Brian T. O'Neill

The latest episode of my podcast features a conversation with Emily Campbell about The Shape of AI, her emergent pattern language for interacting with AI-powered systems. Emily has defined five categories of patterns: identifiers, wayfinders, prompts, tuners, and trust indicators. Employing these patterns can help designers produce systems that are more usable & understandable and give users more agency. This topic is closely aligned with my interests; envision a Venn diagram with circles that say AI, systems, and design. As such, this was one of my favorite recent conversations on the show. I hope you get as much value from this interview as I did — and thank you Emily for creating The Shape of AI and sharing with us! Link in the first comment below 👇

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**DECISION DESIGN – Mapping the Field (#GG 1)** I began mapping decision design and its context to enable broader discussions on the topic. This exercise is a starting point to nuance arguments around what decision design can become. The image below is a simplification and extension of Elliott P. Montgomery's unresolved mapping of Speculative Design (V 2.0; link in comments). For readability, I’ve reduced elements to top-level categories only, added a present–future(s) axis to qualify levels of constraint in more detail, and included “Risk and Opportunity Management” as another discipline of increasing relevance for future(s) shaping. Moreover, I’ve highlighted the futures studies sub-category of “Desired Futures”. The dark matter of culture is the often forgotten canvas of it all. As you can see on the map, decision design is situated very much in the present. Decisions are the atoms of social and organizational life and are thus heavily constrained by daily necessities. However, it is this elementary level that makes good decision design impactful. The purpose of #design in the decision-making process is to reveal and shape opportunities for presencing elements of desired futures while respecting - and leveraging - existing constraints. Decision design channels futures studies into daily routines and bridges the design domain with the expanding field of risk and opportunity management. Similar to Strategic Design, the focus is always on design for active futures creation. However, a formal process for strategy formulation can be bypassed. Strategies, if needed at all, rather emerge from designed decision-making from the bottom up. This makes Decision Design lean and approachable, not only for organizations but also for individuals and their respective concepts of personal futures. --- Would love to hear your feedback: Elliott, Jan Rod, Tobias Revell, Uri Casademont, Michael Shamiyeh, 🔮 Michael Eichelberger, Konstantin Kohne, Elizabeth Hofvenschiöld, tom siegel - and all the other pioneers out there. Open for co-creative work on decision design and respective projects --- Follow Gravity & Grandeur on LinkedIn for more insights on decision design and decision-becoming. Also check out the website and book a free GG Check for your upcoming major decision. Like, comment, spread the word – and BECOME YOUR BEST DECISION.

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If you want to become more strategic in your design role, think of this metaphor: People don't get out of bed in the morning and think, "I need to go to Bloomberg to find that feature." They just need to know what the weather is like today. It's about helping customers be fast and efficient.

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I noticed in my last few years of leading UX Design and Research teams that the most gnarly problems that needed solving were ORGANIZATIONAL 💡 not interface usability 🖥 problems. Issues like built up technology debt that could no longer be ignored - but is too big to fix 💰, legal contracts that preclude access to, and thus learning from, customer's behavioral data 📰 , and lack of connection, alignment, and trust between senior leadership and employees 💔. Leaders, these are the problems to solve to create growth that is cumulative, generative, and sustainable 🌳. It takes courage to tackle the big stuff but that's where the big results and the big boost in meaning and engagement lies - for you and for your employees. What organizational problems do you want to tackle and solve? 👇 #organizationalchange #transformation #leadership #courage #employeeengagement

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#CoDesign according to the #NDIA #NDIS Doesn't look like #CoDesign. No mention of #UNCRPD in *OUR* (ie #NDIA's) #CoDesign principles. A little hint: the #UNCRPD is *THE* design determinant. #CoDesign *CAN'T* happen without explicit commitment to #UNCRPD. Explains why the #NDIS Bill breaches #HumanRights The #CoDesign Advisory Group - which "provides strategic advice to the NDIA on the implementation of co-design and engagement processes in the disability community" -  hasn't met in 9 months. As I explained in my recent article, #CoDesign has been weaponised. https://lnkd.in/d8VMKkvZ Take a look. #NothingAboutUsWithoutUs #RoboNDIS #ClassAction #RoyalCommission robondis.org Mark Toomey Tony Ridley, MSc CSyP FSyI SRMCP Karen Kline Samantha Connor Mark Sweeney Nick Avery Graham Taylor Tara Hannon Muriel Cummins Georgia van Toorn Dr George Taleporos (GAICD, PhD) Shirley Humphris Peter Gregory Jordon Steele-John #BillShorten David Pocock Vinod Ralh Paul Flintoft 👇 👇👇 https://lnkd.in/dKq7mdzZ

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New playbook! The mini-book is a deep-dive into drivers, limiting constraints, floats, and enabling constraints. It is structured as a collection of thought experiments, mental models, reflection questions, and actionable activities. It's designed to be skimmable and flexible—feel free to jump around and explore sections in any order. Throughout, you’ll find specific activities that I recommend trying out in your work or with your teams. I originally created this as a companion piece for my Scoping and Shaping for Success workshop, which I’ve since discontinued as I explore how to integrate these ideas into other learning experiences. Let me know how you like the format and whether it sparks new insights for you! https://lnkd.in/g_SbV4ts

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Ready to transform your UX research with the power of AI? 🚀 Imagine cutting research time in half. Sounds too good to be true? It’s not. Here’s how AI can accelerate your UX research process: Data Collection at Lightning Speed: → Traditional methods can be painfully slow. → Automate surveys and interviews for quick responses. Pattern Recognition and Analysis: → AI tools can sift through massive data sets in seconds. → It can highlight user pain points based on user interactions and feedback. → Visualize complex data through AI driven analytics. Predictive User Behavior: → AI models can predict how users might behave. → Anticipate user needs before they even know them. → Tailor experiences that resonate deeply with users. Personalization at Scale: → AI can customize user experiences for millions. → Deliver relevant content and recommendations. Continuous Feedback Loop: → Implement AI to gather continuous user feedback. → Adapt products in real-time based on insights. Speed up the research process without compromising on quality. Remember, it’s not about replacing human intuition but enhancing it. What AI tools have you found most effective in your UX research journey? Share your experiences below!

