Design of AI: The AI podcast for product teams

Phillip Maggs, who leads Generative AI Excellence at Superside and has collaborated with giants like Netflix and Google, shares invaluable insights on design and AI. He emphasizes that merely consuming AI content isn't enough; experimentation is key to career advancement. Maggs also highlights the shift in design roles due to GenAI, advocating for the automation of routine tasks while preserving the artistry in brand-defining designs. Additionally, he discusses the importance of codifying brand rules to unlock AI's potential in creative processes.

GenAI’s promise is that digital experiences will become more intelligent. Big Medium Founder Josh Clark and his daughter, Veronika Kindred, are the authors of the upcoming book “Sentient Design” and the latest guests on the podcast. They see products that are radically adaptive to our situational needs and collaborate with users in ways that seemed insane a few years ago. Listen on Spotify | Listen on Apple PodcastsBut what struck me the most were three things:* Veronika, a GenZer who figuratively grew up inside of tech because of her father’s work, sees the role of AI much differently than what us older folk would expect. There’s an awkward comfort with the centralization of power within these systems and the expectation that we, the users, will decide whether it is used for good or bad.* Not building towards personalization. Josh knows that it requires far too much data for a system to understand us and what we truly need. So they’re better suited to inferring where we are in our journey, making assumptions about what might have changed about us, and adapting to meet us where we are.* Josh is a champion for embracing the weirdness of AI. Rather than be intimidated and worried about hallucinations, use the not-so-perfect technology in ways that provide unexpected results. The counter-point to intelligent products continues to be how much intelligence a user wants and how much personal information they are willing to give up for it. There’s nothing more uncomfortable than a salesperson who doesn’t get your signals.Adobe’s Project Concept is the start of something hugeEmbracing the weirdness is exactly what Adobe’s new product, Project Concept does. Better you watch the video than me try and explain. It will be interesting to see how agencies respond to the further commoditization of their expertise.Always remember, GenAI is great at the boring stuffAmazon, in its quest for greater efficiency, has developed new systems to shave seconds off each package delivery and to help customers make faster buying choices, even for new product types that they may know little about. The company announced Wednesday it has created spotlights within its trucks to guide delivery people to packages for each stop along a route."When we speed up deliveries, customers shop more," said Doug Herrington, CEO of Amazon worldwide stores in remarks at the event. "Once a customer experiences fast delivery, they will come back sooner and shop more."Interestingly, this also highlights the tech’s ability to imagine solutions to problems that humans may not be able to see otherwise. You could call that embracing the weirdness again. We’ll go into this conversation in detail when we interview Lisa Weaver-Lambert, the author of The AI Value Playbook. In the book she interviewed business leaders to document exactly where and how AI has been delivering value.Multi-modal AI: 8 ways computer vision will change our livesWhile GenAI has been monopolizing the headlines, Apple, Meta, and Snap continue to invest in augmented reality headsets. Apple's Vision Pro landed with a thud —largely due to the price and home-bound use cases— but the others stirred buzz because they focused on lightweight and fashionable eyewear (courtesy of their partnership with Ray-Ban).We've been here before though. Google Glass famously failed. And no one remembers Snap's previous eyewear.But now is different.AI researchers have made huge advancements related to computer vision. If AI enables computers to think, computer vision enables them to see, observe and understand.Continue reading the article on LinkedIn…Want to join as a contributor?Contact us info@designof.ai to help us collect the best resources about how AI is shaping the world around us.Thanks for reading Design of AI: News & resources for product teams! Subscribe for free to receive new posts and support my work. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit designofai.substack.com

Join Kristie J. Fisher, Sr. Director of Global User Research at PlayStation Studios, as she shares insights from her impressive journey in the gaming industry. Discover the unique challenges of designing GenAI products, where user control meets the leap of faith in technology. Learn about evolving research methodologies that adapt to digital trends, the importance of crafting joy-focused experiences, and redefining success through new user-centered metrics. Kristie's expertise bridges gaming, psychology, and product strategy to enhance user engagement.

