Tech on F L O T I S S E R I E 🕳️ 🐇

Wed, 28 Oct 2026 08:24:21 -0500

Fun: I discovered one of my old electrical metering contacts lives nearby and invited him out for a coffee. He was a fellow townie, old enough to be my father, who worked with and alongside the engineers in a factory environment, now retired. I want to catch up and pick his brain about the current era. The last time we talked was in the IOT, smart energy era when we were putting Bluetooth and Zigbee automation into everything we did.

Customer service 101

Fri, 23 Oct 2026 16:27:00 -0600

🎵 : Waiting Room - Fugazi

AI’s growth has widened the understanding gap between leaders and the people who use these tools most, as emerging tech tends to do. I’m tracing emerging leadership approaches with juice; this Intel interview argues that leaders should weigh what we lose when we cleave workers from relational processes through automation. (And: avoid the ways that proofs of concept become pitfalls.)

I’m seeing some early chatter online about the return of old-school customer service models, where people talk to and resolve issues in real-time for other people (they treat you right!). Demonstrating solid customer service values and elevating audience perspectives is a plus for any org in the current business environment — so much CX is about keeping customers and critics at bay. Investing in a call center would be a wild flex for an emerging leader. Let’s see if it’s real or if it’s three TikToks in a trench coat.

Tue, 06 Oct 2026 21:21:55 -0500

Reading about critical code studies and AI rhetoric.

Sun, 27 Sep 2026 08:31:53 -0500

Trend watch: Defanging consumer surveillance technology by emphasizing cuteness.

Fri, 25 Sep 2026 18:19:55 -0500

Konstantinos Komaitis has started a ten-part series at Techdirt called The Metric Is Not the Mission. It traces how Big Tech went from building the open internet to reshaping it around its own metrics and incentives. Part I argues that the recurring fights over content moderation, privacy, recommendation algorithms, and AI are symptoms of one long shift.

Search, social networks and recommendation systems solved real problems of navigation and abundance. Eventually each solution becomes the environment itself, and continues to be optimized for incentives that benefit the companies behind tech solutions. His phrase for how we’ve been reading the news about tech is “paying attention to the weather while overlooking the climate.”

The historical framing will only pay off if later installments name specific mechanisms and the people who made the decisions, and I’m reading the rest to see whether they do. New parts come out twice a week, with a full PDF at the end.

Fri, 25 Sep 2026 07:19:04 -0500

Grief resources from fellow internet long-hauler Lenée.

Tue, 22 Sep 2026 07:58:45 -0500

Machines and machine learning change the ways we think about humans and humanity. In cyberspace, we create “digital doubles,” or data doubles, or digital human twins (DHTs), and now these digital doubles move through assemblages of AI systems. New politics are emerging from this tangle.

Tue, 22 Sep 2026 07:52:29 -0500

Reading about personalized LLMs and the risks of the digital twin metaphor.

Mon, 21 Sep 2026 13:25:53 -0500

🎵: Witch Doctor - Erykah Badu and The Alchemist

Over the weekend, I asked Gemini to examine the career trajectories of the authors in this 2019 Jezebel article by Soraya Roberts, which covered the ins and outs of the major conflicts that erupted over the feminist blogs.

(I am sad to hear that Soraya passed away last month. During her research for this article, I enjoyed discussing the technical details that created these spaces and how our collective work facilitated everything that came afterward, or didn’t. I know Soraya was hanging a lot of her career on this article and felt it was poorly handled at the time, speculating it was because the voices most implicated by the research now manage the levers of publishing.)

Knowing Google has the juice for search, including all the missing bits deprecated over time, I asked it what technical and social lessons were learned, assuming Gemini could treat that work like a portfolio and provide a business analysis with the full benefits of hindsight.

Per Gemini, links added by me:

Looking back at the mid-2000s, the feminist blogosphere achieved extraordinary cultural breakthroughs, but it also operated with distinct technical and social failings and prejudices. By treating cyberspace as a purely ethereal or detached realm, bloggers unintentionally reproduced offline power dynamics, a phenomenon known as the “digital twinning” of cyberspace.

Viewed through a critical, retrospective lens, four major areas show where different choices around technology, institutional strategy, and social solidarity could have altered digital feminism’s trajectory.

1. Technical: platforms are not neutral The early blogosphere largely treated technical tools (like WordPress, Blogspot, Google Search, and ad networks) as neutral pipes rather than profit-driven entities with embedded incentives. Bloggers built incredible social capital on free or cheap third-party services without owning the underlying code or digital infrastructure. When Web 2.0 shifted toward algorithmic feeds and centralized social media (Twitter, Facebook), bloggers willingly migrated their engagement to those platforms to chase larger audiences.

Protocol-Level Investment: Instead of relying on proprietary platforms, the cohort could have invested in building and maintaining independent digital commons, including federated software, cooperative hosting collectives and shared digital archives owned directly by the movement.
Data Sovereignty: Early writers rarely anticipated how their essays, comment sections and personal narratives would be scraped, monetized, and eventually used as training data for commercial algorithms and search engines. Establishing strict open-source licensing (such as Copyleft or peer-production licenses) and sovereign archiving practices could have protected intellectual labor from platform extraction.

