Building trust in brittle systems

The Infrastructure of Trust by S. Chung, PhD — Dialogue between Board Chair, Executive Director, and Indigenous Director Executive Director: We’ve built systems—policies, reports, KPIs—yet it still feels like control, not coherence. Why? Board Chair: Fear of failure builds reports. Insecurity builds hierarchy. Few build what truly holds everything together: trust. Indigenous Advisor: And trust is not policy. It’s breath between people. You can’t measure it—but you can feel it when it breaks. Executive Director: Trust sounds like…so soft. Board Chair: It isn’t. It’s structure. When trust holds, people risk truth. When it cracks, strategy dies in polite silence. Indigenous Advisor: In our ways, trust is ceremony—rebuilt through listening until words and actions walk together. Actions for Trust and Listening 1. Budget for Listening — Create pay systems for Elders, meals, and circles. 2. Listening Minutes — End meetings with one truth heard, one not. 3. Relational Reporting — Replace one KPI with a story of restored relationship. 4. Reverse Consultations — Ask partners to grade how we listen. 5. Land-Based Orientation — Begin projects with a land walk. 6. Trust Metrics — Track how fast truth moves from voice to action. 7. Courage Reviews — Ask: When did you tell an uncomfortable truth this year? 8. Silence Logs — The issues avoided are your data. Executive Director: So trust becomes the system? Indigenous Advisor: Yes. When listening changes the plan, you’ve begun to decolonize. With gratitude to Ktunaxa land, colleagues, and to all allies who work through relationship and listening.

I walked into a room full of frustration. The project was off track, the budget was bleeding, and trust had worn thin. As the new project manager, I had 30 days to rebuild what was broken not just the plan, but the relationships. 💡 Here’s the exact trust-building strategy I used to shift the momentum one conversation, one quick win, and one honest update at a time. ▶ Day 1–5: I started with ears, not answers. 🎧 Active Listening & Empathy Sessions I sat down with stakeholders one by one, department by department. No slides. No status updates. Just questions, empathy, and silence when needed. 💬 I didn’t try to fix anything. I just listened and documented everything they shared. Why it worked: They finally felt heard. That alone opened more doors than any roadmap ever could. ▶ Day 6–10: I called out the elephant in the room. 🔍 Honest Assessment & Transparent Communication I reviewed everything timelines, budgets, blockers, and team dynamics. By day 10, I sent out a clear, no-spin summary of the real issues we were facing. Why it worked: I didn’t sugarcoat it but I didn’t dwell in blame either. Clarity brought calm. Transparency brought trust. ▶ Day 11–15: I delivered results fast. ⚡ Quick Wins & Early Action We fixed a minor automation glitch that had frustrated a key stakeholder for months. It wasn’t massive, but it mattered. Why it worked: One small win → renewed hope → stakeholders leaning in again. ▶ Day 16–20: I gave them a rhythm. 📢 Clear Communication Channels & Cadence We set up weekly pulse updates, real-time dashboards, and clear points of contact. No more guessing who’s doing what, or when. Why it worked: Consistency replaced confusion. The team knew what to expect and when. ▶ Day 21–25: I invited them to the table. 🤝 Collaborative Problem-Solving Instead of pushing fixes, I hosted solution workshops. We mapped risks, brainstormed priorities, and made decisions together. Why it worked: Involvement turned critics into co-owners. People support what they help build. ▶ Day 26–30: I grounded us in reality. 📅 Realistic Expectations & Clear Next Steps No overpromising. I laid out a realistic path forward timelines, budgets, trade-offs, and all. I closed the month by outlining what we’d tackle next together. Why it worked: Honesty created stability. A shared plan gave them control. 💬 In 30 days, we hadn’t fixed everything but we had built something more valuable: trust. And from trust, everything else became possible. Follow Shraddha Sahu for more insights