Episode 17. Our guest is Glenn MacDonald who was Spotify’s Data Alchemist, building it into an algorithmic powerhouse.We’re critically evaluating algorithms' effectiveness and why GenAI probably isn’t the best technology for many problems.Some key insights:#1. As Spotify's former data alchemist, I expected huge advocacy for hashtag#ML & hashtag#AI as a predictive technology. Instead, we must not play god with algos. They should be assistive tool to get people to where they're headed. Prediction leads to errors.#2. You must be able to evaluate algorithms. Too often we're deploying fancy tech with no way to know it is performing better than an alternative. hashtag#GenAI has a huge risk of this because the assumption is that it solved everything. But the cost of deploying it is also very high."I think the main thing I've learned Is actually not to think about it as prediction, I think the thing that happens to you when you start thinking about things as prediction, and I think this applies to thinking about LLM, LLM outputs as predicting text. It also applies to A& R and music as like predicting hit artists. The moment you start thinking about it as prediction, you've sort of internalized sort of ugly idea that the future is kind of determined and you're just attempting to guess what it's going to be and thus profit by anticipation. And I think it's a lot more productive to not think about the future as something you're predicting, but it's something you're making. ""I think a lot of the time we evaluate new tech against really Poor baselines, like against randomness or against the most popular things, or like you said, against just like our intuitive guesses. And in those contexts, sometimes the fancy tools seem like, Oh, they're clearly better. But then when you compare them against, Oh, what if we just did some math and you realize. Oh, the math's even better. It's a lot simpler. "The episode is hosted by:Arpy Dragffy Guerrero (Founder & Head of product strategy, PH1 Research) https://www.linkedin.com/in/adragffy/Brittany Hobbs (VP Insights, Huge) https://www.linkedin.com/in/brittanyhobbs/Glenn McDonald is a music evangelist, algorithm designer, software engineer and technology strategist. He created the music-exploration website Every Noise at Once, and for 12 years was the Data Alchemist at the Echo Nest and Spotify. He has written about music online since before "blog" was a word, and his first offline book, You Have Not Yet Heard Your Favourite Song: How Streaming Changes Music, is available now from Canbury Press.00:24 Meet Glenn MacDonald: Spotify's Data Alchemist01:50 The Evolution of Music Discovery08:39 The Role of AI in Music and Beyond13:29 Challenges and Future of AI in Music29:14 Navigating AI in the Workplace31:25 Designing User-Friendly Algorithms34:59 Challenges with Algorithmic Recommendations39:42 Evaluating AI and User Testing47:41 The Future of Music and AIThank you for listening to the Design of AI podcast. We interview leaders and practitioners at the forefront of AI. If you like this episode please remember to leave a rating and to follow us on your favorite podcast app.Take part in the conversations about AI https://www.linkedin.com/company/designofai/And subscribe to our newsletter for additional resources https://designofai.substack.com/ This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit designofai.substack.com

Yasemin Cenberoglu, Principal Design Manager at Microsoft and the first designer for Copilot, shares her journey in AI design. She discusses the secretive creation of Microsoft's Copilot and the collaboration with OpenAI. Yasemin contrasts European and North American design philosophies, highlighting their impact on innovation. She emphasizes the role of iterative design and user feedback in AI development, and the importance of building trust in AI tools while navigating past perceptions. Her insights offer a fresh perspective on evolving service design in AI.

Arpy Dragffy Guerrero, founder of PH1 Research and consultant for industry giants like Spotify and Microsoft, shares his insights on building AI products that resonate with customers. He discusses the struggles of identifying meaningful AI use cases and the mismatch between technology capabilities and customer value. Arpy emphasizes the importance of learning from failures, applying systems thinking, and the transformative potential of AI agents over traditional chatbots. Tune in for strategies to navigate the evolving landscape of AI in product development!

What is the path to building responsible AI products? We have a special guest: Jess Holbrook, the Head of UX Research for Microsoft AI.We discuss:‣ Responsible AI: What it is and how orgs need a clear vision for it‣ Data transparency: Ensuring you are communicating appropriately‣ Becoming one of Google’s first user researchers working on machine learning‣ Philosophical differences to user research at Google, Meta, and Amazon‣ Bridging academic research and the practical development of AI products‣ The paradigm shift that big tech is expecting AI to deliver‣ Why the last thing you should want is a user over-trusting your productAs one of the first user researchers working on AI products, Jess offers a deep and informed perspective on the challenges and opportunities of working with this new technology. He challenges organizations to build values into their products, unwaveringly and without vagueness. Jess Holbrook is the Head of UX Research for Microsoft AI. Prior to that he was Director of UX Research for Generative AI and Responsible AI at Meta. He got his start in human-AI research about 10 years ago at Google where he was a founder and lead of Google’s People + AI Research group (PAIR). Prior to joining Google, he was a UX Researcher at Amazon and Microsoft. He received his Ph.D in Psychology from the University of Oregon and a B.S. in Psychology from the University of WashingtonFollow Jess: https://linkedin.com/in/jessholbrook/ https://x.com/jesssconResources mentioned by Jess:https://pair.withgoogle.com/https://research.google/teams/responsible-ai/https://runwayml.com/Please subscribe to: Design of AI: The podcast for product teams, on Spotify, Apple podcasts, Youtube, substack. We interview leaders and practitioners at the forefront of AI to help product teams navigate where and how to leverage AI. Have questions? Join the conversation in our LinkedIn community: https://www.linkedin.com/company/designofai/ Hosted by: Brittany Hobbs https://www.linkedin.com/in/brittanyhobbs/ Arpy Dragffy Guerrero https://www.linkedin.com/in/adragffy/ This Design of AI episode is brought to you by PH1: A research & strategy consultancy that helps clients build AI products that customers want https://ph1.ca This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit designofai.substack.com

