UX Design And Privacy Concerns

Privacy by Design and Default are more than just buzzwords They're fundamental principles that can make or break trust with your users. Yet, many professionals still struggle to grasp their importance. Let me break it down using a timely example from Telegram Messenger: The Good: Privacy by Design Telegram gets it right when it comes to Privacy by Design. Their settings are a masterclass in giving users control, offering three privacy levels for most options: -Everybody - Contacts - Nobody This shows they’ve integrated privacy into the very fabric of their app, giving users the power to decide who sees what (in the design). The Miss: Privacy by Default But here’s where Telegram drops the ball—Privacy by Default. Despite offering granular privacy controls, all options are set to ‘Everybody’ by default. This is a major oversight. Why does this matter? Privacy by Default means that the most secure, private setting should be the default. Telegram should have set all options to ‘Nobody’ by default, allowing users to opt into less privacy if they choose. This approach not only protects users but also demonstrates a commitment to their privacy from the get-go. A Timely Reminder: The recent arrest of Telegram’s CEO highlights the importance of getting privacy right—it’s not just about ticking boxes; it’s about safeguarding your users and the integrity of your platform. In an era where trust is easily lost, these principles are not optional; They are essential. Your Actionable Takeaways: Embed Privacy by Design: Start with privacy as a core principle, not an afterthought. Make it easy for users to control their data. Default to Safety: Always set the most private option as the default. This small step goes a long way in protecting users. Educate and Empower: Make sure your team understands these principles and can apply them. Privacy isn’t just the responsibility of the legal team—it’s everyone’s job. The Bottom Line: In today’s digital landscape, privacy is power. Build it into your product from the start. Always put your users first by defaulting to the most privacy friendly settings. This ensures compliance and also builds a foundation of trust that will set you apart. -----------  👋 I'm Jamal! I want to help you become a world-class privacy expert so you can have the thriving career you deserve. 🔔 Hit that bell for more inspiration, insights and tips. ♻ You've made it this far - so why don't you, repost to your network now so they can benefit too

A hairdresser and a marketer came into the bar. Hold on… Haircuts and marketing? 🤔 Here's the reality: Consumers are more aware than ever of how their data is used. User privacy is no longer a checkbox – It is a trust-building cornerstone for any online business. 88% of consumers say they won’t share personal information unless they trust a brand. Think about it: Every time a user visits your website, they’re making an active choice to trust you or not. They want to feel heard and respected. If you're not prioritizing their privacy preferences, you're risking their data AND loyalty. We’ve all been there – Asked for a quick trim and got VERY short hair instead. Using consumers’ data without consent is just like cutting the hair you shouldn’t cut. That horrible bad haircut ruined our mood for weeks. And a poor data privacy experience can drive customers straight to your competitors, leaving your shopping carts empty. How do you avoid this pitfall? - Listen to your users. Use consent and preference management tools such as Usercentrics to allow customers full control of their data. - Be transparent. Clearly communicate how you use their information and respect their choices. - Build trust: When users feel secure about their data, they’re more likely to engage with your brand. Make sure your website isn’t alienating users with poor data practices. Start by evaluating your current approach to data privacy by scanning your website for trackers. Remember, respecting consumer choices isn’t just an ethical practice. It’s essential for long-term success in e-commerce. Focus on creating a digital environment where consumers feel valued and secure. Trust me, it will pay off! 💰

I’m excited to share our latest working paper, “𝐓𝐨𝐰𝐚𝐫𝐝𝐬 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐢𝐧𝐠 𝐚𝐧 𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐨𝐟 𝐂𝐨𝐧𝐬𝐮𝐦𝐞𝐫𝐬’ 𝐏𝐞𝐫𝐜𝐞𝐢𝐯𝐞𝐝 𝐏𝐫𝐢𝐯𝐚𝐜𝐲 𝐕𝐢𝐨𝐥𝐚𝐭𝐢𝐨𝐧𝐬 𝐢𝐧 𝐎𝐧𝐥𝐢𝐧𝐞 𝐀𝐝𝐯𝐞𝐫𝐭𝐢𝐬𝐢𝐧𝐠”, co-authored with Kinshuk Jerath (Columbia Business School) and Daniel Sokol (University of Southern California). We conducted online experiments with U.S. and European consumers and compared how different ad-targeting strategies affect perceived privacy violations (PPV). Key take-aways - Behavioral targeting (high tracking + individual matching) generates the strongest PPV (Mean = 5.22). - Cutting-edge, on-device privacy-enhancing technologies (PETs) lower PPV only marginally (≈ 4.5), even when targeting is aggregated to groups. - Contextual targeting—ads chosen purely from page content, with no tracking—slashes PPV by ~50 % (Mean = 2.7). - Consumers show virtually the same comfort with untargeted ads (2.1) as with no ads / no tracking at all (1.86). These results echo dual-privacy theory: people value privacy both intrinsically (tracking feels wrong) and instrumentally (risk of personal harm). Technical fixes that focus only on data locality miss the bigger picture—perception matters. A consumer-centric lens is essential for regulators and ad-tech practitioners who want to rebuild trust in the data-driven web. The full paper is available (link in comments). I’d love to hear your thoughts! #Privacy #AdTech #MarketingResearch #PETs #ConsumerInsights #HECParis #ColumbiaBusinessSchool #USC (Figure 1 below: Perceived Privacy Violations across advertising strategies—lower scores are better)

