Trade-offs in user trust vs experience design

"But it's an extra click" Yes, but would you rather... Click one more time, Or, send money to the wrong person? Click one more time, Or involuntarily see sensitive / graphic content? The truth is, friction still gets a bad rep But less clicks doesn’t always mean a better experience Less clicks doesn’t always mean a quicker journey Less clicks doesn’t always mean easier to use Sometimes that extra step, that extra click, that extra loading state, is good Actually, adding friction can be crucial → It can increase trust → It can reduce mistakes → It can keep people safe How? By giving people control  By enabling them to pause and evaluate their actions → Am I sending money to the right person? → Do I really want to delete all of my photos? → Do I actually want to mass email the company? → Do I want to see that graphic / sensitive content? → Did I mean to add 3 of the same things to my basket? → Do I believe that the system actually did what it said? → Did I create an account with the right details, or now will I be called Emilu? I’m not saying to always add extra steps for the sake of it But, we can’t underestimate the value of slowing people down So, what we can we do? → Map the journey (and system interactions). What decisions can people fly through vs where do we need them to slow down? Are there any destructive actions (like deleting) → Ask what could go wrong and think how it could be prevented. What actions can be make reversible? → Understand people's behaviours. What are they doing, intentionally or unintentionally. What behaviour are we trying to amplify or change? Where can we give more control? → Can we add friction to tailor their experience? It could be as simple as: → Adding an "are you sure prompt" → "Check your details" page at the end of the flow We can't define success by how many times we tap Design for the experience, not for the clicks Design for people, always 💛

I’ve been designing + building products for 20 years. One AI project changed everything I thought I knew. It was 5 years ago. The brief: an AI assistant for financial advisors. "Easy" I thought. I brought the playbook - understand users, map needs, prototype, iterate. Within weeks, every method had failed. User-centred design has given us incredible tools: journeys, personas, usability testing. It created a shared language for innovation and put users at the centre of product development. But it also gave us something dangerous: the illusion that good process guarantees good outcomes. Where design methods break: 🔴 They treat all problems as design problems. Not every challenge needs a workshop. Some need engineering breakthroughs. Some need business model innovation. Some need regulatory change. When your only tool is empathy, everything looks like a user experience problem. 🔴 They assume user needs reveal future possibilities. Advisors thought they wanted better dashboards. Not "AI that predicts my clients needs and anxiety levels". Revolutionary products create needs people didn't know they had. 🔴 Confuses good process with good results. Following the method perfectly doesn't guarantee you're solving the right problem. Great design comes from insight, not adherence to frameworks. What building AI systems has taught me: 🤔 The old tools need rethinking. User research couldn't predict interactions with something that evolves. Journey maps couldn't map AI that creates new paths. Prototypes couldn't capture systems that learn and change. 🤔 The real design challenge isn't the interface - it's the intelligence architecture. Should the system interrupt or wait? Learn from the user or protect their privacy? Optimise for efficiency or explainability? These aren't UX decisions. They're ethical and technical decisions that determine trust, dependency, and agency. 🤔 And critically: AI systems create feedback loops that change user behaviour over time. Traditional design assumes static user needs. AI design requires predicting how your solution will reshape the problem space. We're designing systems that could shape human behaviour for generations. User research and workshops aren't enough anymore. We need a new playbook. What I've learnt: 🟢 Ask "should we?" before "how might we". Consider consequences, not just possibilities. What data does this use? How does it learn? What could break? 🟢 Develop systems thinking. Your decisions ripple through complex networks of technology, behaviour, and culture. 🟢 Design for responsibility, not just iteration. Every design choice becomes a values statement when scaled through AI. 🟢 Question the AI narrative. Not every problem needs an AI solution. Some need better human processes. 🟢 Partner deeply with engineers and data scientists. The best AI experiences emerge from true collaboration, not handoffs. The craft evolves. The responsibility remains the same. Let’s write new rules. Who’s in?

