Intuitive Interaction Methods

Human conversation is interactive. As others speak you are thinking about what they are saying and identifying the best thread to continue the dialogue. Current LLMs wait for their interlocutor. Getting AI to think during interaction instead of only when prompted can generate more intuitive and engaging Humans + AI interaction and collaboration. Here are some of the key ideas in the paper "Interacting with Thoughtful AI" from a team at UCLA, including some interesting prototypes. 🧠 AI that continuously thinks enhances interaction. Unlike traditional AI, which waits for user input before responding, Thoughtful AI autonomously generates, refines, and shares its thought process during interactions. This enables real-time cognitive alignment, making AI feel more proactive and collaborative rather than just reactive. 🔄 Moving from turn-based to full-duplex AI. Traditional AI follows a rigid turn-taking model: users ask a question, AI responds, then it idles. Thoughtful AI introduces a full-duplex process where AI continuously thinks alongside the user, anticipating needs and evolving its responses dynamically. This shift allows AI to be more adaptive and context-aware. 🚀 AI can initiate actions, not just react. Instead of waiting for prompts, Thoughtful AI has an intrinsic drive to take initiative. It can anticipate user needs, generate ideas independently, and contribute proactively—similar to a human brainstorming partner. This makes AI more useful in tasks requiring ongoing creativity and planning. 🎨 A shared cognitive space between AI and users. Rather than isolated question-answer cycles, Thoughtful AI fosters a collaborative environment where AI and users iteratively build on each other’s ideas. This can manifest as interactive thought previews, real-time updates, or AI-generated annotations in digital workspaces. 💬 Example: Conversational AI with "inner thoughts." A prototype called Inner Thoughts lets AI internally generate and evaluate potential contributions before speaking. Instead of blindly responding, it decides when to engage based on conversational relevance, making AI interactions feel more natural and meaningful. 📝 Example: Interactive AI-generated thoughts. Another project, Interactive Thoughts, allows users to see and refine AI’s reasoning in real-time before a final response is given. This approach reduces miscommunication, enhances trust, and makes AI outputs more useful by aligning them with user intent earlier in the process. 🔮 A shift in human-AI collaboration. If AI continuously thinks and shares thoughts, it may reshape how humans approach problem-solving, creativity, and decision-making. Thoughtful AI could become a cognitive partner, rather than just an information provider, changing the way people work and interact with machines. More from the edge of Humans + AI collaboration and potential coming.

Intuitiveness is a "briefcase word" - it needs to be unpacked to be meaningful. And yet we often see "intuitive UI" used as a description of a feature, or worse, a product *requirement.* One issue is that "intuitive" really has two components, and you need both for a good product. One is the delta between the mental model of the product's designer and its user; it's "intuitive" if the workflow the user is accustomed to is mirrored precisely by the interface. The UI presents interactive elements in the hierarchy *and order* that the user looks for them, the affordances "speak the language" of that user. Designers trying to make "intuitive" interfaces often think they can achieve this by hiding complexity. But if their users are *looking* for that complexity, the design will be a disaster; the complex needs to be made *understandable* rather than merely simple. The other side of "intuitive" is the product's effectiveness at teaching its mental model to the user. This is necessary if - like any good innovation - you've come up with a new and better way of doing something. A really good primer on this is Arin Hanson's "Sequelitis" - exploring how the first few screens of Mega Man X introduce new mechanics that players of the other Mega Man games would be unfamiliar with. Another good example is Solitaire - training Windows users of bygone days to operate the newfangled thing called a "mouse" and practice interaction techniques like dragging and dropping. A product that only engaged with "intuitiveness" in the first way would be completely impenetrable to new users who weren't already experts in the old way of doing things. But a product that only engaged with it in the second way would be extremely frustrating for those expert users, who will initially make up your user base and don't want you to reinvent their wheel. Customizability is another element that often comes up - rather than make users re-learn, we let them adapt the system to their mental model - but it's usually used as a crutch by product teams who are not willing to learn that mental model in the first place. Customization created under this paradigm tends to be the opposite of intuitive, requiring lengthy 3rd party guides. This nuance is why designers must never rely on stakeholder approval as the "user acceptance test" of their work. What's "intuitive" for an exec is likely useless to a worker.

