Innovative Design Labs

☂️ Designing For Edge Cases and Exceptions. Practical design guidelines to prevent dead-ends, lock-outs and other UX failures ↓ 🚫 People are never edge cases; “average” users don’t exist. ✅ Exceptions will occur eventually, it’s just a matter of time. ✅ To prevent failure, we need to explore unhappy paths early. ✅ Design full UI stack: blank, loading, partial, error, ideal states. ✅ Design defaults deliberately to prevent slips and mistakes. ✅ Start by designing the core flow, then scrutinize every part of it. ✅ Allow users to override validators, or add an option manually. ✅ Design for incompatibility: contradicting filters, prefs, settings. 🚫 Avoid generic error messages: they are often main blockers. ✅ Suggest presets, templates, starter kits for quick recovery. ✅ Design extreme scales: extra long/short, wide/tall, offline/slow. ✅ Design irreversible actions, e.g. Delete, Forget, Cancel, Exit. ✅ Allow users to undo critical actions for some period of time. ✅ Design a recovery UX due to delays, lock-outs, missing data. ✅ Accessibility is a reliable way to ensure design resilience. Good design paves happy paths for everyone, but also casts a wide safety net when things go sideways. I love to explore unhappy paths by setting up a dedicated design review to discover exceptions proactively. It can be helpful to also ask AI tooling to come up with alternate scenarios. Once we start discussing exceptions, we start thinking outside of the box. We have to actively challenge generic expectations, stereotypes and assumptions that we as designers typically embed in our work, often unconsciously. And to me, that’s one of the most valuable assets of such discussions. And: whenever possible, flag any mentions of average users in your design discussions. Such people don’t exist, and often it’s merely an aggregated average of assumptions and hunches. Nothing stress tests your UX better then testing it in realistic conditions with realistic data sets with real people. Useful resources: How To Fix A Bad User Interface, by Scott Hurff https://lnkd.in/ecj6PGPU How To Design Edge Cases, by Tanner Christensen https://lnkd.in/ecs3kr8z How To Find Edge Cases In UX, by Edward Chechique https://lnkd.in/e2pfqqen Just About Everyone Is an Edge Case, by Kevin Ferris https://lnkd.in/eDdUVHyj Edge Cases In UX, by Krisztina Szerovay https://lnkd.in/eM2Xynba Recommended books: – Design For Real Life, by Sara Wachter-Boettcher, Eric Meyer – The End of Average, by Todd Rose – Think Like a UX Researcher, by David Travis, Philip Hodgson – Mismatch: How Inclusion Shapes Design, by Kat Holmes #ux #design

When I introduce myself as a systems designer, a curious question often pops: What's the difference between design thinker and systems designer? In my experience, design thinking is zooming in. It's all about understanding people's needs and creating solutions that work for them. Systems thinking, on the other hand, is like zooming out. In other words, stepping back to see the big picture. Design Thinking: • Human-centered approach • Focuses on customer desirability, solution feasibility, and business viability • Iterative process of understanding, ideation, prototyping, and validation Systems Thinking: • Holistic approach to complex problems • Examines interconnections between parts, dynamics, and paradigms. • Considers structures, relationships, and cultural factors As a systems designer, I integrate both approaches. I start with a systems perspective to understand the big picture, then zoom in on human aspects. This combination has consistently led to innovative and effective solutions in product design. It's not about choosing one or the other - it's about knowing when to use each lens. The power lies in leveraging both: using systems thinking to grasp complexity and design thinking to create human-centered solutions within that context. #design #ux #ui

For Halloween last year, I shared a post about what kept me up at night as a Chief Engineer. I'd like to expand on that by sharing more about what didn't - mechanical design. Let me explain. As someone who is deeply involved in the industry, and was a longtime designer of mechanical structures and systems, I often find myself discussing the importance of looking beyond mechanical CAD when it comes to digital twins and digital transformation. Here’s the thing – while CAD crucial to the foundation of the digital twin, it's just one piece of the puzzle for today’s fast paced innovation. Because it is visually appealing, mechanical CAD is often what people think of when they hear about digital twins. In times past, I was guilty of that myself. But the true value of digital transformation can only be realized by fully integrating mechanical design with electrical, electronics, and semiconductor design, in a multi-domain environment that seamlessly connects to downstream manufacturing and delivery processes. The integration of these domains along with requirements, simulation, analysis, and Bill of Materials on a robust PLM foundation creates a comprehensive digital twin that connects every aspect of product development and production. This holistic approach ensures that every component, from electrical circuits to semiconductor chips, is accurately represented and optimized within the digital twin. The ability to seamlessly connect mechanical, electrical, and electronics design is what sets industry leaders apart, enabling them to deliver innovative solutions that drive digital transformation. Further, by integrating IoT-enabled hardware, software, and digital services, companies can create a cohesive digital ecosystem. This integration ensures that every component is accurately represented and optimized within the comprehensive digital twin, providing real-time insights and enabling better, and faster, decision-making. In our industry, it's easy to get caught up in the visualizations, but the disruptors of tomorrow are looking beyond these and  holistically adopting digital transformation today. A broader understanding of digitalization, and the ability to utilize the full potential of digital technologies, can provide a provable and measurable competitive advantage in the increasingly tech savvy market landscape. So, next time you think about digital twins, remember – it's more than just 3D geometry and visualizations. It's about creating a comprehensive digital ecosystem that brings real value to the products of today and tomorrow.