2. Reproducing social hierarchies online “Digital twinning” can mean several things in context, but in our case it refers to the way online spaces mirror (and often amplify) offline power structures like race, class, disability and educational privilege. While early blogs claimed to be radical open spaces, their structures often recreated corporate and academic gatekeeping.

Many of the highest-profile blogs were anchored by white, college-educated, urban writers who inadvertently treated their lived experiences as the “default” feminist lens. Marginalized writers, particularly Black, Indigenous, AAPI, disabled, and trans writers, frequently had to demand inclusion, fight for citation, or build separate spaces (Racialicious, Crunk Feminist Collective, Reappropriate, FWD/Disabled Feminists) to address the dominant blogs’ weak spots.

Resource and Power Redistribution: Rather than treating traffic and ad revenue as individual metric wins, major sites could have operated as resource-redistribution networks—directly funding, platforming, and sharing domain authority with writers from marginalized backgrounds from the outset. This is what Feministe.us aimed to do with our rotating lineup of guests, with mixed results.
Rethinking “public” vulnerability: The blogosphere heavily rewarded raw, highly personal exposure (“confessional blogging”). However, this cost was asymmetric: white, middle-class bloggers often parlayed personal exposure into book deals, while marginalized bloggers faced severe offline economic risk, doxxing and targeted harassment for sharing the same level of personal detail. Many of us also needed to earn a paycheck with benefits. Depending on your demographics, angles and timing, writing opportunities were limited, and only a small fraction of the talent generated in the collective saw durable career impacts. A more intentional approach would have prioritized pseudonyms, pen names, shared authorship, and safety-first rhetoric.

3. The siren song of individual upward mobility The most consequential structural shift was how the blogosphere interacted with traditional media and corporate capital. As more corporate outlets (Jezebel, HuffPost, The Guardian) realized feminist commentary drove clicks, they offered individual bloggers lucrative staff jobs, book deals and column spaces. This transformed a collective political movement into a pipeline for individual career advancement. As top talent moved into legacy media, independent blogs lost the labor needed to sustain them.

Building cooperative media outlets: Instead of individual writers accepting staff roles at corporate outlets, the cohort could have formed reader-owned media cooperatives (similar to worker-owned publishing models today). This would have allowed writers to earn a sustainable living while keeping their intellectual output in a community-controlled space.
Resisting algorithmic speed: Legacy media required bloggers to output somewhere between 3-10 quick, hot-take posts per day to satisfy ad-driven impression quotas. Resisting this pressure in favor of slower, deeper, “thick” theory would have preserved the intellectual rigor of the spaces instead of reducing feminism to consumable digital commentary.

4. Politics: Hesitancy to be the “fly in the ointment” Beyond technical tools and corporate pipelines, there was a profound rhetorical hesitation within many of the era’s flagship blogs to comfortably occupy the role of the “fly in the ointment,” the deliberate, disruptive presence that insists on disrupting false consensus to center genuinely aggrieved interests.

Because major blogs faced constant, bad-faith attacks from right-wing media and anti-feminists, an implicit pressure emerged to project a unified “united front.” This often created an environment where internal dissent, particularly from disabled, working-class, trans, or non-white women pointing out the movement’s ongoing failures, was framed as unhelpful infighting or a distraction from the broader political battle. The push for a polished, accessible and broadly appealing “Feminism 101” frequently smoothed over the jagged edges of critique.

Sanctifying disruption as methodology: The blogosphere could have explicitly framed the “fly in the ointment” not as a threat to solidarity, but as the primary engine of accountability. Rather than managing or policing internal conflict to maintain a clean editorial brand, blogs could have deliberately designed their platforms to hold open space for radical and uncomfortable grievances within the plurality of feminist thought.
Protecting uncommodifiable voices: Corporate platforms favor palatable, easily shareable commentary by design. By shying away from deeply uncomfortable, non-mainstream grievances, the blogosphere left a vacuum filled with endless explainers. A more resilient model would have actively protected and amplified the most uncompromising, “unmarketable” voices, including those whose positions could not be sanitized for an ad sponsor or a cable news segment.

By failing to fully institutionalize the “fly in the ointment” as an essential, protected role within digital spaces, the early blogosphere left itself vulnerable to the corporate absorption that eventually dismantled it. When mainstream media stepped in, it easily plucked away the polished, palatable commentary while abandoning the uncomfortable, dissenting labor that keeps a political movement expansive and honest.

Old playbook, new eyes

Mon, 21 Sep 2026 08:35:59 -0500

🎵: Veteran of the Psychic Wars - Blue Oyster Cult

When tech enthusiasts discuss federation today, they usually mean open protocols like ActivityPub or Mastodon. But in the 2000s, the feminist blogosphere was one of the earliest, most powerful examples of practical Web 2.0 federation, a decentralized, cross-site architectural network where open web standards powered a global ideas lab.

Instead of sitting inside a single corporate platform (like today’s X, Meta, or Substack), early blogs like Feministe, Reappropriate and Jezebel functioned as individual nodes in a federated ecosystem. Open protocols linked them, letting theory, critique and discussion travel seamlessly across independent servers, seeding some of the political conditions we face today.

