know AI matters but need clarity on where to start and what to prioritize.
We partner with:
Healthcare & Public Health Leaders
Your AI decisions affect patient safety and community trust. You need AI in care, access, and operations that improves outcomes without widening gaps.
Public Sector Agencies
You’re accountable to constituents, not shareholders.
If AI touches eligibility, prioritization, or enforcement, it must be explainable, defensible, and equitable.
Nonprofits & Social Impact Organizations
Your mission requires technology that serves communities, not extracts from them. You need practical AI that reduces admin burden and expands reach—without compromising trust.
Academic & Policy Partners
You’re advancing research on AI ethics and equity. We help translate research and policy into governance and implementation that organizations can actually run.
If you’re a leader responsible for real people—not just performance metrics—this work is for you.
Blogs
Healthcare & Public Health Leaders
Your AI decisions affect patient safety and community trust. You need AI in care, access, and operations that improves outcomes without widening gaps.
FREE GUIDE
Ethical AI That Scales: Principles for Expanding Reach, Relief, and Resilience
AI doesn’t fail because leaders don’t care about ethics—it fails because ethics aren’t built into how systems are designed, governed, and deployed.
This guide shows you how to start building AI that can scale responsibly in real-world settings.
- A clear starting point: how to assess AI readiness and decide what to do first
- Design choices that matter: where equity, governance, and trust must be embedded early
- The HEAT framework: Human impact, Ethical governance, AI operations, Trust & accountability
- Practical equity checks: questions and signals to identify risk before harm occurs
- From pilots to progress: how to avoid the design traps that stall scale
