As I read online (and watch videos on YouTube), I bookmark resources I find interesting and useful. I share these links about once a month here on my blog. This post includes links related to AI ethics and challenges, tips for improving AI image and audio results, UX research techniques, and Articulate Rise.
AI ethics and challenges
AI and Branding 2026: Copyright Risks for Content Creators
Harriet Moser generates a lot of fantastic AI images; she’s one of the people I follow on LinkedIn for inspiration with her delightful visuals. This blog post on her site is much more serious though. Just because you can put celebrities and brands in your AI images and videos doesn’t mean you should. Get an overview of the copyright risks for content creators in this post.
My Recommendation:
Invest in properly licensed AI tools and original content creationMaintain human oversight and creative directionDevelop distinctive brand identities rather than imitating othersCommunicate transparently about AI useRespect intellectual property rights as a fundamental ethical standard —Harriet Moser
The Shape of AI: Jaggedness, Bottlenecks and Salients
Ethan Mollick describes one of the challenges of working with AI: its capabilities are very jagged. AI can be really good at some tasks but terrible at others, and it’s not always easy to predict where it’s most useful. When weaknesses that create bottlenecks are identified, AI companies focus development in those areas. Just because something is a weakness now doesn’t necessarily mean AI will never be able to do that task.
You can see how AI is indeed superhuman in some areas, but in others it is either far below human level or not overlapping at all. If this is true, then AI will create new opportunities working in complement with human beings, since we both bring different abilities to the table.
The exact abilities of AI are often a mystery, so it is no wonder AI is harder to use than it seems.
A system is only as functional as its worst components. We call these problems bottlenecks. Some bottlenecks are because the AI is stubbornly subhuman at some tasks.
Bottlenecks can create the impression that AI will never be able to do something, when, in reality, progress is held back by a single jagged weakness. When that weakness becomes a reverse salient, and AI labs suddenly fix the problem, the entire system can jump forward.
—Ethan Mollick
Why is Everyone So Wrong About AI Water Use?
Hank Green explains why it’s hard to figure out how much water AI actually uses and why different sources report wildly different results. It depends on how you measure the use (including training). The quick answer is that you should be skeptical of any single number for AI water use that doesn’t include the explanation of how they got to that number. The slightly longer answer is that the water use is often significantly overstated. It’s not nothing, but the impact of water use for AI is much lower than things like golf courses or growing corn for ethanol.
Fairly Trained certified models
Fairly Trained is a nonprofit that certifies AI models for using only licensed content for training their AI. The list of certified models mostly includes AI music generation tools currently, but this is an interesting idea for improving transparency around AI training.
Tips for AI images and audio
The #1 AI Image Trick You’re MISSING – Ideogram Character in FLORA
This tutorial shows how to use the Ideogram Character model within the Flora node-based AI canvas tool to create multiple images of the same character in different settings or styles.
Best practices | ElevenLabs Documentation
Eleven Labs has documentation on how to control pauses, pronunciation, and emotions in their voices.
UX research techniques
User Experience Research Techniques for Instructional Design
Rather than guessing which designs will work better for users (which we do a lot of in L&D), borrow techniques from UX. Connie Malamed summarizes multiple UX research techniques. Note that a lot of UX research can be done pretty cheaply and simply. You don’t need hundreds of people to test for many of these. Small scale usability testing with 4-6 people can give you useful results.
You can use A/B testing software on learning portals, mobile apps, and other online resources when traffic is high. Otherwise, consider a manual A/B test, which would be more like typical observational usability testing but for alternative designs.
For example, you could observe a good sampling of audience members using two different prototype designs. Check whether the participants understand the instructions, respond to the design, or are able to work through a game interaction. Collect data and compare the results of each design.
—Connie Malamed
Articulate Rise
Articulate Rise: The Emperor’s Getting Dressed
Zainab Fawzul takes a critical look at Articulate Rise. She argues that even though Articulate has been doing some more substantive updates to Rise recently, it’s still lacking some highly useful requested features. Multiple external additions have come out to help fill the gaps in Rise’s capabilities.
Additional curated resources
Check out my complete library of links or my previous bookmarks posts.
