In the Loop №5: User Experience x AI
Every month we’ll be sending out a curated list of articles and resources on a specific theme within the AI x Design landscape, as well as highlight updates and works from members of the community. Subscribe to receive our monthly newsletter and stay up in the loop with our community!
Taking into account the user experience of your solution is as essential to success as your model’s performance. If it doesn’t align with human needs and mental models, your system will be a piece of intricate engineering with little to no real-life value.
Every design materials come with unique opportunities and challenges. Designing the user experience of adaptive, intelligent, and semi-autonomous systems present a range of new challenges for designers to take on.
This month we explored generative and exploratory user research to inform how to build your model, make certain trade-offs, and design the frontend interface of your AI-driven offering. Looking at challenges such as Trust & Transparency, User Autonomy & Control, and Value Alignment, we zoom in on the role of UX design(ers) in the development of AI-driven products and services.
Spotify’s Three Principles
This article by Spotify Design sheds light on three principles they believe will help others design ML-powered experiences by utilising a human-centered perspective.
Three Principles for Designing ML-Powered Products
Machine Learning (ML) has become an indispensable tool at Spotify for delivering personal music and podcast…
Cheatsheet to Human-Centered Design
This cheatsheet provides a set of questions to think about when designing AI systems for people. Josh Lovejoy reminds us of human and machine capabilities, helping designers to remain grounded and human-focused.
Human-centered AI cheat-sheet
Throughout my journey as a UXer working on AI, I’ve been refining a cheat-sheet of questions-as-guidance to help find…
Applying UX for Data Scientists
Having an accurate machine learning model means nothing if users or stakeholders, internal or external, do not find your insights, product, or organisation to be credible. This article presents some approaches that data scientists can use to help explain results and decision process behind the AI blackbox.
“[ML explainability] is not a problem you can set aside until after you built the model(s) — it is important to think in advance about the data and components of the model that the user may want to see and how to present results in a way that builds user trust.”
#5: Machine Learning is Very Much a UX Problem
The Importance of Explainability When Using Machine Learning Models in Your Product and Different Approaches to User…
Choosing UX Metrics
A group of quantitative UX researchers at Google developed a couple of useful methods to help choose and define appropriate metrics that reflect the quality of user experience and the goals of your product or project. Learn more about the methods through this animated article they did in collaboration with Digital Telepathy.
How to Choose the Right UX Metrics for Your Product
Identifying clear goals will help choose the right metrics to help you measure progress. You may not realize that…
Trust as a Design Challenge
Without trust, there is little chance that AI systems will be adopted, which can potentially jeopardise the whole future of human and machine collaboration. This article walks you through three stories to give you an idea about what the components of trust (competence, honesty and reliability) would look like from a UX point of view.
UX for AI: Trust as a Design Challenge
What could a trustful relationship between a business user and the digital assistant look like in practice?
UX of AI Case Study
A case study of how Google Clips uses practices of human-centered design to create an inclusive AI-powered product. This piece presents takeaways from three years of development of the intelligent camera.
The UX of AI - Library - Google Design
Just getting more UXers assigned to projects that use ML won't be enough. It'll be essential that they understand…
November Event: Designing ML with Michelle Carney
We’re proud to have hosted an event this month with Michelle Carney, founder of MLUX and User Researcher at Google AI. Michelle shared her 3-step process for generative and explorative research to understand user needs before building your machine learning model.
Read more about her approach and applied use-cases for designing ML-products in our event summary.
Building ML Products for people
Learn from MLUX founder Michelle Carney’s 3-step process for early-stage AI development
Upcoming: AIxDesign 2020 Wrap Up
The AIxDesign Community has grown tremendously in the last 6 months and we are grateful for everyone that has been a part of our journey so far. To end the year on a high note, we are hosting an open office hangout session to connect with you all!
This is open to everyone who is curious about what this intersection of AI and design is all about, to learn more about everything being done at our community, and to bring in their own questions, projects, or ideas to pick our brains about. Drop by anytime with your thoughts and questions. We look forward to meeting you on December 1st :)
AIxDesign Community: Wrap-up 2020
Eventbrite - AI x Design Community presents AIxDesign Community: Wrap-up 2020 - Tuesday, December 1, 2020 - Find event…
Here are some things within the AI x Design space for you to check out!
📖 Read: AI-Driven Design
AI-driven Design: AI will undeniably shape the user experiences of tomorrow
In this Brain food ebook series "AI Driven Design" Joël van Bodegraven Product Designer at Adyen, alongside various…
Shoutout to our members for their contributions this month!
- Boshra wrote an article on Computational Creativity: 14 AI Artists whose work to explore.
- Kwan did a workshop at WUD Rome 2020 on Collective Algorithms for Human Interaction.
- Avantika gave a talk at WUD Rome 2020 on Combining AI and Behavior Science. (Keep an eye out on our Medium publication for her write-up!)
We cast a monthly spotlight on one of our members to introduce you to the world of their practice and perspectives. For this month, meet Avantika Mohapatra. She is an engineer-turned-designer, and she also leads Events & Partnerships for our community. Check out the interview where we discuss her foray into AIxDesign, her passion for all things design, and her ambition to bridge the gap between designers and data scientists.
Meet the Community: Avantika Mohapatra
Member Highlight — Events & Partnerships @ AI x Design
1. Become an active contributor
We’re currently looking for an active contributor to fill in the role of Community Lead. This role entails engagement with members in our Slack space — welcome new members in #intros, host FIKAs, ask questions in channels, share articles, keep the conversation going, make connections between members, tag members in open calls, etc. If interested please respond to this email!
2. Collab opp: UX of AI Design Pattern Library
We are looking to develop a UX of AI Design Pattern Library that will translate existing high-level principles of AI-human interaction into tangible wireframes in order to question and inform how we design AI-driven products and services. If you’re interested in being a partner, sponsor, or contributor for co-creation, leave your details here to get involved!
3. Join Elements of AI (Part II) study group
Within our community, we are doing a study group for the Elements of AI (Part II). First meeting is on 3rd of December, where we will discuss the first chapter. Completion of chapter is necessary in order to join the session. Interested in joining or have questions, reply to this email!
AIxDesign is a place to unite practitioners and evolve practices at the intersection of AI/ML and design. We are currently organizing monthly virtual events, sharing content, exploring collaborative projects, and developing fruitful partnerships.