Would you trust a real estate agent who gets kickbacks for every house they recommend? Then why design products that prioritize business goals over user needs? There must be balance. My SIMPLE 6-step framework for being a UX fiduciary: 1. Shield Your Users – Take Responsibility for Their Experience ↳ When you're building interfaces that dance between business goals and user needs, always lead with empathy. ↳ Even when I'm fatigued from remote work Zoom calls, I remember that users feel the same exhaustion. 2. Integrity in Design Decisions – Stand Firm on Ethical Principles ↳ Like I track my workouts strength training, track the ethical impact of every design decision. ↳ The easiest path is rarely the most responsible one. 3. Make Complexity Invisible – Do the Hard Work to Make Things Simple ↳ As a techie who builds AI tool stacks, complexity is inevitable. ↳ But your users shouldn't have to understand the system to use it effectively. 4. Privacy as Default – Protect What Matters Most ↳ Guard user data like it's yours, because someday it might be. ↳ Every piece of data collected should directly benefit the user first. 5. Listen Before Designing – Understand True User Needs ↳ Getting away from screens weekly reminds me that digital experiences should serve human needs. ↳ The best solutions come from observing behavior, not from confirming biases. 6. Educate Your Team – Be the Ethics Advocate ↳ Share your knowledge generously but stand firm on non-negotiable user protections. ↳ Test new tools and approaches, but never at the user's expense. Being a UX fiduciary means putting users' interests first—even when it means pushing back against business pressures. It's about creating trust through integrity, not conversion through manipulation. --- PS: If your design decisions were regulated like financial advice, would you still make the same choices? Follow me, John Balboa. I swear I'm friendly and I won't detach your components.

Not all friction in your core product experience is bad!!! Removing friction isn't the golden rule for growth or a great product design. Many examples of intentional healthy friction that drives growth, builds better early habits, early filtering of high value users. - Depending on the product, adding certain steps during onboarding vs pushing them out within the core product experience could in fact lift overall activation rate and eventual LTV as well - Optimized taste onboarding before early habit creation can lead to a more personalized experience early on, leading to stronger early retention - Of course, a simple confirmation step to review & validate high value trade, may seem an extra step but it builds trust & security for the user Friction isn't the problem -- misplaced friction is. the "context" is key: - Does this additional step help protect the user? - Does it help them make better decisions? - Or does it help product elevate the experience and value for the user? #growth #UX #productDesign #userExperience

Zepto, Blinkit, Instamart: When 10-Minute Delivery Comes With Hidden Costs Dark Patterns in Quick Commerce: Growth Hack or Ethical Red Flag? As Blinkit, Zepto, and Swiggy Instamart face serious allegations of manipulating prices and using dark patterns, it’s a sharp reminder of what unchecked growth in tech can lead to. The bigger concern isn't just about hidden charges or device-based pricing. It is about how design can quietly erode trust, especially when it favours business goals over user experience. 📌 What are dark patterns in this case? Interfaces are built to mislead. Options hidden in plain sight. Prices fluctuate based on the phone you use. Promos added without consent. Loyalty benefits that aren’t auto-applied but hidden behind a small checkbox. These aren’t just flaws. They’re strategic nudges pushing consumers into decisions they didn’t intend. 📌 Why this matters in 2025 more than ever When the cost of building a business is high and investor pressure is mounting, shortcuts seem tempting. But digital trust isn’t a luxury. It is currency. When a consumer feels manipulated, you don’t just lose a sale. You lose future growth. 📌 What can today’s entrepreneurs learn from this? - Scale is not just about faster delivery or bigger numbers. It’s about how responsibly you grow. - Your UI is not just design. It’s a communication tool. If it’s confusing or misleading, it becomes your brand voice. - Transparency is not just a policy. It’s a competitive edge. When you simplify your offering, people trust you more. - Customers don’t just buy convenience. They buy fairness. And fairness should never be an add-on. 📌 And for funded platforms Growth targets should never justify customer exploitation. Every dark pattern you use may help you hit numbers today, but will cost you community tomorrow. Building long-term consumer relationships takes consistency, not clever UI tricks. 📌 For the policy ecosystem As regulators step in, this will set the precedent for how Indian digital businesses are governed in the coming decade. Businesses need to be as innovative in ethics as they are in technology. 📌 For early-stage founders This is a moment to build trust-first businesses. If you are building anything that touches users at scale, ask yourself one thing every time you ship a feature: Is this empowering the user or manipulating them? Because what you design is what you stand for. The question now is simple: is growth worth it if you lose trust on the way? In a world racing for speed, who wins, the one who delivers first, or the one who earns trust forever? #fooddelivery #zepto #blinkit #swiggyinstamart #ecommerce #business