𝐎𝐧𝐞 𝐥𝐞𝐬𝐬𝐨𝐧 𝐦𝐲 𝐰𝐨𝐫𝐤 𝐰𝐢𝐭𝐡 𝐚 𝐬𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 𝐭𝐞𝐚𝐦 𝐭𝐚𝐮𝐠𝐡𝐭 𝐦𝐞 𝐚𝐛𝐨𝐮𝐭 𝐔𝐒 𝐜𝐨𝐧𝐬𝐮𝐦𝐞𝐫𝐬: Convenience sounds like a win… But in reality—control builds the trust that scales. 𝐋𝐞𝐭 𝐦𝐞 𝐞𝐱𝐩𝐥𝐚𝐢𝐧 👇 We were working on improving product adoption for a US-based platform. Most founders would instinctively look at cutting down clicks and removing steps in the onboarding journey. Faster = Better, right? That’s what we thought too—until real usage patterns showed us something very different. Instead of shortening the journey, we tried something counterintuitive: -We added more decision points -Let the user customize their flow -Gave options to manually choose settings instead of setting defaults And guess what? Conversion rates went up. Engagement improved. And most importantly—user trust deepened. 𝐇𝐞𝐫𝐞’𝐬 𝐰𝐡𝐚𝐭 𝐈 𝐫𝐞𝐚𝐥𝐢𝐬𝐞𝐝: You can design a sleek 2-click journey…  …but if the user doesn’t feel in control, they hesitate. Especially in the US market, where data privacy and digital autonomy are hot-button issues—transparency and control win. 𝐒𝐨𝐦𝐞 𝐞𝐱𝐚𝐦𝐩𝐥𝐞𝐬 𝐭𝐡𝐚𝐭 𝐬𝐭𝐨𝐨𝐝 𝐨𝐮𝐭 𝐭𝐨 𝐦𝐞: → People often disable auto-fill just to manually type things in.  → They skip quick recommendations to do their own comparisons.  → Features that auto-execute without explicit confirmation? Often uninstalled. 💡 Why? It’s not inefficiency. It’s digital self-preservation. It’s a mindset of: “Don’t decide for me. Let me drive.” And I’ve seen this mistake firsthand: One client rolled out a smart automation feature that quietly activated behind the scenes. Instead of delighting users, it alienated 15–20% of their base. Because the perception was: "You took control without asking." On the other hand, platforms that use clear confirmation prompts (“Are you sure?”, “Review before submitting”, toggles, etc.)—those build long-term trust. That’s the real game. Here’s what I now recommend to every tech founder building for the US market: -Don’t just optimize for frictionless onboarding. -Optimize for visible control. -Add micro-trust signals like “No hidden fees,” “You can edit this later,” and clear toggles. -Let the user feel in charge at every key point. Because trust isn’t built by speed. It’s built by respecting the user’s right to decide. If you’re a tech founder or product owner: Stop assuming speed is everything. Start building systems that say, “You’re in control.” That’s what creates adoption that sticks. What’s your experience with this? Would love to hear in the comments. 👇 #ProductDesign #UserExperience #TrustByDesign #TechForUSMarket #DigitalAutonomy #businesscoach #coachishleenkaur Linkedin News LinkedIn News India LinkedIN for small businesses

