TechCrunch reports on the problems inherent to AI-generated restaurant advertising - it looks wrong.
AI
A composition teacher friend shared this paper on social media: Lester Faigley’s “Literacy after the Revolution”, the essay version of his 1996 CCCC Chair’s address. In it, the author argues that the economic impacts of the digital revolution had begun to undo an older commitment, formed in the Civil Rights era, to teaching literacy as a path toward equality. He further argues that writing instruction was being reorganized around tools owned by a few firms (then: Netscape, Microsoft) at a moment when wealth was concentrating upward. Faigley left us with the question of whether educators can hold onto literacy-for-equality while the tides run against it.
Thirty years later, the worry has a new face: AI will do young people’s writing for them and their thinking with it. Ultimately, Faigley believed the need for the skills that composition teaches will keep growing, not despite, but because of our need to convey information in and around that technology and the humanity it serves in a complex society. Does that suspicion hold water today?
Computah: Make it a link
Thursday, August 13, 2026
I spent a little time with the blog last night and pulled together two new site features using Claude Cowork. The last time I experimented significantly with Claude like this was to use Claude chat to build the link log from scratch, walking it through my thinking in plain language, then copying and pasting its suggestions into the backend of the site and hitting publish. This time I used Cowork, the tool that runs in the browser, and it clicked through the screens itself, fully taking on the execution of tasks. I have some coding skills, but not the kind these changes required. If I were taking this on, I would need YouTube, Hugo for Dummies, and my own personal IT guy, and still probably couldn’t pull it together.
Last night I asked a few things of Claude: I asked Claude Cowork to get into the backend of the micro.blog site and change my theme to link each line in the linklog back to my original post. The date field in the right column now links back to the original post for each link logged. No problem, easy request with easy execution. I made the request, confirmed the plan, and went about my business while Claude made the edits.
I also asked it to analyze my post content and suggest category tags for groups of content, then to label that content correctly in the backend. Claude reviewed about 500 posts and suggested I add a few new categories to my blog: AI in Practice, Books & Reading and Writing & Language. Then I set up some auto-filters to run at publish time to automatically categorize posts based on keywords moving forward.
Finally, I manually added the archive page, which lets you sort posts by category or year. This means I now have a functional archive here. Enjoy my anodyne thoughts, dear reader.
Adjacent to my day job, I’ve been toying with Claude Pro now for about a year; in my experience, it has improved significantly within the last six months. It’s not perfect: my requested edits were completed, but it also changed the CSS on the linklog so some of the text is too light to read, which I didn’t ask for and don’t want. But it has arguably extended my ability to execute on work that requires skills I don’t otherwise have (such as design and coding). What I do bring to the table is an expansive practical background in publishing and production, and all the language to describe it.
A friend of the blog shared the Embroidered Computer, a programmable 8-bit computer created by using a combination of magnetic and glass beads, gold wire, and traditional gold embroidery techniques to fix material elements to cotton cloth. When complete, it has the processing capacity of a 1950s mainframe computer without the modern silicon microchip. Something about this reminds me of Ellen Ullman’s observation that computers are made of boxes and wires, written on chips and tape. (via)
Claude is launching an AI watermark, one that users can’t opt out of (but can easily outsmart). As internet god Notopoulos wrote, “Claude’s watermarking poses the question: Are you willing to proudly own that you write with AI?” More: What is an AI watermark and how do they work?
I can’t believe it’s mid-August. I’m terribly behind on my reading list. Still, I did want to draw attention to this entertaining and extremely shareable article on the glory of Record Head, a legendary record store in Milwaukee. Make sure to watch their public access TV commercials at the link.
The knitting community is one of the great deliberative communities of the internet, and as they’ll happily tell you, knitting and fiber arts are closely tied to industrial and computing history. It’s really hard to pull one over on knitters online, because they have a deep and different relationship to the technical side of their hobby and all of the political and tech history behind it, and especially how it relates to computer engineering. I was thinking about that dynamic while reading about the latest fracas around YouTuber Hank Green, who is taking time away from public life after being called out by his audience, when his AI use was perceived as being in contradiction with his public persona. If you want to go down the rabbit hole on this, here’s a good video summary.