AI systems don’t just reflect the world as it is - they reinforce the world as it's been. When the values baked into those systems are misaligned with the needs and expectations of users, the result isn’t just friction. It’s harm: biased decisions, opaque reasoning, and experiences that erode trust. UX researchers are on the front lines of this problem. Every time we study how someone interacts with a model, interprets its output, or changes behavior based on an algorithmic suggestion, we’re touching alignment work - whether we call it that or not. Most of the time, this problem doesn’t look like sci-fi. It looks like users getting contradictory answers, not knowing why a decision was made, or being nudged toward actions that don’t reflect their intent. It looks like a chatbot that responds confidently but wrongly. Or a recommender system that spirals into unhealthy loops. And while engineers focus on model architecture or loss functions, UX researchers can focus on what happens in the real world: how users experience, interpret, and adapt to AI. We can start by noticing when the model’s behavior clashes with human expectations. Is the system optimizing for the right thing? Are the objectives actually helpful from a user’s point of view? If not, we can bring evidence - qualitative and quantitative - that something’s off. That might mean surfacing hidden tradeoffs, like when a system prioritizes engagement over well-being, or efficiency over transparency. Interpretability is also a UX challenge. Opaque AI decisions can’t be debugged by users. Use methods that support explainability. Techniques like SHAP, LIME, and counterfactual examples can help trace how decisions are made. But that’s just the technical side. UX researchers should test whether these explanations feel clear, sufficient, or trustworthy to real users. Include interpretability in usability testing, not just model evaluation. Transparency without understanding is just noise. Likewise, fairness isn’t just a statistical property. We can run stratified analyses on how different demographic groups experience an AI system: are there discrepancies in satisfaction, error rates, or task success? If so, UX researchers can dig deeper into why - and co-design solutions with affected users. There’s no one method that solves alignment, but we already have a lot of tools that help: cognitive walkthroughs with fairness in mind, longitudinal interviews that surface shifting mental models, participatory methods that give users a voice in shaping how systems behave. If you’re doing UX research on AI products, you’re already part of this conversation. The key is to frame our work not just as “understanding users,” but as shaping how systems treat people. Alignment isn’t someone else’s job - it’s ours too.

Designing for delight is easy. Designing for trust is haarrrddd. I sat down with Adam Iscrupe, Director of Product Design at Boatsetter, and we went deep on how trust is quickly becoming the most critical variable in digital experiences, especially as AI reshapes the way we build and interact with products. Here are a few key takeaways from our conversation: 1. Trust-driven design is the next evolution of UX. As interfaces get easier to build and AI gets more involved, what will separate good experiences from great ones is transparency. Show users why they’re seeing a result, where it came from, and how it’s being used. 2. Personalization without context is creepy. Hyper-personalized experiences only work if users understand the inputs. Clear, contextual trust signals help users feel in control and more open to sharing data. 3. Designing for consent will become table stakes. We’re moving beyond cookie banners. AI-powered experiences will require new ways of asking for permission, communicating data use, and earning the right to personalize. 4. Trust has to work both ways. It’s not just about proving your business is trustworthy. It’s about verifying the customer is real too. In a world of deepfakes and synthetic content, human verification is going to be just as important as identity verification. 5. Delightful experiences happen off-screen too. Adam shared how Boatsetter is thinking beyond just the app or website, like giving customers the ability to extend their trip while they’re still on the boat. The best CX shows up in moments people remember, not just moments they click. We talked about how all of this is reshaping product design, what trust-first UX looks like in the wild, and how design teams should evolve in the age of AI. Catch the full episode below: YouTube - https://lnkd.in/eGfaTN3p Spotify - https://lnkd.in/e3KfZY9A Apple - https://lnkd.in/e3pzX9Za