With global temps at peak in several areas of the world, the BBC covers how critical tech infrastructure is impacted by high heat.
Tech
I found this piece from an anthology celebrating 50 years of women’s studies, which explores the intersection of scholarship and publishing practices 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.
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.
Some media and ad-tech operations hire “clippers,” people who cut and distribute high volumes of short video across social platforms, to manufacture cultural relevance. The strategy in short: volume generates attention, and attention confers legitimacy.
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.
How early blogging tools like Movable Type made reverse-chronological posting the path of least resistance, killing the curated, librarian-style personal homepage and locking the whole web into the chronostream.
For those who love to post, a guide to the Internet of the future.
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.
Some contemporary thoughts from Ana Rodrigues on the perennial question of being a “woman in tech.”
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.
It looks like Wordpress has produced a short-form blogging app that duplicates the model we are trying over here on the even-more-indie web. I might give it a spin.
I’m reading about trends in book and phone bans in American public schools, and reminded that reading novels was once considered an idle and immoral pasttime, just as internet use is today. This 2016 article from JSTOR goes into the history of reading books and the fear that it “enfeebled the mind.”
Fellow Madisonians, someone pulled together a website ranking local businesses in Madison by how local they are (by what criteria, idk). In my experience, this is one way we’re likely to see AI used in the next couple of years, via prototyping and/or executing ideas that result in dynamic websites.
Centaurs and Cyborgs on the Jagged Frontier by Ethan Mollick in 2023: “On some tasks AI is immensely powerful, and on others it fails completely or subtly. And, unless you use AI a lot, you won’t know which is which.”
Last night I had dinner with a friend in tech who recently attended a training on AI and analytics, where they made the observation that we’re in the “Napster era” of artificial intelligence. It’s an imperfect comparison but useful to consider.
I’ve posted a couple of times about instances I’m aware of where people are using AI in pro se court cases, especially family courts. A new study shows evidence of increasing numbers in pro se cases at the federal level, exacerbating existing bottlenecks. Many trade-offs abound here.
A professor asked students to self-report AI usage on their homework, leading to lots of confusion and uproar. Points aside, it’s clear people want more clarity up front about when and whether to use LLM tools. In the meantime, treating students like they’re guilty until proven innocent is a bad MO.
I missed this 2025 article by Noah Hawley on Vonnegut, war and the atomic bomb, and it is worth the time.
What does it mean for the culture when everything (everything!) is content, even war and mass shootings?
Timothy Chester offers some thoughts on the place of AI-assisted software development in a modern research university, and suggests that just because you can doesn’t necessarily mean you should.
Out: Twitter on a vape. In: AI-powered crypto vape. Is this real? Who can tell anymore.
A nostalgic read on how music nerdery bloomed online.
More on user-generated content marketing and how it works. UGC is a powerful example of “social proof,” where people’s parasocial tendencies are leveraged to boost brand credibility and conversions. This is the consumer psychology behind celebrity and influencer sales and endorsements.
Watching the fallout: Fans discovered that the band Geese benefitted from a hefty marketing campaign. Folks are debating whether this makes Geese a “psy-op” or merely “sell-outs”, to use an old term of art. Meanwhile the marketing firm behind the push is getting a ton of attention in its own right.
Tom’s Hardware on Mythos and marketing hype. Additional commentary from Michael Corn, asking whether Mythos coverage reinforces or establishes perceptions about cybersecurity.