Ultimately viewers are reacting negatively to Green’s admission of using AI to quickly aggregate research to drive his content creation, suggesting that he lost his own creative discretion amid a growing demand for online content. But in the meantime, his technical inaccuracies were paired with completely avoidable gender bias alongside the AI use, which drew additional scrutiny from technical experts. It wasn’t his first go-round with the knitting community, it turns out. Was the bias Green’s or facilitated by his use of the tools? Debate ensues.
I found this American Affairs article on the insidiousness of ad tech quite relevant. It focuses on foreign propagandists’ exploitation of social media, but it’s just as instructive for thinking about ad tech as tech, channel and product, and its entwinement with social media as infrastructure.
Garbage Day uses Jimothy to trace how virality works on the internet of 2026. Related: this story on how the algorithm has prevented us from producing a single “song of the summer.”
Scheduled send as alibi? Nice try, Costanza.
The Atlantic takes on the prevalence of the “it’s not X, it’s Y” construction in AI-generated writing, highlighting the semantic roles in sentence construction that differentiate ideas for clarity. Chatbots seem to like this construction, despite how clunky it sounds to the human ear.
Finished reading: Yesteryear A Novel by Caro Claire Burke 📚
Dan Hon made me laugh with “carbon-based chauvinism.”
Among other disappointing SCOTUS announcements today: Supreme Court Rejects Lawsuit Alleging Roundup Weedkiller Caused Cancer. In a previous life, I worked in the same college as a cancer researcher who developed twenty years of conclusive research that Roundup causes cancer in dogs by studying Scottish terriers. Scotties, it turns out, tend to be susceptible to bladder cancer, and thus make good candidates for related research when cancer is present. For several years, I got to witness a veritable army of Scottie dogs dressed in bowties and plaid jovially trotting in and out of our veterinary research hospital to seed her research during their cancer treatments in West Lafayette.
What I learned during that time is that a great deal of veterinary research is about looking for health patterns across species. While not all carcinogens act identically across species, most known cancer-causing agents affect both dogs and people in similar ways. Because dogs share our homes and have similar biological responses to toxins, scientists track canine cancers as an early-warning system for human health risks and to research viable interventions to treat them.
In any case, while I don’t know the ins and outs of the specific laws in play here, this is a disappointing outcome when it comes to the science.
Another old article on the emotional toll of being an internet personality and a woman with a platform in the public sphere. I’m quoted briefly: I intentionally broke my social presence when I stepped away, which gave me necessary peace but made it harder to claim my work in this arena over time.
I attended the Clayman Institute’s talk on Gender, Power and Artificial Intelligence earlier this month. They now have the session shared on YouTube for posterity. There are many topics and ideas here to chew on as this AI moment develops, and I recommend giving their angles some consideration.
There are enough common signs of AI writing now that the subject has its own Wikipedia page. Via John Gallagher’s latest on “template rhetoric.”
The Pope provides a vision for living with artificial intelligence (gift link).
The Harris digital campaign head does a post-campaign autopsy of the conditions that impacted the DNC’s 2024 presidential strategy, with lessons learned. I enjoyed this read because it was so close to the work that there are relevant takeaways for other public marcomms practitioners.
After listening to the talk yesterday, I was reminded of this article describing a journalism model for using AI that shared some parallels with D’Ignazio’s research.
Gender, Power and AI: Wrestling for the soul of the network, again
Thursday, May 14, 2026
Stanford’s Clayman Institute ran a virtual panel this morning called “Gender, Power, and Artificial Intelligence,” with Safiya Noble (UCLA), Catherine D’Ignazio (MIT), Angèle Christin (Stanford), and moderator Genevieve Smith, a Clayman Institute Postdoctoral Fellow. The panel applied principles from feminist tech studies to the current moment, and covered how gender norms get encoded in data and reproduced by AI systems, and discussed whether the technology has real capacity for equitable design and implementation at scale.