Here are 3 predictions for the future of UX. We talk enough about AI and the big tech trends of the 2020s, but here’s my big-picture perspective on how they’ll actually reshape UX. 🔮 Anticipating user needs before they exist With tech like applied AI, you can ideate, test, prototype and code and market a new app at record speeds. When product moves so fast, it also means competition. Just look at any App store, there are about 100 different apps for any user need or niche. Everyone can build the same features in a couple weeks. User expectations on features / capabilities for products will also go up. To stand out in such a market, you’ll need to ship even faster to meet current AND future user needs. Products that win will live in the future even more and anticipate based on the user’s problems the capabilities they WILL want, not just what they’re asking for today. 🧭UX-ers will become strategic discovery guides AI's speeding up research workflows already. It can transcribe, code data and take notes faster than human assistants. Figma plugins are auto-generating UI components, and tools like Voiceflow are building conversational prototypes in minutes. Here’s our AI research assistant btw: https://bit.ly/4dAc3O0 So what’s left for the human researchers and designers? More strategy, high-impact questions, and facilitating org-wide discovery frameworks. With more cross-functional teams, UXRs will need to shift tactical, low-impact studies to non-researchers to run themselves. Research methodology may shift to more strategic questions to help teams anticipate user needs. Think decision-maker’s table product strategy and design frameworks, not just testing prototypes  or running usability tests. 🛡️Increasing wariness about big tech Users are more wary of big tech in this era. Just look at the rise in privacy blockers, cybersecurity solutions and activism around the impunity of big tech.  Trust may become the new UX currency. This could look like baking privacy and security considerations into every step of the design process. Transparency is crucial. We'll need to be designing clearer data dashboards, more intuitive permission flows, and ethical AI explainability features. UX interactions will focus heavily on building trust. Every UX decision will need to reinforce data ethics. We go into more detail on these predictions in our latest blog post on the future of UX: https://bit.ly/4dVxl8S Do you agree with my predictions? I want to know what you think! #futureofux

Over the past few months, I’ve noticed a pattern in our system design conversations: they increasingly orbit around audio and video, how we capture them, process them, and extract meaning from them. This isn’t just a technical curiosity. It signals a tectonic shift in interface design. For decades, our interaction models have been built on clickstreams: tapping, typing, selecting from dropdowns, navigating menus. Interfaces were essentially structured bottlenecks, forcing human intent into machine-readable clicks and keystrokes. But multimodal AI removes that bottleneck. Machines can now parse voice, gesture, gaze, or even the messy richness of a video feed. That means the “atomic unit” of interaction may be moving away from clicks and text inputs toward speech, motion, and visual context. Imagine a world where the UI is stripped to its essence: a microphone and a camera. Everything else, navigation, search, configuration, flows from natural human expression. Instead of learning the logic of software, software learns the logic of people. If this plays out, the implications are profound: UX shifts from layouts to behaviors: Designers move from arranging buttons to choreographing multimodal dialogues. Accessibility and inclusion take center stage: Voice and vision can open doors, but also risk excluding unless designed with empathy. Trust and control must be redefined: A camera-first interface is powerful, but also deeply personal. How do we make it feel safe, not invasive? We may be on the cusp of the first truly post-GUI era, where screens become less about control surfaces and more about feedback canvases, reflecting back what the system has understood from us.

Most companies are breaking the law before the user even sees a cookie banner. The German courts have just confirmed what many privacy engineers have known, and what most compliance teams have tried not to look at too closely: Google Tag Manager is illegal in the EU without prior, valid consent. The court’s ruling (VG Hannover, 10 A 5385/22) makes it explicit: • GTM contacts US servers before consent • Injects scripts and stores data on devices pre-consent • Enables shadow tracking through third-party payloads • And the IAB TCF-based CMP in use was deemed non-compliant This isn’t just a German regulatory footnote. It’s a strategic signal, one that cuts through the haze of “consent mode” PR and forces us to confront a deeper truth: You cannot enforce privacy at runtime using tools designed to avoid it. Here’s the fundamental flaw: Most organizations use GTM to load their CMP. Which means: by the time a user sees the consent dialog, tracking has already started. Consent isn’t controlling tracking, here tracking is controlling consent. This creates a legal paradox and an engineering nightmare: • Your compliance posture depends on a script you can’t see • Your user experience depends on a framework you don’t control • And your data risk is abstracted away in layers of third-party complexity This ruling doesn’t just clarify the law. It exposes the architecture. What to do instead? A strategy, not a workaround: 1. Stop treating consent as a UI problem. It’s an infrastructure problem. The logic must live in your backend — not a banner. 2. Deploy a first-party trust layer. Your consent logic, your enforcement primitives, your systems. Not Google’s. 3. Load nothing until consent is confirmed. Not GTM, not Consent Mode, not SDKs. If it calls home, it waits. 4. Monitor for "shadow loading." If third-party vendors can execute before policy runs, you’ve already lost. At Ethyca, this is why we built Janus. It’s not a banner. It’s a programmable control plane for consent. It doesn’t “ask for permission”, it enforces policy before any code is touched. You can’t leverage your data or build trustworthy AI at enteprrise scale without lawful, explicit user intent, resolved and enforced at the infrastructure layer. The court has made its ruling. Now, so must enterprise data architecture. Want to talk about what a real trust layer looks like and what it means to turn policy into code? We’re building it every day. Book a conversation and let’s talk about what real compliance looks like at scale. #PrivacyEngineering #AIInfrastructure #GDPR #ConsentManagement #GTM #DataGovernance #Ethyca #TrustLayer #TTDSG #Fideslang #DigitalSovereignty