The engineer knew the launch would fail. But no one said a word. “We thought you had it covered.”   I’ve seen programs implode—not from bugs, but from buried risks.   Trust isn’t a soft skill. In complex delivery, it’s infrastructure.   And it’s built—or broken—by how you lead under pressure.   After 100+ high-stakes programs, I’ve learned: Drama doesn’t scale. Quiet systems do. Because when pressure hits, it’s the system—not the slogans—that carries the load.   5 rules I follow to build high-trust, high-performance teams: 🔹 Make risks visible early 🔹 Document like you’ll hand it off tomorrow 🔹 Default to transparency 🔹 Say “I don’t know”—early 🔹 Treat attention like a budget   Quiet, repeatable, and drama-proof—these rules have helped us deliver with speed and clarity, without the fire drills.   Which rule does your team need most right now?   🔁 Know a team where bad news travels slow? Share this. ➕ Follow Rajesh Mathur for delivery + clarity insights.

HOTLINES: THE GRIEVANCE MECHANISM PEOPLE ACTUALLY USE. Safety culture takes more than an annual awareness day. The same truth applies to grievance lines. A phone number on a poster cannot protect anyone unless people trust it. I have walked sites across the Gulf where a “twenty‑four hour ethics line” hangs, faded and untranslated, while real complaints travel by whispered voice note. That gap between policy and lived experience is where reputations unravel. The illusion we keep buying Executives love to say, “We have a hotline.” It sounds neat, measurable, auditable. Yet global research shows only a handful of workers ever pick up, and many who do fear retaliation afterward. A silent line is rarely proof of harmony. More often it signals fear. Design with people, not at them. Any channel workers do not help shape will feel like surveillance. The best ones I have seen were built in workshops that included the very people they aim to protect. Workers chose the language, often voice instead of text, picked an app they already trust, insisted on real anonymity, and demanded a simple guarantee: every report gets a receipt and a follow‑up call. Once that promise was kept, usage rose within weeks. Five choices that build or break trust 1.     Access. If Wi‑Fi disappears after sundown, a web portal will fail. A toll‑free line with a call‑back works better. 2.    Anonymity. Caller IDs must be stripped before any supervisor sees a case. 3.    Speed. A complaint that vanishes teaches silence. 4.   Money. The team logging the case needs the authority and budget to fix the harm, not just file it. 5.    Transparency. Share a quarterly snapshot of issues closed, lessons learned, and fixes funded. When people see change, they speak up more. What the board should ask Boards track injuries, cyber incidents, and cash cycles. They should treat social signals the same way. Know how many reports arrive per hundred employees, how long it takes to resolve them, and how satisfied complainants are. Those three numbers reveal more about organisational health than any glossy pledge. Start small, learn fast Pilot a second intake route in your toughest site, perhaps a WhatsApp voice line. Review the results every month, share what you learn, and scale only what workers rate four stars or higher. Trust builds one honest conversation at a time. Final thought A grievance mechanism is not a compliance badge; it is a mirror. If the reflection comes back empty, investigate. Build a channel your people choose to use, then let the data and the repairs it triggers speak for themselves. That is how risk intelligence turns into real‑world dignity.

“Trust scales change. Say–do consistency lowers noise and resistance, especially when trade-offs bite.” What it really means - Trust is a force multiplier. In low-trust systems, every change requires more explanation, control, and incentives. In high-trust systems, the same change travels on less friction because people grant leaders benefit of intent and competence credit. - Say–do consistency is the engine. When promises match delivery—on time, to spec—people update their internal “leadership reliability score.” Over time, this becomes a shared belief: what leadership says will happen, happens. - Noise = uncertainty. Inconsistency creates prediction errors. People fill gaps with speculation, hedge their effort, and wait. That is the “noise” that drowns execution. - Trade-off moments are the exam. Budget cuts, delayed hires, reprioritized projects these are loss events. If leaders still keep their word (or clearly renegotiate it before the deadline), trust rises. If not, resistance hardens.