Noble’s argument throughout is that the governance conversation has gotten too high-level and universalizing while the actual outputs of these systems have profound day-to-day consequences for specific people today. She named the role of AI in the recent gerrymandering of Louisiana and Indiana as examples, and called for tripling down on long-term social science research about AI’s impacts. She also pointed out that philanthropy is retreating from feminist academic and organizational work because that work originates from the same dynamics that critique philanthropy itself, precisely at a point when this research is sorely needed. A lot of money is moving in AI, and very little of it is funding the people best positioned to study how it impacts everyone downstream.
D’Ignazio was asked directly whether feminist generative AI at scale is possible. Her answer was no, with caveats, given who owns the technology today and the current emphasis on profit motive. She suggested it is more important to consider how to organize around our relationship to technology, and how we might approach questions of profit and ownership, policy and decision-making, and data and tech governance.
She provided an example of a reasonable use case by walking us through a project from her Data + Feminism Lab. The example is documented at length in her recent book “Counting Feminicide: Data Feminism in Action,” where her team partnered with activists who scour news reports to document the gender-related killing of women and girls, including cisgender and transgender women. The lab built a very lightweight AI-based approach that streamlines the scanning and identification of news stories as possible cases to include in their project, supercharging their work (note: very similar to how the NYT uses AI to analyze data for reporting). In this example, the AI’s job is task-scoped, democratically co-determined with the people who use it, and small. Smith picked this up: there is an idea baked into the current LLM moment that AI must scale to make it marketable, and the alternative is using purpose-built models that are right-sized against a body of work.
Christin spoke at length about how embodiment is one of the primary focuses of feminist theory, and how AI perpetuates the “disembodied” illusion of technology, and how this dynamic shows up in everything from the marketing to UX to user comprehension. This spoke to my thoughts on how the single-interface design of LLM chat reproduces Haraway’s “god trick,” knowledge that presents as universal while concealing the specific and situated position it comes from.
The parallel I kept returning to, listening to this, is one I think about often with my own cohort of early bloggers, women who grew up alongside the rise of the internet — and then the rise of ad tech. The internet of the late 1990s and early 2000s was being shaped by several camps: writers, students, information architects, and user-centric researchers who saw it as an information access network and a space of possibility; entrepreneurs and opportunists who saw it as a channel for marketing, monetization and extraction; and a smaller boycott camp that wanted to limit and refuse the whole personal computing and digital revolution altogether.
It was generally considered weird to be a girl on a computer or a woman on the internet — so weird that many of our peers didn’t recognize us at all — and we were there anyway, making stuff, witnessing, learning, advocating, producing, influencing. So when I watch some of my old peers, many of whom are professional writers and academics today, treat LLMs as a question of refusal rather than a condition to engage with critically, I worry we are abdicating a responsibility at precisely the moment when our technical and rhetorical expertise applies. Their refusal has good logic: user-centric researchers and communities engaged extensively with the early internet and the extractive camp won anyway, so why expect a different outcome here?
But Noble’s work on algorithmic bias attributes that failure not to engagement, but to the institutional and financial disadvantages that user-centric approaches operated under relative to gargantuan commercial interests. David and Goliath. That gap does not close through abstention. Understanding the trade-offs around tech, producing knowledge and analysis that does not depend on investors and marketers to frame the platform and the questions, requires presence. Refusal cedes so much ground.
Overall, the recommendations from the panel were practical. Noble called for people with capital (and the political will to spend it) to consider how to put money toward socially responsible research and development. D’Ignazio called for alternative funding infrastructure outside of venture capital logic, and pointed at European digital sovereignty models as worthy of consideration here. She also gestured at the popular AI Skeptics reading group as one current example of mad-and-commiserating-as-organizing that is creating safe psychological space for people to talk about AI and its tradeoffs. Christin’s recommendation was community organizing, on the grounds that LLMs are unpopular with a lot of people who feel there is no space to say so, and that finding those spaces is itself worthy because it provides shared language and awareness of others’ knowledge and experiences.
Personally, it was refreshing to hear reflections on the work (and the feelings) of being inside institutions that are being reshaped by AI, and being responsible for some of how that reshaping gets communicated and absorbed. I’m thinking about the incredible value of interdisciplinary governance, and how the commitment to governance is a specific position, and all the margins to consider.
Further reading:
Catherine D’Ignazio and Lauren Klein, Data Feminism. The foundational text on applying intersectional feminist thinking to data science practice.