How and to what extent can ethical theories guide the design of AI systems? This is the question I'd like to tackle in this week's #sundAIreads. The reading I chose for this is "Ethics of AI: Toward a Design for Values Approach" by Stefan Buijsman, Michael Klenk, and jeroen van den hoven from the Delft University of Technology. It's a chapter in The Cambridge Handbook of the Law, Ethics and Policy of Artificial Intelligence, which is available open access here: https://lnkd.in/dmP7hBnJ. The authors argue that familiar ethical theories such as virtue ethics ("what character traits should I cultivate?"), deontology ("which moral principles should I follow?"), and consequentialism ("what actions maximize wellbeing?") are necessary, but insufficient to guide the responsible development and deployment of #AI systems. Instead the authors advocate for a #design approach to AI ethics, which entails identifying relevant values, embedding them in AI systems, and continuously evaluating whether and to what extent these efforts were successful. Of course, this is easier said than done. Why? Because: 1️⃣ Values come with trade-offs, e.g., #privacy versus #security or #usability. 2️⃣ Values can change, both in terms of what they mean and how important they are to people, e.g., #sustainability. 3️⃣ AI systems are socio-technical systems, i.e., AI ethics is "just as much about the people interacting with AI and the institutions and norms in which AI is employed." These challenges can be addressed by: ✅ Making trade-offs between values explicit and either trying to resolve them or at least documenting the reasoning behind why one value was chosen over the other. ✅ Designing for "adaptability, flexibility and robustness" to account for changing values over time. ✅ Considering the environment in which AI systems will be deployed, including not only the people who will use AI systems, but also those affected by their use. I first encountered the values-by-design literature during my postgraduate studies with Helen Nissenbaum at the NYU Steinhardt Department of Media, Culture, and Communication and have been a huge fan ever since. For an even more hands-on approach to translating ethical values into technical design, I recommend checking out Dr. Niina Zuber, Severin Kacianka, Alexander Pretschner, and Julian Nida-Rümelin's Ethics in Agile Software Development (EDAP) project at the Bayerisches Forschungsinstitut für Digitale Transformation (bidt) (https://lnkd.in/dNiBUxBF) and Dr Lachlan Urquhart's Moral-IT Deck (https://lnkd.in/d9J2WQNi).

How can designers create solutions that ripple through entire communities? Imagine a park bench. It’s a simple design, right? But what if that bench, originally intended to provide a place for rest, became part of a much larger system designed to promote healthy lifestyles in a city? Now, it’s not just a bench—it’s part of a network of walking paths, bike lanes, and shared green spaces that encourage social interaction and well-being. This shift in thinking is exactly what the Social Design Pathways matrix helps us achieve. Created by the Winterhouse Institute, the Social Design Pathways matrix pushes us to think beyond isolated solutions. It challenges designers to collaborate across disciplines, scale up their impact, and work with a wide range of stakeholders—from community members to city planners. For example, when a team of designers, landscape architects, and social workers come together, they’re not just designing a park—they’re helping to reimagine how a city supports the health and social needs of its residents. The beauty of this approach is that it encourages designers to step out of their comfort zones. The more diverse the collaboration, the bigger the potential for change. And these aren’t just theoretical ideas. According to the World Health Organization, cities that prioritize active transportation systems, such as bike lanes and pedestrian paths, report significant improvements in public health and reduced environmental impact. The ripple effect is real. By using tools like the Social Design Pathways matrix, designers can clarify their intentions, collaborate effectively, and ultimately create holistic solutions that address complex social challenges. It’s not just about designing objects—it’s about designing systems that foster long-term, sustainable change. What design project are you currently working on that could benefit from this kind of collaborative, big-picture thinking? #SocialDesign #CommunityImpact #SustainableDesign #DesignForChange #Collaboration