Here is how the federated architecture of the 2000s web directly built the “ideas lab” for fourth-wave feminism:

1. Federated communication engine: CMS and protocol Before quote-tweeting or tagging existed, the open web used Trackbacks and Pingbacks. If a post on Feministe analyzed an article about reproductive rights, a writer on Racialicious or Shakesville could respond on their own site. The underlying blogging software (Movable Type, WordPress) would automatically send an XML RPC “ping” back to Feministe.

Socially, this created architecture for ideas: a ping automatically listed the response essay in Feministe’s comment section or sidebar. Readers didn’t just consume one blogger’s singular and authoritative opinion; they could immediately follow the thread across five different independently hosted platforms. This created an inter-site conversation tree, allowing complex ideas to be cross-examined, refined, or challenged without any single person controlling the narrative.

2. Blogroll as federated curation and mutual discovery Before algorithmic feeds dictated what readers saw, blogs relied on the Blogroll, a curated list of links in the site’s sidebar. Blogrolls formed a human-curated, decentralized routing layer. When a high-traffic node like Feministe added a smaller, independent blog (such as a disability rights blog like FWD or a smaller blog like Crunk Feminist Collective) to its blogroll, it directed server traffic directly to that independent domain.

Socially: This was a non-algorithmic way to expand the collective’s political consciousness. It allowed marginalized perspectives to build their own audiences and force mainstream feminist sites to engage with race, class, disability and queer theory. The blogroll mapped an intellectual community in real time – with strong caveats.

3. Open syndication protocols The Architecture: Feeds ran on RSS (Really Simple Syndication), an open XML standard. Readers used independent RSS aggregators (like Google Reader or Bloglines) to subscribe directly to a site’s feed.

Socially: RSS meant no algorithm stood between the writer and the reader—no engagement bait, no rage-farming optimization, and no platform throttling links. Writers could publish 5,000-word, dense theoretical essays knowing their subscribers would receive the complete text in chronological order as designed. This structural stability gave writers the freedom to experiment with complex, “thick” personal narratives and political theory.

4. Real-time stress testing and spillover moderation Because the blogosphere was a network of independent domains, each site maintained its own “house rules” and moderation policies. If a topic proved too controversial or toxic for one comment section, the conversation naturally federated outward. A reader who felt silenced or misunderstood in one blog’s comments could launch their own blog, write their response, and ping back into the original discussion.

Socially, this prevented any single author from monopolizing the narrative. It created a system of checks and balances where academic concepts (like intersectionality, rape culture, or microaggressions) were stress-tested across dozens of distinct, interconnected communities simultaneously.

Thinking about this architecture today The feminist blogosphere proved that decentralized web protocols can generate deep, movement-building intellectual work. When platforms like Facebook, Twitter, and corporate media conglomerates centralized the internet in the 2010s, they broke those open connections. Conversations were locked behind platform walls, trackbacks were abandoned and RSS was marginalized, breaking, fencing and otherwise moderating independent community connections.

Rebuilding a modern “ideas lab” with modern federated protocols (like Webmentions, ActivityPub, RSS, and static site architecture) is simply picking up the technical blueprint OG feminist bloggers used to transform digital culture two decades ago.

Fri, 04 Sep 2026 14:13:29 -0500

Manton on AGI: “As we reach AGI… I’d like to set some ground rules for myself — beliefs that won’t change as technology changes. AI will be smarter than us, but consciousness and ‘a soul’ can’t be created from computation.”

Fri, 04 Sep 2026 11:56:24 -0500

Where we’ve been: “Today’s young American women were born into a world of unfinished feminism. We have freedoms our great-grandmothers couldn’t have imagined, but also fewer rights than we did just a handful of years ago.” Plus, some examination of how ad tech and algorithmic sorting set the table.

Tue, 01 Sep 2026 18:49:32 -0500

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.

Fri, 28 Aug 2026 13:09:01 -0500

“Students who spoke to ESPN said that betting is an accepted part of day-to-day life and that they learned about their school’s gambling culture immediately after arriving on campus. A 2023 NCAA survey of 18- to 22-year-olds found that 51% of the women and two-thirds of the men have bet on sports.”

Fri, 28 Aug 2026 12:48:03 -0500

Guerrilla marketing: When someone built a fake deodorant company with a lightweight marketing plan to capture long-tail search results, she found her way into AI recommendation results, showing how brands can gain visibility in emerging discovery systems.

Wed, 26 Aug 2026 17:03:00 -0500

“We all know that you can get lied to online at any point. If you don’t get that this is an obvious lie, then you’re washed and you’re unc and you’re chopped.”

Computer Love

Tue, 25 Aug 2026 08:28:18 -0500

I listened to two great podcasts this week exploring the tangle of human/AI relationships. In “Computer Love,” the guests explore whether these relationships are good for us, and in “Your AI Companion Doesn’t Love You,” they explore the technical and business implications of these relationships. Both of these feature podcaster and writer Bridget Todd, who is promoting her new book “Love at First Prompt.” As of today, about 1 in 5 young people in the U.S. have asked a chatbot for mental health advice, and 1 in 5 high schoolers have had a romantic AI relationship.