Our tech was bulletproof. But voters still didn’t trust it. We built what we thought was the most secure digital voting platform possible: → End-to-end encryption → Blockchain-based ledgers → Multi-factor authentication → Independent audits & compliance → A scalable, bulletproof infrastructure Yet the first question we got wasn’t, “Is your tech solid?” It was, “Will my vote stay anonymous?”, “Can I trust the system?” That’s when it hit us: in public systems, like voting, trust isn’t a feature. It’s the product. Most builders (including us) obsess over scalability, uptime, and security protocols. But real adoption came only when we started prioritizing perception, not just protection.  → We decoupled personal identity from vote history. → Made audit trails transparent without exposing individuals → Ran pilots in schools, universities, and private communities → Let people test—not just the tech. And that changed everything. The biggest barrier wasn’t technological. It was emotional assurance that their vote counted. That no one was watching. That democracy could go digital without compromise. Tech enables trust. But trust activates tech. If you’re building in civic tech, Web3, or digital identity: What are you doing to build belief, not just systems? I’d love to hear—have you ever worked on platforms where tech takes the backseat and trust drives adoption? Share your lessons. Let’s build better—together. #DigitalDemocracy #CivicTech #Blockchain #CyberSecurity #AI #Innovation #EthicalTech #TrustByDesign #StartupLeadership #BallotNow

𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝟱.𝟬: 𝗧𝗿𝘂𝘀𝘁 𝗮𝘀 𝘁𝗵𝗲 𝗖𝗼𝗿𝗻𝗲𝗿𝘀𝘁𝗼𝗻𝗲 𝗼𝗳 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝘆 As Industry 5.0 takes shape, trust becomes the defining factor in securing the future of industrial ecosystems. With the convergence of AI, digital twins, IoT, and decentralized networks, organizations must adopt a structured trust architecture to ensure reliability, resilience, and security. 𝗪𝗵𝘆 𝗶𝘀 𝘁𝗿𝘂𝘀𝘁 𝗰𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗶𝗻 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝟱.𝟬? With the rise of AI-driven decision-making, digital twins, and decentralized networks, industrial ecosystems need a robust trust architecture to ensure reliability, security, and transparency. 𝗧𝗵𝗲 𝗧𝗿𝘂𝘀𝘁 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗳𝗼𝗿 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝟱.𝟬 J. Mehnen from the University of Strathclyde defines six progressive trust layers : 𝗦𝗺𝗮𝗿𝘁 𝗖𝗼𝗻𝗻𝗲𝗰𝘁𝗶𝘃𝗶𝘁𝘆 – The foundation of Industry 5.0 trust. This layer ensures secure IoT networks, smart sensors, and seamless machine-to-machine communication for industrial automation. 𝗗𝗮𝘁𝗮-𝘁𝗼-𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 – Moving beyond raw data, this layer integrates AI-driven analytics, real-time insights, and multi-dimensional data correlation to enhance decision-making. 𝗖𝘆𝗯𝗲𝗿 𝗟𝗲𝘃𝗲𝗹 – The backbone of digital security, incorporating digital twins, simulation models, and cyber-trust frameworks to improve system predictability and integrity. 𝗖𝗼𝗴𝗻𝗶𝘁𝗶𝗼𝗻 𝗟𝗲𝘃𝗲𝗹 – AI-powered diagnostics, decision-making, and remote visualization ensure predictive maintenance and self-learning systems that minimize operational disruptions. 𝗦𝗲𝗹𝗳-𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝘆 – AI-driven systems that self-optimize, self-configure, self-repair, and self-organize, reducing dependency on human intervention. 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝘆 – The highest level of trust, where decentralized computing, autonomous decision-making, and blockchain-based governance eliminate single points of failure and ensure system-wide resilience. 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗧𝗿𝘂𝘀𝘁 𝗶𝗻 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹 𝗔𝗜: 𝗧𝗵𝗲 𝗖𝗼𝗿𝗲 𝗣𝗶𝗹𝗹𝗮𝗿𝘀 To achieve a trusted Industry 5.0 ecosystem, organizations must embrace a structured framework : 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 – Ensuring ethical AI, traceable decision-making, and accountable automation. 𝗥𝗲𝘀𝗶𝗹𝗶𝗲𝗻𝗰𝗲 – Withstanding cyberattacks and operational disruptions. 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 – Protecting data, IoT devices, and industrial networks from cyber threats. 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹𝗶𝘁𝘆 – Ensuring system performance across various conditions. 𝗩𝗲𝗿𝗶𝗳𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆 – Enabling auditability, transparency, and regulatory compliance in automation. 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 & 𝗥𝗲𝗴𝘂𝗹𝗮𝘁𝗶𝗼𝗻 – Implementing policy-driven AI and decentralized oversight mechanisms.  𝗧𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗧𝗿𝘂𝘀𝘁 𝗶𝗻 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗠𝗮𝗻𝘂𝗳𝗮𝗰𝘁𝘂𝗿𝗶𝗻𝗴 As industries embrace AI, smart factories, and autonomous supply chains, trust becomes the new currency of industrial success. Ref :https://lnkd.in/dz998J_6