Humanizing AI Through the Kano Model In an era where generative AI has become a ubiquitous offering, true differentiation lies not in merely adopting the technology but in integrating human values into its core. Building on my earlier discussion about applying the Kano Model to Gen AI strategy, let’s explore how this framework can refocus development metrics to prioritize ethics and human-centricity. By aligning AI systems with human needs, organizations can shift from functional tools to trusted partners that inspire lasting loyalty. Traditional metrics such as speed, scalability, and model accuracy have evolved into basic expectations the “must-haves” of AI. What truly elevates a product today is its ability to embody values like safety, helpfulness, dignity, and harmlessness. These qualities, categorized as “delighters” in the Kano Model, transform AI from a transactional tool into a meaningful collaborator. Key Human-Centric Differentiators Safety: Proactive safeguards must ensure AI systems protect users from risks, whether physical, emotional, or societal. Safety is non-negotiable in building trust. Helpfulness: Personalized, context-aware interactions demonstrate empathy. AI should anticipate needs and adapt to individual preferences, turning routine tasks into meaningful experiences. Dignity: Ethical design principles—fairness, transparency, and privacy—must underpin AI development. Respecting user autonomy fosters long-term trust and engagement. Harmlessness: AI outputs and recommendations should prioritize user well-being, avoiding unintended consequences like bias, misinformation, or psychological harm. This human-centered approach represents a paradigm shift in technology development. While traditional KPIs remain important, they are no longer sufficient to stand out in a crowded market. Organizations that embed human values into their AI systems will not only meet user expectations but exceed them, creating emotional connections that drive loyalty. By applying the Kano Model, businesses can systematically align innovation with ethics, ensuring technology serves humanity rather than the other way around. The future of AI isn’t just about efficiency it’s about elevating human potential through thoughtful, responsible design. How is your organization balancing technical excellence with human values?

Turning apple waste into furniture? Material innovation is being redefined with a groundbreaking vegan-certified leather alternative crafted from upcycled agricultural waste. This innovative material offers a premium, bio-based option that seamlessly blends environmental responsibility with practical versatility. Manufactured on wide rolls, it provides a luxurious, durable alternative to traditional leather while addressing the urgent need for eco-friendly solutions. By utilising by-products of agricultural processes, this innovation exemplifies how waste can become a cornerstone for transformative design, challenging industry norms and fostering a more circular economy. Recently, this material has been introduced in the furniture sector, demonstrating its versatility and effectiveness in reducing carbon footprints. For example, when used in furniture, it achieves significant reductions in carbon emissions compared to traditional materials. This measurable impact highlights the potential of sustainable materials to advance both environmental and business objectives. Key Features of Bio-Based Materials →Transformative Origins: Converts agricultural by-products into high-quality materials. →Cross-Industry Applications: Ideal for furniture, fashion, and automotive sectors. →Design Customisation: Supports diverse finishes and textures, meeting unique design needs. →Supply Chain Transparency: Offers full traceability, ensuring ethical production and enhancing storytelling. Business Impact and ROI →Sustainability Leadership: Collaborating with material innovators demonstrates a commitment to Environmental, Social, and Governance (ESG) goals. →Cost Optimisation: By utilising waste-based inputs, businesses can reduce dependence on costly, resource-intensive materials. →Market Differentiation: Offering products made with innovative materials positions companies as leaders in sustainability, appealing to a conscientious consumer base. →Carbon Reduction: Bio-based materials deliver tangible emissions savings, supporting corporate decarbonisation objectives. This innovation exemplifies how rethinking waste can drive sustainability and profitability, empowering businesses to lead in the era of bio-based innovation. Link for more info: https://lnkd.in/dmtMrnP3 #sustainability #esg #biomaterials #decarbonisation #wasteupcycling #innovation #bioeconomy #climateaction #circularity #greendesign