Note: Todd’s (excellent) podcast title is a reference to Rule 30 of the internet.

Mon, 24 Aug 2026 09:41:02 -0500

Micro.bloggers: I’m interested in turning the link log into a micro.blog plug-in, but I don’t have the skill or the will to make it happen. Where should I begin?

Wed, 19 Aug 2026 17:04:09 -0500

Question for parents: How are you teaching your teens to stay safe and think about safety and security while they surf, shop, chat and learn on their digital apps and devices? Are you sharing books, articles and videos with one another? If so, which ones? I’m asking for a friend; the friend is me.

Some thoughts on linklogs and link libraries

Tue, 18 Aug 2026 19:03:19 -0500

A linklog is a dated list of outbound links, maybe a tag, and a note about why it’s worthwhile. But that little note does two things at once, and together they make for a better web.

First, it’s a way of organizing the web. The web doesn’t sort itself, so finding good information depends on someone curating and tracking interesting content, preferably on the open, free internet. It acts as a customizable bookmark library: newest at the top, tags to group items, and a line explaining why the link was worthwhile. This is similar to what del.icio.us did, where people grouped and tagged links, creating a rough filing system.

Second, it’s a social act. An outbound link points to someone else’s work, so a linklog is essentially a renewable engine for sending traffic to other people and places. It stays renewable because the content is easy to sort and remix: a URL’s relevance no longer depends on where an algorithm or activity feed happens to place it, so older links can keep resurfacing instead of scrolling out of reach. That’s the precise opposite of what big platforms design for audiences; platforms such as Twitter, Instagram and Facebook quietly bury posts with outbound links to keep your attention (and dollars) on their site and with their advertising customers, losing relevance after one interaction. A linklog explores the opposing dynamic: it willingly hands your audience and attention away while crediting your forebears, comrades, mentors and co-conspirators. It turns the rough digital filing system into a “folksonomy,” if you will.

Compare these dynamics to an algorithmic feed on a platform. An algo also sorts the flood of content, but computer magic does the sorting, and someone else monetizes your attention and relationships and hoards your data. “Engagement” for these companies is primarily a measure of how long you stay on their platform with their content. The goal is to keep you scrolling and the ad revenue rolling. But over here on the indie internet, our goal is to build human communities online and connect people to quality information, tools, ideas and processes.

Back in the day, we had blogrolls, and blogrolls came with a lot of politics around representation and belonging, and some of those choices had real-world impacts. Who you listed in your sidebar was a public statement about your community and your allegiances; however, though smaller blogs linked to bigger ones, the big blogs rarely returned the attention. That contentious dynamic faded as social platforms became the main sites for online interaction, and the follow list, or the Twitter list, took over the blogroll’s old job of reinforcing networked hierarchies of writers and audiences. Because a blogroll is a static list of people, it hardens into a status game and is kind of stale the moment someone stops babysitting it; meanwhile, a linklog points at individual pieces of writing one at a time, so it stays current and rewards the work rather than the social and professional standing of the writer.

In this sense, a linklog is an easy way to be an opinionated curator and a decent neighbor at once, by hosting and sharing with thoughtfulness and deliberation. Out here, my data is also likely being scraped, but I have far more control over what data is findable, shared, and shareable, and over what is investigable and degradable over time.

Tue, 18 Aug 2026 11:54:13 -0500

Chester argues that universities should govern AI by classifying data by sensitivity rather than approving specific tools. Public data goes anywhere –> regulated data requires an institutional contract –> sensitive data requires a local system. He also makes a renewed case for MS Copilot.

Tue, 18 Aug 2026 10:59:15 -0500

Community Notes was meant to democratize moderation power (and spare platforms the burden of thinking through moderation). Instead, a new paper shows that 20% of users cast 80% of ratings, and removing just ten active note writers from the pool changes what happens to nearly 5,000 community notes.

Computah: Make it a link

Thu, 13 Aug 2026 15:40:59 -0500

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.

Thu, 13 Aug 2026 12:45:13 -0500

“When you gaze long enough into Instagram, Instagram gazes back into you.”

Wed, 12 Aug 2026 17:22:28 -0500

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)

Wed, 12 Aug 2026 16:37:43 -0500

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?

Thu, 06 Aug 2026 09:42:03 -0500

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.

Tue, 04 Aug 2026 17:34:45 -0500

Winer on the purpose of web standards: “I find that most standards that come out of the standards bodies aren’t developed by implementors or with them in mind. They avoid trying to solve any specific problem, rather focusing on the elegance and flexibility of the format. This makes interop much less likely. I saw the differences several times as the web standards were growing up.”

Tue, 04 Aug 2026 12:37:59 -0500

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.

Fri, 24 Jul 2026 13:26:32 -0500

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.”

Wed, 22 Jul 2026 13:52:16 -0500

UW–Madison communication professor Catalina Toma argues that technology-mediated communication more often supports human connection and well-being than harms it, provided people use it intentionally.