Intelligent interfaces make real-time design choices. For designers, sharing design decisions with robots can be… uncomfortable. But delegation ≠ abdication. The new work for designers is to give context and guidance to help the system make good choices. I made a guide, demo, and video for designers (link in the comments) about how to do this and keep the results on the rails. Done right, the result is a radically adaptive experience that responds to user context and intent. Layouts that rearrange themselves. Forms that choose smart defaults. Chat that “speaks” with well chosen GUI elements instead of text. It’s easier and more reliable than you might expect. The guide includes a simple, directional pattern library for giving the LLM its marching orders. For designers, sketching in simple plain-language system prompts becomes part of the design process, at least as important as drawing interfaces in your design tool. Instead of designing every interaction, you’re designing the *physics* of your application’s tiny universe. You define the behavior and constraints for making design decisions in the interface. It’s design system work for real-time decision-making. The basic recipe for wiring interface to intent: 1. Provide a constrained set of UI outputs. 2. Map those outputs to intent (“use this pattern to address that intent”). 3. Ask the LLM to understand intent and choose the right UI or action. It used to be really, really hard for systems to determine user intent from natural language or other cues. Now LLMs just get it. They grasp underlying semantics, they get slang, they can infer from context. LLMs may hallucinate facts, but they’re brilliant at interpreting intent and the shape of the expected response. This makes them a powerful and reliable partner for interpreting user meaning and delivering an appropriate interface. Check out the demo and give it a try yourself. Start writing; the interface is listening. Link in the comments (because you know, LinkedIn).

Are the interactions in your e-learning course about clicking, not learning? Try this 3-step method to fix it. You spend hours trying to design interactive e-learning—adding clicks, drag-and-drops, and hotspots. But learners rush through, and leadership barely notices. 𝘚𝘰𝘶𝘯𝘥 𝘧𝘢𝘮𝘪𝘭𝘪𝘢𝘳? Many instructional designers feel stuck; they don’t know how to create meaningful interactions instead of interactions that let people click. The key? 𝘚𝘵𝘳𝘢𝘵𝘦𝘨𝘺 𝘰𝘷𝘦𝘳 𝘥𝘦𝘤𝘰𝘳𝘢𝘵𝘪𝘰𝘯. Here’s a simple 3-step method to design interactions that truly enhance your e-learning courses: 1️⃣ 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗘𝗻𝗱 𝗶𝗻 𝗠𝗶𝗻𝗱 ✅ 𝗗𝗢: Before designing an interaction, ask yourself: *What should learners be able to do after this?* ❌ 𝗗𝗢𝗡’𝗧: Add interactions to make a course "look engaging." 📌 𝗤𝘂𝗶𝗰𝗸 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: If you aim to teach customer service skills, don’t just add a drag-and-drop activity where employees match cybersecurity terms to definitions. Create a simulated phishing attack in which learners must identify suspicious emails, decide whether to open links, and take appropriate action to protect company data. 2️⃣ 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗠𝗮𝗸𝗶𝗻𝗴, 𝗡𝗼𝘁 𝗝𝘂𝘀𝘁 𝗖𝗹𝗶𝗰𝗸𝗶𝗻𝗴 ✅ 𝗗𝗼: Use interactions that make learners think, not just click. ❌ 𝗗𝗢𝗡’𝗧: Overuse simple interactions (like clicking hotspots) without real engagement. 📌 𝗤𝘂𝗶𝗰𝗸 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: Instead of a basic hotspot where learners click on different parts of a customer service desk to "learn more," create a decision-based hotspot interaction. For example, learners see a busy retail counter with different customer scenarios. Based on urgency and priority, they must click on the right customer to assist first. 3️⃣ 𝗧𝗲𝘀𝘁, 𝗔𝗻𝗮𝗹𝘆𝘇𝗲, 𝗮𝗻𝗱 𝗜𝗺𝗽𝗿𝗼𝘃𝗲 ✅ 𝗗𝗢: Gather feedback and track learner performance. ❌ 𝗗𝗢𝗡’𝗧: Assume that an interaction is effective because it "looks fun." 📌 𝗤𝘂𝗶𝗰𝗸 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: Check if learners are engaged or just rushing through. If they struggle with assessments, go back and refine the interaction—maybe it needs more explicit instructions, better feedback, or a stronger real-world connection. By following these steps, you’ll move beyond generic interactions and create learning experiences that help learners retain knowledge—while making your work stand out. Which of these 3 steps do you already use? Follow me - Mark Spermon - to learn more about creating e-learning courses that engage and deliver results with Articulate Storyline #InstructionalDesign #eLearning #CareerGrowth #L&D #ArticulateStoryline