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Popular, but not often discussed opinion: It is significantly more fulfilling to support Product Managers/ Owners who "get" the value of User Research and data than those who don't. So this series, at least for now, is dedicated to them. After you watch it, let me know what else we should discuss.

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LLMapper, my experimental LLM-driven concept mapping tool, has reached a point where it's producing somewhat consistent results. I haven't devoted much time to this over the last month, in part because further efforts at prompt tweaking are producing diminishing returns. It feels like further progress will require fundamental shifts in the approach. Still, I'm happy with where this is. One possible area for near-term improvement: changing it so it accepts as input any public URL (i.e., not just Wikipedia pages.) Stay tuned... Link to more details in the first comment below. 👇

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When I was in grad school, I used to hate when my advisor would say, over and over, some version of, "Have you done some simulations of the data?" Little did I know, nearly 25 years later, that I would find data simulations the most helpful way to illustrate a concept. (I still struggle to create them myself...) But I'm simply blown away by folks like Matt Gershoff and Georgi Georgiev, who so easily "throw together" a quick simulation to explain some concept or other - and who then write these amazing articles that help educate our industry - just because they are good people. This time, Georgi has created simulations to help folks understand the ROI of testing. 1. Q: Should you test or not test? A: TEST 2. Q: If you can't do perfect, high-standard (0.05 sig threshold) testing right away, should you just start? A: TEST - however you can 3. Then, he helpfully and wonderfully explains 1 & 2 and provides many easy-to-understand explanations AND important considerations and caveats. So - read it. And share it. It's worth your time.

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Occasionally folks will ask for recommendations for authors who write about the intersection of AI & UX research. One that I'd like to share today is Donna Tedesco -- who you might recognize as the author of "Beyond the Usability Lab" and "The Moderator's Survival Guide" -- whose series of articles on Medium are a really thoughtful look at how to apply AI in UX. https://lnkd.in/eqQxBjvi

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More UX and Product leaders need to hear Diana DeMarco Brown (she/her)'s wisdom. Diana is a pioneer in the UX field who takes a thoughtful and nuanced approach to assessing the current state of the tech industry. In our recent conversation, Diana shared many insights, including: - How to evaluate a company's culture during the hiring process - Why private equity ownership can result in design divestment - How Product and UX leaders can effectively influence business decisions - Why we don't need to panic with the rise of AI, but we need to think critically and prioritize regulation during this early stage Link to our full conversation: https://lnkd.in/eemDimVb

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AI for Accessibility: Elon's Tweets Based on a request from engineers and artists, I've been building (or have built) a complex alt text generator for large, information-rich visuals. While testing, I've processed thousands of vintage maps, schematics, infographics ... you name it. The absurdly high resolution images can be found at https://buff.ly/4bZiXvf. However, there are a lot of smaller graphics too that don't warrant their own major post. I'm sharing them free as Substack notes - but join the Substack (or Patreon) for a lot more!

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What big-picture challenges are facing #designsystem practitioners and teams today? Tell me here or in the comments: https://lnkd.in/e4KenRtF

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🚀 Should We Teach Data Analytics to Designers in School? Reading this article got me thinking: how much statistics and mathematics does a designer need to apply human-centered design principles when creating AI products? Humanizing technology has always been a critical goal of user-centered design, but our traditional tools seem insufficient for humanizing AI. There's much talk about the need to put humans in control and create transparent AI. If that's the case, designers must understand the science behind algorithms—how they work and their impact on people's lives—to play their role in the system, especially regarding equity, diversity, and inclusivity. It is clear that the design world is behind in training UCD designers who can navigate AI design challenges. With my background in science, I see firsthand how much knowledge of mathematics helps me understand the challenges of AI. 🔗 Join the Conversation! Do you think data analytics should be a part of the design curriculum? What other skills do designers need to thrive in an AI-driven world? Share your thoughts below! https://lnkd.in/gxmjMucE #Design #DataAnalytics #AI #Education #FutureSkills #Innovation #HumanCenteredDesign #EthicalAI

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I think what an analytics product manager [or] an AI product manager needs to accept is there are other ways to measure the value of UX design’s contribution to your product and to your organization. Let’s say that you have a mission-critical internal data product, it’s used by the most senior executives in the organization, and you and your team made their day, or their month, or their quarter. You saved their job. You made them feel like a hero. What is the value of giving them that experience and making them feel like those things… What is that worth when a key customer or colleague feels like you have their back with this solution you created? Ideas that spread, win, and if these people are spreading your idea, your product, or your solution… there’s a lot of value in that. Or is there? What do you think? ⬆️ Join 2k readers: tap “Visit my website” to get my latest thinking in your inbox 🚫 Don’t like LinkedIn’s algo deciding what you see? Tap the bell under my profile banner to get all my posts ♻️ Please repost if this was useful 🎧: https://bit.ly/4esNjaw #DataScience #ai #dataproducts #analytics #design

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