The better your ML system gets, the more painful its failures become. When a system works 95% of the time, people start to 𝘁𝗿𝘂𝘀𝘁 it. They stop checking. They assume it just works. And then? One strange failure. Unexplained. Misaligned. Just off. And trust is gone. This happens all the time in: - Agent-based systems - RAG pipelines - Customer-facing applications - Even a simple churn model that flags your biggest client by mistake 𝗥𝗲𝗹𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗯𝘂𝗶𝗹𝗱𝘀 𝘁𝗿𝘂𝘀𝘁. 𝗧𝗿𝘂𝘀𝘁 𝗶𝗻𝗰𝗿𝗲𝗮𝘀𝗲𝘀 𝗿𝗶𝘀𝗸. That’s the paradox. 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 𝗿𝗮𝗶𝘀𝗲𝘀 𝗲𝘅𝗽𝗲𝗰𝘁𝗮𝘁𝗶𝗼𝗻𝘀. And when your system slips, it doesn’t feel like a bug.  It feels like a breach of trust. 𝗪𝗵𝗮𝘁 𝗰𝗮𝗻 𝘆𝗼𝘂 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗱𝗼 𝗮𝗯𝗼𝘂𝘁 𝗶𝘁? This is not just for production teams. Even small portfolio projects benefit from this mindset. 𝟭. 𝗗𝗼𝗻’𝘁 𝗷𝘂𝘀𝘁 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗳𝗼𝗿 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆. • Track weird and rare inputs • Tag errors by why they happened, not just how many • Log how users react: ignore, undo, repeat 𝟮. 𝗕𝘂𝗶𝗹𝗱 𝗴𝘂𝗮𝗿𝗱𝗿𝗮𝗶𝗹𝘀 𝗮𝗻𝗱 𝗳𝗮𝗹𝗹𝗯𝗮𝗰𝗸𝘀. • Add a check: if confidence is low, return a safe default • Show a confidence score or quick explanation • Catch hallucinations and infinite loops with basic logic 𝟯. 𝗗𝗲𝘀𝗶𝗴𝗻 𝗳𝗼𝗿 𝘀𝗵𝗶𝗳𝘁𝗶𝗻𝗴 𝘁𝗿𝘂𝘀𝘁. • First-time users need context and safety • Repeat users can become overconfident, so remind them • If your model or data changes, let the user know 𝗜𝗻 𝗼𝗻𝗲 𝗥𝗔𝗚 𝗽𝗿𝗼𝗷𝗲𝗰𝘁, 𝘄𝗲 𝗻𝗼𝘁𝗶𝗰𝗲𝗱 𝘀𝗼𝗺𝗲 𝘂𝘀𝗲𝗿 𝗾𝘂𝗲𝗿𝗶𝗲𝘀 𝘄𝗲𝗿𝗲 𝘁𝗼𝗼 𝘃𝗮𝗴𝘂𝗲 𝗼𝗿 𝗼𝘂𝘁-𝗼𝗳-𝘀𝗰𝗼𝗽𝗲. Instead of letting the system hallucinate, we added a simple check: → If similarity score was low and the top documents were generic, we showed: “𝘚𝘰𝘳𝘳𝘺, 𝘐 𝘯𝘦𝘦𝘥 𝘮𝘰𝘳𝘦 𝘤𝘰𝘯𝘵𝘦𝘹𝘵 𝘵𝘰 𝘩𝘦𝘭𝘱 𝘸𝘪𝘵𝘩 𝘵𝘩𝘢𝘵.” It wasn’t fancy. But it prevented bad answers and kept user trust. Because these systems don’t just run on code. They run on trust. 𝗜𝗳 𝘆𝗼𝘂'𝗿𝗲 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗔𝗜 𝗳𝗼𝗿 𝗿𝗲𝗮𝗹 𝘂𝘀𝗲, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗳𝗼𝗿 𝗮 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗽𝗿𝗼𝗷𝗲𝗰𝘁: → Start small. → Add a fallback → Explain your outputs → Track how your system performs over time These aren’t advanced tricks. They’re good engineering. 💬 What’s one thing you could add to your current project to make it more reliable? ♻️ Repost to help someone in your network.