AI is changing the role of the designer and shifting how product teams succeed. We have a special guest: Scott Jenson, formerly from Apple, Google, and Frog Design.We discuss:* Why designers feel like their entire job will go away* What advice he offers to the teams and individuals he coaches* How AI is over--hyped and where it will have impact* Lessons from working at the forefront of mobile technology* Why Google, Apple, Meta, Microsoft are all racing to get there first* Recommendations to build successful products todayThis conversation is more of a coaching session for the designers, researchers, and product teams trying to navigate this time of great change.We try and cut through the hype to distill out key lessons that will help you all in your careers.Scott Jenson has worked in user interface design and strategic planning for over 30 years. The first member of the System Software Human Interface group at Apple in the late 80s, working on System 7, the Apple Human Interface guidelines and the Newton digital assistant. After Apple, was a freelance design consultant, doing work for Netscape, Mayo Clinic, American Express, and several web startups. Then director of product design for Symbian, then managed Mobile UI design at Google for 6 years. Left to become creative director at frog design for 2 years but returned to Google to explore advanced UX concepts for IoT and Android at Google. 35+ patents.  https://www.linkedin.com/in/scottjenson/Please subscribe to: Design of AI: The podcast for product teams, on Spotify, Apple podcasts, Youtube, substack. We interview leaders and practitioners at the forefront of AI to help product teams navigate where and how to leverage AI.Have questions? Join the conversation in our LinkedIn community: https://www.linkedin.com/company/designofai/Hosted by:Brittany Hobbs https://www.linkedin.com/in/brittanyhobbs/Arpy Dragffy Guerrero https://www.linkedin.com/in/adragffy/This Design of AI episode is brought to you by PH1: A research & strategy consultancy that helps clients build AI products that customers wanthttps://ph1.ca This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit designofai.substack.com

This conversation is a deep case study into what the capabilities of the technology are today and how product teams must leverage both creative experts and these emerging technologies, side-by-side. Our guest is Trisha Causley from Shopify.Topics we discuss:▪ Why Trisha went from an AI skeptic to a champion▪ What types of creative tasks GenAI is best at▪ Tactical lessons for leveraging GenAI across product experiences▪ Why prompt engineering must become part of your toolkit▪ Shopify’s plan to leverage GenAI to scale & personalize brand-building▪ Why GenAI enhances the role of creatives by expanding what you doTrisha Causley is a Senior Staff Content Designer at Shopify in Toronto, Canada, where she works on AI-powered product features. She previously worked with IBM and on the Watson team. https://www.linkedin.com/in/tcausley/The Design of AI podcast is available on Spotify, Apple Podcast, and Youtube.Have questions? Join the conversation in our LinkedIn community: https://www.linkedin.com/company/designofai/Subscribe to the Design of AI podcast for more in-depth resources for product teams.Hosted by:Brittany Hobbs https://www.linkedin.com/in/brittanyhobbs/Arpy Dragffy Guerrero https://www.linkedin.com/in/adragffy/ This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit designofai.substack.com

Why are brands investing into AI? How can they succeed? What can we learn from how experts in the field of innovation lead transformation projects? Where will AI actually deliver impact in the near term? Joining us is Nick Sherrard, who is involved in these conversations across Fortune 500, government, and startups.He is a co-founder of Label Sessions, the global innovation expert network, and Label Ventures, the venture studio. He is also a board member at Substrakt, the digital agency, and Collective art gallery in Edinburgh. Nick is often said to be the only person to have run an innovation lab inside a bank, a government department, a big 4 consultancy and a circus. His approach to making change happen in organisations fuses his more classic brand and product development background, with the devising mindset of arts producer. Nick advises boards and entrepreneurs globally.In this episode we cover:* Top-down and bottom-up approaches to leading AI projects* History of art and innovation is the history of rejection* Leaders of AI projects often don’t anticipate what’s needed* The problem with design thinking when building AI products* How the creative & consulting worlds are enhanced by AI* Use cases where AI will have impactAlso find us Apple Podcast & SpotifyHave questions? Join the conversation with other product leaders on LinkedIn https://www.linkedin.com/company/designofai/Subscribe to the Design of AI podcast for more in-depth resources for product teams. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit designofai.substack.com