User-Centered AI Weekly

Editor's thoughts

Hi Folks! 👋 Key insights in the fascinating intersection of AI and user-centered design

AI presents a lot of exciting opportunities, but for it to truly thrive, it has to consider the wealth of knowledge accumulated over the last 30 years in the fields of UX and human-centered design.
UX designers must expand their skill set and comprehend the concept of the consistent UX & hybrid UI - aka holistic AI-user experience design.
To achieve this, UX designers need to jump back to the foundations: basics of cognitive psychology, perception, memory, reasoning and more fundamentals of human brain.
For the emerging AI unicorns, it's crucial to understand that scaling and AI adoption hinge on user-centered AI design as a fundamental pillar.

If you're intrigued by the world of user-centered AI, be sure to subscribe to our newsletter and join us on this exciting learning journey.

Human-AI Emotions

It’s Not a Computer, It’s a Companion! | Andreessen Horowitz

enerative AI models will fundamentally change our relationship with computers, putting them beside us as coworkers, friends, family members, and even lovers. Most of the attention around LLMs thus far has focused on how they’re automating more traditional tasks—like customer support, research, document drafting, and summarization—but when you look at what’s driving emergent consumer use cases and excitement, AI companionship leads the way.

This is just the beginning of a seismic shift in human-computer interactions that will require us to re-examine what it means to have a relationship with someone (person or bot). We’re entering a new world that will be a lot weirder, wilder, and more wonderful than we can even imagine. This post provides a glimpse of the early activity we’ve seen, but we’re confident that there’s much more happening in the far flung corners of the Internet—and we can’t wait to see AI companions take their rightful place alongside the rest of us.

User-Centered AI

3 Wishes for AI UX -by Jacob Nielsen

By far, the most crucial wish is #1: having strong UX involvement in planning, designing, and implementing all AI products, from foundation models to vertical applications. This is my gold medal goal, and if it happens, the silver and bronze goals will be less critical because similar improvements will follow due to a strong UX impact on AI. Even though the low-hanging fruit is real and should be picked first, the most critical issue for the future of artificial intelligence is for these companies to rapidly advance up the UX maturity scale and build high-powered UX teams and repeatable UX processes. There are easily several hundred percent productivity gains for the world’s users (which will soon be virtually every company in the world) if AI products could be built from the ground up to serve human needs and respect human limitations and capabilities.

Design & AI

Elad Gil Fireside w/ Dylan Field - CEO of FIGMA | Design & AI

We're exploring a lot around what it can mean for Figma and for designers and how can we make it so that designers are able to collaborate with AI better. But I think that outside of Figma there's basically every industry probably will be touched by this. And I think it's super interesting the pace at which this is happening. Gosh. Even over the last three months, the number of papers that are coming out in different new fields using some of these models and ideas is staggering. And I just think it's a completely new tooling method. And even if we just pause it at the current technology we're at today, which obviously is not the case. That's already world changing for pretty much every single segment of every market.

HCAI - Human-Centered Artificial Intelligence

Introduction to Human-Centered Artificial Intelligence - by Lex Friedman

Human Centered AI in the 21st Century Prediction: AI systems will become more & more learning based Corollary: Smarter AI is achieved through:

Better machine teaching (optimizing data annotation) human centered
Better machine learning (optimizing learning algorithms) current focus

Ethical and safety implications of learning based AI systems:

AI will not be provably safe → Human supervision is required
AI will not be provable fair → Human supervision is required
AI will not be perfectly explainable → Human supervision is required

Solution: Human Centered AI

Deep integration of humans into the data annotation process Deep integration of humans into real world operation