On Making
TLDR: I gain a lot of fulfillment by making things. I don't consider things built by others at my request to be made by me, and are therefore much less fulfilling. And then I feel sad. This article starts strong and then heads off into the weeds.
Disability Dongle
Disability Dongles are contemporary fairy tales that appeal to the abled imagination by presenting a heroic designer-protagonist whose prototype provides a techno-utopian (re)solution to the design problem. Disability Dongle rhetoric instills in students the value of a quick fix over structural change, thus preventing them from seeking out, participating in, and contributing to existing inquiry. By labeling these material-discursive phenomena—the designed artifacts and the discourse through which their meaning is constituted—we work to shift the focus from their misguided concern about our bodies to their under-analyzed intentions and ambitions.
Ideation with Generative AI—in Consumer Research and Beyond
Abstract The use of generative AI (genAI) in consumer research is rapidly evolving, with applications including synthetic data generation, data analysis, and more. However, their role in creative ideation—a cornerstone of consumer research—remains underexplored. Drawing on the human creativity literature, we propose that ideation with genAI is facilitated by its productivity and semantic breadth, which are psychologically analogous to the dual pathways of persistence and flexibility in human ideation. Further, we distinguish between the utility of genAI as a key ideator versus humans as key ideator, conceptualized through the genAI ideation roles of Designer and Writer and of Interviewer and Actor. While genAI excels in generating incremental improvements, its potential for groundbreaking innovation could be unlocked by leveraging its ability to prompt human creativity. This article advances the theoretical and practical understanding of genAI in ideation for consumer research, offering numerous practical guidelines for integrating generative AI into research while emphasizing human–AI collaboration to achieve radical insights.
Quotes
I have a theory, which has not let me down so far, that there is an inverse relationship between imagination and money. Because the more money and technology that is available to [create] a work, the less imagination there will be in it.
Quotes
I have a theory, which has not let me down so far, that there is an inverse relationship between imagination and money. Because the more money and technology that is available to [create] a work, the less imagination there will be in it.
How to be more creative in seconds!
Technology is a Siren Song
Orangutan thinking This started with a question I asked myself: How do our minds change when we can receive a plausible, informed, and convincing answe...
What neurodivergent people really think about the words used to describe them
Research reveals a clear preference for how neurodivergent adults want to be described, though not everyone agrees.
On Writing #3
Periodically I like to gather various observations about writing, and share my perspective.
Anthropic on Twitter / X
New Anthropic research: A global workspace in language models.Of everything happening in your brain right now, only a tiny fraction is consciously accessible—thoughts you can describe, hold in mind, and reason with.We found a strikingly similar divide inside Claude. pic.twitter.com/aLUPBifxth— Anthropic (@AnthropicAI) July 6, 2026
The 1960s Art School Experiment That Redefined Creativity
A groundbreaking study revealed that the most compelling artists seek to find problems, not solve them.
I'm thinking about what *generatives* are most applicable in the atmosphere — per Kevin Kelly, "better than free" qualities that can't be copied even on the internet: edge.org/conversation/kevin_kelly-bett… Things like contextualization, personalization, sensemaking…ideas? Need to write about this more!
“The task that generative A.I. has been most successful at is lowering our expectations, both of the things we read and of ourselves when we write anything for others to read.” — Ted Chiang
Why A.I. Isn’t Going to Make Art
www.newyorker.com