Trust is the backbone of every system—human or technical. But unlike encryption, there’s no patch for broken trust. In leadership and cybersecurity, trust is your firewall. It’s what keeps the good actors in and the bad actors out. It’s what empowers a team to report a mistake before it becomes a breach. It’s what keeps your people from walking out the door with your IP in their back pocket and a new job offer in the other. But here’s a little something no one likes to say out loud (or actually do): If you’re going to make claims—have the damn receipts. Don’t promise transparency and then ghost your own employees. Don’t preach integrity while covering up the real cause of a security incident. Don’t say “people are our greatest asset” if you treat them like disposable endpoints. Trust is built through policies and people. Through security awareness and psychological safety. Through owning mistakes and not just spinning them into a comms plan. The most dangerous insider isn’t always malicious. Sometimes it’s the loyal employee you burned. Sometimes it’s the one who trusted you… until you made that impossible. So if you want to lead well— If you want to secure not just your systems but your culture— Start here: ✔️Keep your promises. ✔️Document your claims. ✔️Listen like trust depends on it—because it does. ✔️And when trust is broken, don’t pretend it isn’t. Rebuild it. Brick by brick. Because in cybersecurity and leadership, even in personal relationships, once trust is gone the breach is already in progress. Once trust is broken, transparency is no longer optional. You don’t get to rebuild it on vibes. You rebuild it on accountability. You rebuild it by being ruthlessly consistent. You rebuild it by showing—not telling. (Actions speak louder than words!) So if you’re tempted to shade the truth, inflate your credibility, or coast on charm alone, just remember: Trust isn’t given. It’s loaned. With interest. And people are keeping score. #trust #brokentrust #cybersecurity #leadership #spycraftfortheheart

The quality of your technology systems and products simply reflects the quality of your organization. An organization’s culture, specifically the tolerance for contrary ideas and conflicting opinions, directly impacts a system’s quality, its capacity to perform its core function with elegance and flexibility. Teams building these systems must be enabled, even encouraged, to discuss, debate, and push back. In organizations where negative information or contrary opinions are discouraged, architectures proceed often by fiat from the highest paid person’s opinion. Thus if that information flow is stunted, constrained, or otherwise dampened, the resulting system will emerge brittle and fragile in its implementation, unable to anticipate shocks that could overwhelm its capacity. The flow of communication among the teams building a system will be reflected in the end result. We know this from Conway’s Law, long regarded in the systems community, and recently popularized by our friends at Team Topologies. The form of processes and incentives also further shapes the outcomes that teams are able to achieve. How work is organized, the quality of the tooling available, the carrots and sticks leveraged by management, all these impact the end result. We want to build systems that are flexible, reliable, and adaptable—”anti-fragile” even. Since cross-functional collaboration and proper team-based incentives promote a culture of quality in the systems those teams build, teams should be evaluated and rewarded collectively to encourage collaboration and innovation. Leaders should go out of their way to create fora for dissent and debate, not shrink from difficult architecture discussions, but encourage them. Instead, many leaders drive for consensus too early, simply it because it makes them nervous, because they are not confident enough in their own leadership to welcome differences of opinion. Until leaders enable and empower teams to operate like flexible, creative, and cross-functional autonomous units, engaging with each other collaboratively to build the best and most flexible systems possible, we will continue to build and market substandard products, suffer massive outages, and generally waste time and money that could have been put to better use.