I brainstormed a list of things I ask myself about when designing for Human-AI interaction and GenAI experiences. What's on your list? • Does this person know they are interacting with AI? • Do they need to know? • What happens to the user’s data? • Is that obvious? • How would someone do this if a human was providing the service? • What parts of this experience are improved through human interaction? • What parts of this experience are improved through AI interaction? • What context does someone have going into this interaction? • What expectations? • Do they have a specific goal in mind? • If they do, how hard is it for them to convey that goal to the AI? • If they don't have a goal, what support do they need to get started? • How do I avoid the blank canvas effect? • How do I ensure that any hints I provide on the canvas are useful? • Relevant? • Do those mean the same thing in this context? • What is the role of the AI in this moment? • What is its tone and personality? • How do I think someone will receive that tone and personality? • What does the user expect to do next? • Can the AI proactively anticipate this? • What happens if the AI returns bad information? • How can we reduce the number of steps/actions the person must take? • How can we help the person trace their footprints through an interaction? • If the interaction starts to go down a weird path, how does the person reset? • How can someone understand where the AI's responses are coming from? • What if the user wants to have it reference other things instead? • Is AI necessary in this moment? • If not, why am I including it? • If yes, how will I be sure? • What business incentive or goal does this relate to? • What human need does this relate to? • Are we putting the human need before the business need? • What would this experience look like if AI wasn't in the mix? • What model are we using? • What biases might the model introduce? • How can the experience counteract that? • What additional data and training does the AI have access to? • How does that change for a new user? • How does that change for an established user? • How does that change by the user's location? Industry? Role? • What content modalities make sense here? • Should this be multi-modal? • Am I being ambitious enough against the model's capabilities? • Am I expecting too much of the users? • How can I make this more accessible? • How can I make this more transparent? • How can I make this simpler? • How can I make this easier? • How can I make this more obvious? • How can I make this more discoverable? • How can I make this more adaptive? • How can I make this more personalized? • How can I make this more transparent? • What if I'm wrong? ------------ ♻️ Repost if this is helpful 💬 Comment with your thoughts 💖 Follow if you find it useful Visit shapeofai.substack.com and subscribe! #artificialintelligence #ai #productdesign #aiux #uxdesign