Consent Management Blueprint under India’s DPDP Act is out As businesses prepare to operationalize the Digital Personal Data Protection Act (DPDP Act), MeitY has released a detailed Business Requirements Document (BRD) for Consent Management Systems (CMS). This non-binding BRD sets out the key functional and technical requirements that organizations should incorporate into their consent workflows to enable a user-centric and transparent data governance framework - with ‘consent’ being the cornerstone for processing personal data under Indian law. 🔍 What does the BRD for CMS cover? ✅ Consent must be purpose-specific, granular, and based on explicit affirmative action; ✅ Users must be able to view, update, renew, or withdraw consent at any time; ✅ Real-time APIs must validate consent before processing any personal data; ✅ Web and app interfaces must implement cookie banners with granular controls—only essential cookies can be enabled by default; ✅ Built-in grievance redressal, multilingual support, and activity logging; and ✅ Immutable audit logs with metadata and cryptographic hashes for accountability. Whether you’re a data fiduciary or a data processor, this is the consent architecture that will help you ensure compliance with the DPDP Act. 🕒 While the DPDP Act is yet to come into force, the direction is clear. If your systems aren’t already being aligned - now is the time to act. #DPDP #ConsentManagement #DataProtection #PrivacyCompliance #MeitY #IndiaPrivacyLaw #DigitalIndia #DataGovernance

Data Exposure from LLM Apps: An In-depth Investigation of OpenAI’s GPTs LLM app ecosystems are quickly maturing and supporting a wide range of use cases, which requires them to collect excessive user data. Given that the #LLM #apps are developed by third-parties and that anecdotal evidence suggests LLM platforms currently do not strictly enforce their policies, user data shared with arbitrary #third-#parties poses a significant #privacy #risk. In this paper we aim to bring transparency in data practices of LLM apps. As a case study, we study #OpenAI’s #GPT app ecosystem. We develop an LLM-based #framework to conduct the static analysis of natural language-based source code of #GPTs and their Actions (external services) to characterize their data collection practices. Our findings indicate that Actions collect expansive data about users, including sensitive information prohibited by OpenAI, such as passwords. We find that some Actions, including related to advertising and analytics, are embedded in multiple GPTs, which allow them to track user activities across GPTs. Additionally, co-occurrence of Actions exposes as much as 9.5× more data to them, than it is exposed to individual Actions. Lastly, we develop an LLM-based privacy policy analysis #framework to automatically check the consistency of data collection by Actions with disclosures in their #privacy #policies. Our measurements indicate that the disclosures for most of the collected #data #types are omitted in privacy policies, with only 5.8% of Actions clearly disclosing their data collection practices. Centro de Investigación de Ciberseguridad IoT - IIoT

Why do users stay engaged with health apps — even when sharing sensitive personal health information? Our recent study reveals fascinating insights into what motivates users of women's health apps to remain actively engaged, even when privacy concerns could pose barriers. Using Privacy Calculus Theory, we explored how perceived privacy risks, benefits to oneself (personal health management), benefits to others (contributing to scientific research), and trust affect user engagement. Analysing survey responses and app usage data from over 350 active users, here's what we found: ✅ Perceived benefits to others significantly boosted app engagement, both in terms of longer sessions and broader usage of app features. Users were motivated by the idea that their participation contributes to advancing scientific research and improving healthcare for future patients. ❌ Surprisingly, trust, privacy risks, and self-benefits (personal health improvement) did NOT significantly predict sustained user engagement. These results highlight a powerful insight: when users see clearly how their data positively impacts broader scientific or community goals, they’re more inclined to stay actively involved. For mHealth designers, strategists, and product managers, this emphasises the importance of clearly communicating the societal and research value of user participation — not just personal health benefits. Curious to dive deeper? Check out our full study published in Behaviour & Information Technology! Thank you for excellent collaboration, FEMaLe project, Georgios Tsirozidis, and Michael Zaggl. #DigitalHealth #mHealth #Privacy #Engagement #HealthApps #Research #UserExperience #PrivacyCalculus #PCT #WomensHealth #Endometriosis Health - Aarhus University Aarhus BSS - Aarhus University PhaseV Health studies Trine Rolighed Thomsen Ida Hestbjerg IHI READI https://lnkd.in/d4Fwav_b