Tue, 21 Jul 2026 11:51:53 -0500

A colleague hosted a nice discussion of the work of David Dylan Thomas, who advocates for using human-centered design concepts to bring humanity back to tech. New and novel approaches abound, especially on whether and how to let engagement metrics drive decisions on design teams.

Mon, 20 Jul 2026 15:50:17 -0500

This is a pretty good Tiktok breaking down the historical, cultural and religious meanings invoked in the “computah” memes. An important rule of the internet: the best memes are intertextual.

Mon, 20 Jul 2026 13:23:16 -0500

Scheduled send as alibi? Nice try, Costanza.

Mon, 20 Jul 2026 13:01:24 -0500

Parents wanting stakes lower than a smartphone: consider a kid-friendly Wi-Fi landline, which looks and works like an old corded phone but runs over your internet connection, giving kids the independence to get connected safely. Alternatively, get a VOIP phone through your ISP for ~$10/mo.

Fri, 10 Jul 2026 15:00:55 -0500

rss.chat is a new, free social network service that uses RSS to create a federated social feed that looks and feels a lot like OG Twitter. See also: the launch of HyperTexting, another RSS-based app that centralizes the open web in a way that feels a little like Google Reader (complimentary).

Fri, 10 Jul 2026 14:53:43 -0500

Clothing technology: tracing a history of pockets from ancient coin purses to tie-on pouches to today.

Wed, 01 Jul 2026 12:05:39 -0500

With global temps at peak in several areas of the world, the BBC covers how critical tech infrastructure is impacted by high heat.

Thu, 25 Jun 2026 16:27:25 -0500

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.

Thu, 28 May 2026 13:36:23 -0500

A cathartic read.

Wed, 27 May 2026 10:51:12 -0500

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.

Mon, 25 May 2026 10:52:05 -0500

The Pope provides a vision for living with artificial intelligence (gift link).

Sat, 16 May 2026 09:50:40 -0500

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.

Fri, 15 May 2026 19:55:58 -0500

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.

Fri, 15 May 2026 16:54:08 -0500

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

Thu, 14 May 2026 19:59:40 -0500

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.

Thu, 14 May 2026 11:05:57 -0500

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.

Wed, 13 May 2026 19:09:08 -0500

For those who love to post, a guide to the Internet of the future.

Wed, 13 May 2026 16:13:10 -0500

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.

Tue, 12 May 2026 12:11:23 -0500

Some contemporary thoughts from Ana Rodrigues on the perennial question of being a “woman in tech.”

Mon, 11 May 2026 11:16:51 -0500

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

Fri, 08 May 2026 10:19:05 -0500

Watching a local phone ban policy snake through the community this week, one that state law now requires every district to adopt by July 1. 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, and early data from Florida’s phone ban shows the same pattern. 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. He does ask legislators to act, but his asks center on age limits. 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. A UK study found no difference in student wellbeing between schools with restrictive and permissive phone policies, and a follow-up found that managing phones takes schools more than 100 staff hours a week either way.

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.

Update, September 26, 2026: The Madison School Board approved the policy on June 23, with tighter limits on high schoolers than a UW–Madison La Follette School research team had recommended. Parent Check On Tech, the group linked above, pushed for the stricter version. Elsewhere, a San Diego teacher reports that students hand over burner phones and keep their real ones.

Tue, 05 May 2026 12:12:09 -0500

It’s like the phrase “turtles all the way down,” but turtles are marketing.

Wed, 29 Apr 2026 12:38:06 -0500

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.

Wed, 29 Apr 2026 11:05:30 -0500

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.”

Thu, 23 Apr 2026 17:22:52 -0500

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.

Thu, 23 Apr 2026 12:47:12 -0500

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.”

Thu, 23 Apr 2026 08:35:14 -0500

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.

Wed, 22 Apr 2026 17:27:14 -0500

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.

Wed, 22 Apr 2026 17:10:00 -0500

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.

Wed, 22 Apr 2026 17:05:00 -0500

I missed this 2025 article by Noah Hawley on Vonnegut, war and the atomic bomb, and it is worth the time.

Tue, 21 Apr 2026 11:23:58 -0500

What does it mean for the culture when everything (everything!) is content, even war and mass shootings?

Tue, 21 Apr 2026 10:40:52 -0500

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.

Mon, 20 Apr 2026 14:26:39 -0500

Out: Twitter on a vape. In: AI-powered crypto vape. Is this real? Who can tell anymore. See also: the first Twitter on a vape.

Thu, 16 Apr 2026 08:17:46 -0500

A nostalgic read on how music nerdery bloomed online.

Wed, 15 Apr 2026 10:31:56 -0500

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.

Wed, 15 Apr 2026 10:16:08 -0500

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.

Mon, 13 Apr 2026 15:49:00 -0500

Tom’s Hardware on Mythos and marketing hype. Additional commentary from Michael Corn, asking whether Mythos coverage reinforces or establishes perceptions about cybersecurity.

