Dave
@davekim
Dave
The Dandy’s aesthetic ruses reveal the performativity of identity itself, the fiction of race, gender and all other categories. For their final trick, the Black Dandy makes themselves visible but not fully legible. The trickster is unknowable because he is always in disguise.
I, Dandy
“visible, but not fully legible”
Which does make me wonder: in the face of narrative abundance, what is the appeal of media? Like, it will still be appealing, I know that, but I’d like to understand how precisely.
Interconnected, a blog by Matt Webb
Part of the problem is metaphor. We’re still importing models from legacy media, even as the technical capabilities of the web expand. The “desktop,” the “page,” the “homepage.” But what if we started from scratch with forces native to the web, such as time, movement, depth, interaction?
What even *is* a website?
Here are topics we should be talking about:
- What’s the right balance of generalizable knowledge vs specific, contextual knowledge, how does that vary by type of problem, and who holds generalizable knowledge?
- What elements of systems change are achievable at what levels — local, national, regional, global — and how can the right people get a seat at
Friday Notes, December 1, 2023
Matt Webb describes four areas of AI user experiences.
Looking at this landscape, I’m able to see different UX challenges:
With generative tools, it’s about reliability and connecting to existing workflows. Live tools are about having the right high-level “brushes,”” being able to explore latent space, and finding the balance between steering and helpful hallucination.
With copilots, it’s about integrating the AI into apps that already work, acknowledging the different phases of work. Also helping the user make use of all the functionality… which might mean clear names for things in menus, or it might mean ways for the AI to be proactive.
Agents are about interacting with long-running processes: directing them, having visibility over them, correcting them, and trusting them.
Chat has an affordances problem. As Simon Willison says, tools like ChatGPT reward power users.
The affordances problem is more general, of course. I liked Willison’s analogy here:
It’s like Excel: getting started with it is easy enough, but truly understanding it’s strengths and weaknesses and how to most effectively apply it takes years of accumulated experience.
It’s like Excel: getting started with it is easy enough, but truly understanding it’s strengths and weaknesses and how to most effectively apply it takes years of accumulated experience.
Which is not necessarily the worst thing in the world! But just as there are startups which are essentially an Excel sheet with a good UI and a bunch of integration and workflow, and that’s how value is unlocked, because of the Excel affordances problem, we may see a proliferation of AI products that perform very similar functions only in different contexts.
One way I visualize this relationship between the form of traditional UI and the function of AI is through the metaphor of a ‘workbench’. Just as a carpenter's workbench is familiar and purpose-built, providing an organized environment for tools and materials, a well-designed interface can create productive context for AI interactions. Rather than ... See more
Karri Saarinen • Design for the AI Age
AI Horseless Carriages | koomen.dev
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