Catherine D’Ignazio, Counting Feminicide: Data Feminism in Action. Extended case study of the grassroots data activism project D’Ignazio described on the panel.
D’Ignazio et al., “Feminicide and Counterdata Production.” Research paper on the counterdata methodology behind the femicide tracking project.
D’Ignazio et al., “Data Feminism for AI.” Conference paper extending the data feminism framework to questions specific to AI systems.
Safiya Noble, Algorithms of Oppression. Noble’s study of how commercial search engines reinforce racism and sexism through their ranking systems.
Donna Haraway, “Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspective” (1988). The original essay where Haraway introduces the god trick and the case for situated, embodied knowledge against the view from nowhere.
“Two things can be independently true about social media. First, there is no evidence that using these platforms is rewiring children’s brains or driving an epidemic of mental illness. Second, considerable reforms to these platforms are required, given how much time young people spend on them.”
Garbage Day on whether Bluesky was a net negative for left politics. I’d argue the most important thing Bluesky did/does is technical, by producing the AT protocol that underlies it, thereby building out the federated web. Distribution channels come and go, so consider posting at your own domain.
Reflections on teaching fiction writing in the age of AI, from a professor with ten years of classroom experience teaching writing at MIT.
Why I'm broadly skeptical of device bans in K-12
Friday, May 8, 2026
Watching a local phone ban policy snake through the community this week. Like others have already said, my concern is mostly related to enforcement, as we know enforcement for all school policy lands unevenly across school populations at the expense of Black students. But also, my experience is that the local school system is not communicative in a way that reinforces student and parent desires for two-way communication, especially considering the logistics of having kids who need transportation and after school arrangements.
When I was young, there was a pay phone on every corner and a central landline in every home. We don’t live in that world anymore – in our world, phones and other personal devices are part of our daily processes for school, work and family logistics and communication with friends, family and the broader world. Same for kids with devices.
None of this means screens are neutral or that Jon Haidt is entirely wrong about attention and comparison dynamics. But Haidt et al diagnose a genuine social problem and locate the cause as technology design, then arrive at solutions that are driven by individual consumer behavior. Ultimately he does not call for taxing and regulating algorithmic platforms, regulating algorithmic amplification of distress, regulating algorithmic amplification of marketing, reducing economic precarity, or doing anything about climate change linked to tech. All of the behavioral changes indicated (device bans, Faraday bags) set up fights between kids and adults on phone access at the individual behavior level, fights with consequences that generally land harder on certain students.
While this issue roils locally, my kiddo’s locker was broken for two months this year, and while waiting for repair, she got dinged for having her device in her pocket in class when the locker wasn’t a secure option. She had shoes stolen from her locker in the meantime, proving the point.
I spoke with my kiddo at length to get her thoughts. Her takeaway as an 8th grader is that kids have second and third secret devices that they hide from parents and teachers already – often, mom and dad’s old devices slipped from a junk drawer and connected to wi-fi. She suggested we adults don’t fully appreciate the kids’ ingenuity around their devices, and how they view their phones and tablets as the means to get and stay connected with one another.
While talking, I was reminded of the dance between students and the school system’s IT department during the COVID-19 shutdown. In our community, the kids were in remote learning for a full year and a half, and the IT department chased them around their approved digital tools like a game of whack a mole, shutting down access to chat and collaboration. In the meantime, almost no socialization happened between students that wasn’t directly observed by teachers, on camera. By 2021, the kids were engaged in secret, digital note-passing, chatting within Google docs and slide decks to avoid teacher surveillance. Where there is a will, there is a way.
It’s like the phrase “turtles all the way down,” but turtles are marketing.
A new group is attempting to map influence in the AI industry, with the goal to “produce a structured, shareable, and dynamic resource that identifies who is working on what, where the gaps are, and which partnerships might form across ideological and organizational lines.”
A new study suggests that people who use AI for writing are more able to detect AI writing than automated scanner tools. My current LLM pet peeve is how they use language like load-bearing, structural and legible to describe most ideas.
“Amazon has launched a new feature that uses AI to generate a short, podcast-like audio segment where two AI ‘hosts’ discuss the merits and reviews of a specific product.”