Mon, 13 Apr 2026 15:44:53 -0500

Garbage Day on what makes something cool to Gen Z, and how this is impacted by the degradation of “pillars of coolness” in previous generations like culture rags and MTV. GD predicts that “cool” will be measured by lack of polish and “how many human beings left their house to experience it.”

Sat, 11 Apr 2026 13:21:29 -0500

What the internet was made for: A Chicago music fan secretly recorded over 10,000 live concerts from Nirvana to Sonic Youth to Spoon, and has made them all available online.

Wed, 08 Apr 2026 18:51:52 -0500

Deepfake nude culture and its impact on American teens.

Wed, 08 Apr 2026 17:37:24 -0500

I once worked in a role where I keyed million dollar manufacturing orders into SAP, information that directly fed into factory specs for a manufacturing facility based in another country. Our regional office fed into a massive, global electrical engineering firm that ran on small margins (electricity delivery is a well-trod market), so our ability to deliver accurate orders on time was a differentiator in a field that is otherwise easily interrupted by chip shortages and logistics chains.

It was a big job. I learned a ton about electrical engineering, manufacturing and global logistics from a particular vantage point in North America. Our headquarters were based in Sweden, with locations around the world to support the electrical grid(s), covering both hardware and software solutions. My colleagues and I worked in positions that sat somewhere between B2B customer service, inside sales and data entry, and were expected to maintain a 99.8% accuracy rate because a single fat finger error would cascade across myriad systems, impacting real-world operations to the tune of hundreds of thousands of dollars per error.

Once (and only once), I fat-fingered a serial number during data entry which ruined an entire shipment of widgets. In response, the factory in Mexico sent the incorrect order of widgets, about five pallets, to my location in the United States so I could correct the order by hand. One by one, I had to physically remove each widget from a pallet, then from its individual shipping container, make a correction on the widget itself, and repackage each one, signing my name on each unit to ensure it was corrected by an accountable employee. I can’t recall why the issue couldn’t have been corrected on the factory floor, but it wasn’t on the menu. It was going to stay my problem.

This was the one and only factory error I made in about five years of tenure, precisely because it was so painful to correct it. The process was a little embarrassing but nobody made it especially so. Instead my coworkers up and down the org chart relayed a simple expectation: the desk workers need to pay attention to the details because the alternative is too costly. A few old-timers made sure to razz me about it in good humor, but ultimately the error was mine and the fix was mine, and the experience stuck because the whole chain of responsibility understood the stakes and reinforced the consequences. They also trusted me to stick around and continue to do my best.

During my annual review that year, I was dinged for only having a 98% accuracy rate, and I knew why that was a fair assessment.

I thought about this when I read today’s NYT piece on whether 90% accuracy is good enough for LLMs.

Tue, 07 Apr 2026 18:08:49 -0500

Amid renewed calls for the death of feminism, or of millennial feminism or whatever (TERF alert), I found this old victory lap from the era where it looked like new media had permanently paved the way for a newer, fresher publishing industry. It also tips the hat to Jezebel’s place in the fray, “the first online women’s publication to successfully combine feminist writing with a for-profit motive.”

Tue, 07 Apr 2026 17:59:16 -0500

Poell argues AI is entangled with platform capitalism through shared infrastructure, reinforcing concentration of the market. The hype obscures local realities of adoption, putting public alternatives in the position of proving their existence alongside advocating for their place in the market.

Tue, 07 Apr 2026 08:41:53 -0500

Angst about data center development continues to grow in the Rust Belt.

Mon, 06 Apr 2026 16:12:19 -0500

This post and the accompanying graphs have been a trending topic on social all weekend, particularly on Twitter/X, which is negatively implicated in the findings. In short, social media looks weirder than ever.

Mon, 06 Apr 2026 10:05:53 -0500

Silicon sampling is the practice of using LLMs to run surveys without talking to any people at all.

Sat, 04 Apr 2026 09:58:05 -0500

Just ran across Paul Robert Lloyd’s talk on using tools and approaches from the indie web to build the Internet we want. Talking points and slides at the link.

Fri, 03 Apr 2026 12:27:57 -0500

The cost of moving to token-based access to tech, rather than seat-based licenses based on employee headcount.

Wed, 01 Apr 2026 16:55:11 -0500

An observation on feminist writing and Jezebel: Throughout history, a lot of time and energy has been spent mediating how and whether certain kinds of people talk to one another. The feminist blogosphere, for all its faults, was the first time lateral, public, unmediated conversation happened among women at scale. Many kinds of women were there that had no space at other tables. And it was very messy, and very revealing, because it was the first time that happened at scale for all to see.