Can a micro-interaction make or break your user experience? The answer might surprise you. In the world of UX design, we often focus on the big picture – the overall layout, the color scheme, and the navigation flow. But what about those tiny, seemingly insignificant details? Micro-interactions—subtle animations, transitions, and feedback elements—are the unsung heroes of user experience. They might seem like minor embellishments, but they have a profound impact on how users perceive and interact with your product. Think about it: ✦ The Like animation on YouTube:  When you click the "Like" button, the thumbs-up icon animates with a subtle bounce and shoots sparkles/fireworks, providing visual feedback that your action was registered and acknowledged. This seemingly minor detail reinforces positive interaction and encourages further engagement with the platform. ✦ The "Pull to refresh" gesture in mobile apps:  This intuitive gesture allows users to refresh content with a simple downward swipe. The spinning wheel or animated icon during the refresh process indicates that the app is working, managing user expectations and preventing frustration from perceived delays. ✦ Hover effects on website navigation menus:  When hovering over a menu item, it might change color, slightly enlarge, or reveal a subtle underline. These visual cues signal interactivity, guiding users toward clickable elements and improving the overall navigation experience. These micro-interactions create a sense of responsiveness, feedback, and delight. They make your product feel alive, intuitive, and enjoyable to use. But here's the kicker: micro-interactions can also backfire. A clunky animation, a delayed response, or an unexpected transition can quickly turn a positive experience into a frustrating one. Users might not consciously notice these details, but they'll feel the difference in their overall experience. So, how can you harness the power of micro-interactions to create a truly delightful user experience? ✦ Be intentional: Every micro-interaction should serve a purpose. Use them to guide users, provide feedback, and create a sense of delight. ✦ Keep it subtle: Micro-interactions should enhance the experience, not distract from it. Avoid excessive animations or flashy effects. ✦ Test and iterate: Gather feedback from users to see how they perceive and interact with your micro-interactions. Refine them over time to ensure they're working as intended. The next time you're designing a product, don't underestimate the power of micro-interactions. They might seem small, but they can make a big difference in creating a truly memorable user experience. #uxdesign #motiondesign #microinteractions #userexperience #ui

Ever notice how the best user experiences often feel... invisible? That's the goal. Great UX operates seamlessly in the background. Poor UX screams for attention through friction and frustration. Think of the best apps as intuitive assistants: • They anticipate your needs. • They make complex tasks feel simple. Consider these examples: 1️⃣ Netflix's Seamless Play: Content flows effortlessly, reducing decision fatigue and keeping you engaged without constant clicks. It just works. 2️⃣ Amazon's 1-Click Ordering: Streamlines checkout by securely saving preferences, turning a multi-step process into a single interaction. Efficiency perfected. 3️⃣ Slack's Quick Reactions: Simple emojis (like 👍 or ❤️) allow instant acknowledgment and feedback, reducing notification clutter and speeding up communication. Key Insight: While visually appealing designs might capture initial attention, it's the intuitive, frictionless design that truly drives user adoption and business value. 💰 How to Build Intuitive Interfaces: • Prioritize clear calls-to-action (CTAs). • Use plain language and universally understood icons (e.g., ✅). • Aim for interfaces so intuitive they barely need explanation. What are your favorite examples of 'invisible' yet impactful UX? 👇 PS: A classic test: Could someone unfamiliar with tech (like many grandparents) navigate your core app functions easily? If not, you might be overcomplicating things.

UX That Clicks: Psychology Tricks Top Designers Use Why do some buttons beg to be clicked- while others get ignored? It’s not magic. It’s psychology Let’s break it down 👇  1. Reduce Friction: Too many options = decision fatigue. That’s Hick’s Law in action. 💡 Amazon’s 1-click checkout? Designed to eliminate thinking. 🎯 Fitts’s Law says: The bigger and closer a button is, the easier it is to click. Spotify’s play button? A+ example. 👀 2. Behavior = Engagement: Smart design adds nudges, not noise.  Scarcity: “Only 2 left” = instant FOMO. It works — Booking.com uses it everywhere. 👥 Social Proof: “1,000+ bought today” triggers trust. People follow people.  Micro-Interactions: Like a heart icon turning red = dopamine hit. Small reward loops. Big retention. ✅ 3 Ways to Apply It Now:  • Simplify menus (5–7 items max) • Design for thumbs (lower screen CTAs) • Test everything (yes, even button color!) Stay Ethical: Psychology is powerful - use it wisely. Avoid dark patterns. Build trust instead. Final Thought: Good UX feels intuitive. Not because it's beautiful — but because it's brain-friendly.