While auditing content for an Entrepreneurship course at UNSW Arts, Design & Architecture I discovered a secret. The secret to enhanced user-centric innovation: We often get "stuck" with what we're taught, and this sometimes affects how we think. We all learn about Design Thinking as a standalone tool, but there's MUCH MORE to it. Integrating Design Thinking, Lean UX, and Agile methodologies creates a powerful framework for driving user-centric innovation. Here's how it works: → Design Thinking: for deep empathy and problem definition → Lean UX: for rapid prototyping and validation → Agile: for iterative development and delivery ... And what happens when each is missing? • Without Design Thinking = "Misunderstanding" • Without Lean UX = "Wasted Effort" • Without Agile = "Stagnation" Combining these methodologies offers a holistic approach. Concept Exploration + Iterative Experimentation = Needs-and-Pain-point Discovery The initial stages emphasize brainstorming and prioritizing insights, leading to hypothesis formation that guides subsequent experiments. Continuous experimentation allows for the revision of hypotheses based on real user feedback, creating a dynamic loop of learning and adaptation. Here's how to integrate them: 1/ Design Thinking: Start with empathy. Understand your users deeply before defining the problem. 2/ Lean UX: Prototype quickly. Validate your ideas with real users early and often. 3/ Agile: Iterate. Develop in short cycles and adapt based on feedback. As teams build and explore new ideas, they foster collaboration across disciplines, leveraging diverse perspectives to refine solutions. This integrated framework not only enhances the customer experience but also drives sustainable growth. This helps founders ensure they remain competitive and relevant in their respective industries. George Dr. Kelsey Burton Yenni 👀 LESSGO!

In new research we show how matter can be both process and archive - a living record of forces, environments, and functions. This blurs boundaries between hardware and cognition where infrastructure, implants, and devices "think" and evolve through their own changing manifestation across all scales, from atoms to ecosystems and beyond, a form of "scalogenesis". Check out this new paper in MRS Bulletin "Frontiers of Biological Material Intelligence" (link below), led by my student Lee Marom. A key thesis behind this work is that for too long we treated "matter" and "mind", hardware and theory, or science and art as separate, when what we really needed was a set of constructional principles, shared rules of structure, interaction, and evolution that connect them into one continuous fabric! We explore how the convergence of deep biological insight, computational modeling & advanced fabrication is driving a shift from static synthetic materials to systems capable of sensing, adapting & self-optimizing. Key insights: 1️⃣ Definition of material intelligence: We argue that intelligence is not limited to cognitive systems but can be embedded within a material's physical structure, across all scales (from electrons to the world). Unlike traditional "smart" materials that rely on external sensors or control, intelligent materials possess "agency" - the capacity to initiate context-sensitive action through intrinsic chemical and structural properties. 2️⃣ Three Core Biological Principles: We identify three mechanisms nature uses to achieve this intelligence: 1: Sensing and Responding: Illustrated by sea cucumbers that reversibly alter their stiffness for defense. 2: Self-optimization: Seen across scales (for example in bone, trees or cellular remodeling), where structure is continuously refined based on mechanical stress. 3: Memory encoding: Demonstrated by tree rings and mollusk shells that physically archive environmental history, but extending to evolution of DNA and proteins as populations and ecosystems adapt and realize never-before-seen functions. 3️⃣ Formalizing Nature: To translate these biological behaviors into engineering, we highlight the need for computational tools like Category Theory & graph-based reasoning systems (neural networks extract features; and symbolic logic reason over them for abstraction and explanation). These frameworks allow us to abstract the complex, hierarchical logic of biological systems and predict emergent behaviors. We also explore the future of fabrication to incorporate 4D printing and biofabrication are essential for physically realizing these designs. Altogether we envision a future where materials function as "semi-autonomous experimenters" capable of learning from their environment and evolving their properties in a continuous loop (independent of human intervention). Congrats to Lee on an amazing paper and excited to hear the feedback from the community! Materials Research Society #MRSFall2025

This startup has found a way to make biodegradable furniture that returns to soil in 180 days! Furniture waste is an environmental problem that is not discussed at length or often enough! Conventional furniture relies on MDF, plywood, laminates, adhesives, and plastics. These materials are hard to recycle, release toxins when burned, and can remain in landfills for decades. As a result, most discarded furniture has only one destination: permanent waste! Reading through a September 2025 article by The Better India, I found that Bhakti V Loonawat and Suyash Sawant, architects and founders of ANOMALIA, are crafting furniture from mycelium, the root network of fungi. What I found very interesting … 📍Agricultural waste that would otherwise be burned or dumped is repurposed. 📍The material could substitute for boards made from timber, reducing pressure on forests. 📍At the end of its life, the product can biodegrade fully within 180 days, returning nutrients to the soil instead of adding to landfill volume. Each block of the material weighs just 1.5 kg, yet can withstand 1.5 tons of compressive load. The couple started experimenting during the pandemic, growing mushrooms in cupcake trays. By September 2022, they launched Anomalia in Mumbai. 📌Their work has since travelled to the Venice Biennale 2025 and Seoul, where they presented a 4-metre mycelium facade. 📌In India, they have sold nearly 100 blocks across Mumbai and Surat. I believe that for the design industry, materials like mycelium offer a practical path forward in reducing their carbon footprint and in product circularity. What alternative materials have you encountered in design or construction?