Some thoughts:

When I started in 2001, the most viewed website about feminism on the internet was a solo blog by a man in Portland.
I just pulled Mindy Seu’s “Cyberfeminism Index” off my shelf, a veritable tome, and the feminist sites don’t even make the table of contents. Which is not an indictment of the book, but an example of how ephemeral all this is online.
You can see this on Twitter in the live debate about what Jezebel was and wasn’t, a conversation happening mostly through collective remembering. Jezebel joined the pack of blogs at some point, and they were big dogs, but they weren’t responsible for the creation or steering of the digital movement. They were a glossy, spendy repackaging of the organic thing, backed by real investors. It’s wild to see the entirety of the movement attributed to Jezebel by young Twitter, given that most of the indies kept Jezebel at arms’ length until much later. They were pretty widely considered a corporate interloper in a grassroots arena, though in hindsight that wasn’t right either.
The first time the indie bloggers gave Jezebel their day was when they published the untouched photographs of Faith Hill on the cover of Redbook, a women’s magazine. The Redbook post tore the veil off the beauty industry in real time. Until then, the idea that “celebrities are photoshopped” and “photos are retouched” was almost an urban myth, which is easy to forget given the ubiquity of filters and AI now. Then, you heard about it but couldn’t confirm it for yourself unless you had firsthand experience. Retouching was a discrete industry practice, digital tools were still expensive and clunky, and all of it was surrounded by a lot of tradecraft and secrecy. The mystery of celebrity image management exploded with an animated gif on a public-facing post, and it was rad.

Fri, 27 Mar 2026 17:05:06 -0500

This post is mostly an excuse to talk about my latest playlist: Digital Animal. This one consists of about 200 songs across genres, all reflecting on our human relationship to science and technology, futurism, digital culture and the internet.

When I’m chewing over a big idea, I like to compile resources in and around that idea to help support my thinking. Embracing my angst about artificial intelligence, I started compiling songs that reach back to the early 20th century, tapping into prior generations’ anxieties about telephones, television and early networking technology, adding more contemporary concerns as I went. The playlist runs from David Bowie and Blue Öyster Cult and Kraftwerk to Zapp and Radiohead, then forward into modern takes on social media, cell phones, and the internet from Missy Elliott, Gillian Welch and Charli XCX.

I like a playlist because it’s convenient, and because songs are one place where meaning and feeling are created simultaneously, and because it’s easy to spot salient patterns across disparate sources. Scholars in interdisciplinary studies have long argued that you cannot fully understand a thing without understanding what it feels like to live with it, and that cultural analysis may get you there faster than surveys will anyway. Meanwhile most writing about technology separates feelings from form and function. Art and music compress all three, and have the potential to surface ideas that professional and institutional language can’t. Art and culture frequently peg an issue down before emerging best practices are formalized in business and academia.

For anyone working in technology communications, that lag between culture and practice has practical consequences. The language we use to describe technical systems shapes what people can think and do about those systems. An institutional frame — efficiency, access, innovation, value — consistently misses important dynamics that people living inside those systems are experiencing as users and as people. Art keeps the human subject inside the frame, functioning as both anecdote and data.

Plus, it’s fun and we should collectively think about art as much as possible. So, treat every song like a portal.

What does it mean to be both digital and animal? Some observations:

Grief and sadness sit next to fun and ecstasy. Many of the older songs see computers as friend and companion, treating tech with a kind of tender curiosity, a toy that makes you happy as much as a medium for expressing longing and desire. These nevertheless tend to be layered with a sense of loneliness, a minor key, a dynamic that bears out through user research.
Between the era of telephones and the digital web, there are a charming number of songs about beepers, beeping and pagers. I’m hopelessly devoted to Missy’s “Beep Me 911” right now.
Recent songs are concerned about understanding identity and the self under the pressure of social media. Songs talking about social media persistently trawl the gap between your real identity and your public identity and personal brand, and how this dynamic can hollow out your relationships and quality of life. Songwriters like Jazmine Sullivan consistently refer to tech as a place of escapism, like retreating into the creation of a new Tinder profile while avoiding reflection on your last relationship. Comparison is the product, and sometimes it stinks.
Lots of songs from peak elder Millennial/Gen X songwriters are about watching the old analog world being swallowed by the new. The older the songs, the more aware they are of the machine across the room, and the more they lean into allegory. The contemporary songs don’t worry about the boundary between human and machine much at all, likely reflecting the high level of technical integration (and acceptance) we live with right now.

Is fretting about our relationship to tech and industry part of the human condition? Or is there something specific to tech that accelerates these anxieties and impulses?

A few favs:

I’m enjoying almost everything from the band Automatic. One of the band members is the daughter of the drummer from Bauhaus, and their work is heavily influenced by 80s era synth pop and new wave. I have several of their songs represented on the list, and particularly like “Black Box” off their 2025 album.
Erykah Badu’s “Cel U Lar Device,” which positions the phone as an instrument of interpersonal surveillance, has been on rotation in my house for (cough) years. It is also a reinterpretation of Drake’s hit “Hotline Bling,” itself forever memorialized as a popular meme format.
The Talking Heads’ 1988 “(Nothing but) Flowers” imagines a sunny life after the fall of industrial civilization. For the doomer, afropessimist take on this theme, check out Nina Simone’s cover of “22nd Century.”
Sophie’s “Faceshopping” is about the negative pressures of cultivating a public persona and brand, and tips a hat to our relatively new ability to use science and technology to curate a physical appearance that matches your internal (and digital) one.
Nobody talks about Ladytron anymore.

