Writing, teaching and consulting for a safe, compassionate internet. Explaining risks and opportunities of digital so people can make better choices for themselves and for the wellbeing of others.
AI
The concept of "generative" suggests that the tool can produce what it is asked to produce. In a study uncovering how stereotypical global health tropes are embedded in AI image generators, researchers found it challenging to generate images of Black doctors treating white children. They used Midjourney, a
accessibility
"Accessibility has failed as a way to make computers usable for disabled users." Thus begins a newsletter by Jakob Nielsen. And had it not been written by someone a great many people take seriously in the UX industry I likely would just have dismissed it. But seeing how
newsletter
An image of ChatGPT solving a captcha was spread far and wide recently. The most beautiful thing about the image is of course that it hadn't solved the Captcha. This made it a fantastic stepping stone for talking about the many illusions of technological advancement. đź’ˇIf anybody knows
AI
There are many checkpoints for the EU AI Act to pass through before it becomes legislation and before the law is applicable for all types of AI tools. While we are getting closer to a final vote in the European Parliament, there is some confusion as to when the law
humor
I remember when the newsletter service Mailchimp and its monkey mascot had a tone-of-voice that was full of jokes and whimsiness. Many found this annoying or offensive (either generally or after prolonged exposure). In the end Mailchimp were compelled to implement a setting so that people could switch off the
It is a strange world we live in now, wherein the output of a computer perfectly following its programming can be said to be "hallucinating" simply because its output does not match user expectations or wishes. And across trusted professions, academia and media people are repeating that same
AI
I made this diagram as an explanatory model for showing the relationships between different actors when it comes to AI development and use. It gives you something to point at when showing for example who finances the systems, who contributes to the systems and who benefits or suffers from them.
AI
I read the executive order on AI from the White House, wrote a summary and used an AI-powered video generator to create the appearance of me presenting it. In accordance with suggestions in the order, the video is clearly labeled. 🗣️Interested in trying out the HeyGen tool? Sign up using
digital ethics
In the one-minute video below I am speaking seven languages. In truth, I can speak two of those. None of the audio is actually me speaking, even if it sounds very much like my voice. And the video? Despite what it looks like, that’s not me moving my mouth.
digital ethics
Understand the stages of machine learning where bias can, and often will, contribute to harm.
accessibility
I see more and more people faking bold and italic text on LinkedIn, and other social media, using Unicode characters. This is detrimental to accessibility, findability as well as predictability. Here is an example that you may or may not see depending on your client for viewing this: * Example of
usability
Attempts to classify people into intelligence categories has been going on for many hundreds of years, but none have perhaps proven as prevalent as the intelligence quotient (IQ). The origins of IQ can be traced back to a 1905 test designed by French psychologists Alfred Binet and Théodore Simon to