This is the fourteenth in a series of 24 principles we use at Hatch Duo to craft visually compelling, timeless products. The best products don’t need instructions—they guide users through form. Whether it’s a spout, handle, or button, visual cues can signal function, priority, and behavior before a user makes contact. Visual clarity builds trust and reduces hesitation: - Strong form cues make a product feel approachable and intuitive - Clear affordances reduce dependency on labels or manuals - When function is expressed visually, the design feels confident and self-evident A well-shaped interaction invites use before words are ever read. Communicating Function in Practice - Beoplay H95 features a textured control ring that subtly invites rotation without relying on iconography. - Google Nest Thermostat uses a prominent circular dial that visually suggests grasping and turning to interact. - Simplehuman’s wall-mounted soap pump uses a front-facing lever shaped for the thumb, clearly guiding the squeeze action. Applying Visual Function with Purpose Design Elements that Invite Interaction: → Let curves, grips, and contours naturally guide where hands or eyes should go Use Hierarchy to Show What Matters First: → Emphasize key controls or access points through scale, shape, or placement Let Geometry Suggest Motion or Behavior: → Use directional cues—like pivots, levers, or arcs—to hint at how something moves Build Confidence Through Immediate Legibility: → When users instantly understand how to interact, the product feels effortless When a product communicates function through form, it feels natural, usable, and trustworthy. A strong design speaks clearly—without needing to say a word. This is just one of 24 principles we use at Hatch Duo to craft elegant aesthetics in physical product design. Stay tuned for the next principle in our Aesthetic Principles Series. #industrialdesign #productdesign #interactiondesign #visualaffordance #hatchduo

💡Don Norman’s Six Principles of Design Don Norman in his book Design of Everyday Things shares six fundamental principles that guide intuitive, usable, and human-centered design. These principles help designers create products that are easy to understand, efficient to use, and minimize the risk for errors. 1️⃣ Visibility The more visible a product’s functions are, the easier it is for users to understand what they can do. When actions, controls, or available states are hidden, discoverability suffers, and it often leads to confusion, hesitation, or misuse. How to apply it in design: ✔ Use clear signifiers (labels, icons, highlights) to make essential actions immediately apparent ✔ Avoid hiding core actions under multiple layers unless they are advanced or rarely used 2️⃣ Feedback Feedback informs users about what has happened after they take an action. It closes the loop between the user’s intent and the system’s response, reinforcing correct behavior or signaling errors that need attention. How to apply it in design: ✔ Provide immediate, noticeable, and context-appropriate feedback ✔ Avoid ambiguous states where the user is unsure if their action succeeded 3️⃣ Constraints Constraints limit the range of possible user actions to prevent errors, reduce complexity, and guide behavior toward successful outcomes. How to apply it in design: ✔ Use constraints to guide users toward correct actions ✔ Ensure constraints are communicated clearly to avoid confusion (users shouldn't wonder why they can't do something in UI) 4️⃣ Mapping Mapping is the relationship between controls and their effects. Good mapping ensures that the control layout mirrors the outcome, making it intuitive to operate without trial and error. How to apply it in design: ✔ In interfaces, ensure the position, shape, and labeling of controls reflect their function. ✔ Use spatial or visual cues to reinforce the link between action and outcome. 5️⃣ Consistency Consistency means using the same design patterns, visual attributes, and interaction rules across a product (and ideally across related products). This allows users to transfer knowledge from one part of a system to another. How to apply it in design: ✔ Maintain internal consistency (within the product) and external consistency (with widely used conventions). ✔ Breaking consistency should only be done with strong justification and clear communication. 6️⃣ Affordance Affordances are cues that indicate how something can be used—either physically or digitally. They answer the question: “What can I do with this?” How to apply it in design: ✔ Make affordances visible and match them with the intended action. ✔ In digital design, reinforce affordances with signifiers like shadows, textures, or animations. #design #productdesign #ux #uxdesign