Wed, 18 Mar 2026 16:47:32 -0500

Rapper Afroman is going ultra viral this week as his “Lemon Pound Cake” trial plays out in the news. He captured the raid on security cameras in his home and used the footage in a series of songs, videos and merch. He ultimately did not face charges after the search, and argues (with evidence) that the police broke his door and stole $400, which provides the platform and substance for everything that followed. He argues the police shouldn’t have been there at all, and didn’t follow protocol when they were, and that as a citizen and artist he’s expressing his feelings about it in his preferred medium. Is this a winning legal strategy? Time will tell.

In the meantime he’s winning at public opinion. The trial is shaping up in the public view as a defamation vs. free speech trial, with the artist’s prolific work about this no-knock raid performed at his house, itself arguably unethical, held up as harassment by the officers who did the job. True crime, legal experts and court watcher accounts are going gangbusters providing cultural and legal analysis alongside video of court testimony. It helps that the court footage is a rich text — both hilarious and revealing.

Meanwhile: another first amendment case in and around rap lyrics is playing out now. A brief history of rap and the First Amendment.

Sun, 15 Mar 2026 13:08:05 -0500

Anne Helen Peterson on the erosion of good, stable, sustainable jobs.

Sun, 15 Mar 2026 10:48:19 -0500

My digital presence has been deliberately fractured for years, so I’m watching how this site stitches together my breadcrumbs through SEO, with the serious stuff and throwaway asides alongside the occasional hilarity. Currently one of my top Google results.

Thu, 12 Mar 2026 12:11:31 -0500

A gift link from The Atlantic, a reporter is given $10k to spend on emerging betting markets and reports on what he found. Spoiler: it’s dark!

Wed, 11 Mar 2026 08:53:04 -0500

From 2021, notes on supply chains and chip shortages in a global economy.

Tue, 10 Mar 2026 14:43:27 -0500

Excited about Inkwell, a contemporary treatment of the classic RSS reader.

Tue, 10 Mar 2026 10:17:42 -0500

I need someone to talk me into/out of the new Macbook Neo. Is this just a Chromebook for design people?

AI in practice: Chatbot tool comparison

Sun, 08 Mar 2026 13:19:11 -0500

Come look over my shoulder while I explore how and whether LLMs are good writing tools: Here’s a wee version of the LLM comparison exercise I did with my team. We’ll make it a two-fer so you can see how the “good writing” skill works in practice, though we’ll see how that actually goes.

One of the more useful things you can do with an LLM is hold up a few ideas side by side and apply lenses to them. I know this history pretty well, so I asked a series of LLMs, why is Wisconsin’s cultural identity and cohesion stronger than Indiana’s, from a historical and business perspective?

Here are the answers in one doc, for comparison.

Each LLM will give us more or less the same story, different flavor. Within the industry, the differences across the models reflect “model personality.” Asking “why” instead of “whether” will probably drive the answer to favor Wisconsin. Using multiple lenses (two states, historical + business, identity + cohesion) forces the LLM to cross-reference across more of its training data, which tends to produce a more comprehensive answer.

For all the chatter about consciousness and whatever, remember that an LLM is an infinite series of if/then/elses applied to human language and semantics, so being able to talk about language and communication, getting meta with the tool and how you think through language, helps a lot when using one. This is maybe the one thing I like about experimenting so hard with the tools. I’m thinking about the technical side of writing and enjoying it quite a lot.

Functionally: all of them acknowledge hard historical truths within the subject matter and don’t shy away from critical perspectives, which is good. Both Gemini and Copilot include in-line links, which lets you judge the output’s authority in the moment as a reader. I liked Copilot’s more than I expected here. Claude’s answers are more lyrical and do provide more context, and yet do not encourage checking against outside sources by providing links within the output. And you can see that even with the good writing skill calling out hard bans on certain structure, Claude plows right through them.

Model personality: Claude favors sociological answers to Copilot’s economic answers. Claude is also highly intellectual and narrative by comparison, and that narrative style can mask nuance by sinking relative context within the storytelling. Gemini simplifies, boosts and cheerleads where the others don’t, and really goes hard on Wisconsin’s reputation as a drinking and Packers state when there are stronger structural arguments in play. Copilot is tricky because it looks authoritative like a briefing, which also makes it easily “extractible” for the user, but every citation requires authentication unless this is one of those “good enough” tasks.

As a writer, something I find annoying across the whole spread is the semantic reveal. LLMs are semantic machines, and it is persistently revealed in ways that are weird to the human ear. All of them go out of their way to describe things as “structural,” “connective” as in “connective tissue,” “load-bearing” and “legible.”

Finally, I included a second tab where I asked Claude for analysis across the four outputs, where it suggests that my framing of the question is altogether kind of problematic. It shows how a strong prompt is sometimes also a bad approach.

There are a lot of possible takeaways here, but I’d rather set aside the question of which tool is “good” or “bad” or “better” and think more about the patterns across the tools and their implications.

Sat, 07 Mar 2026 22:51:10 -0500

Winer on Doctorow on RSS.

Sat, 07 Mar 2026 20:48:00 -0500

One of the tricky things about consumer AI tools like Claude and Gemini is that the experience varies widely depending on the person using it, and it’s not always clear why. I have spent a lot of time learning the tools so I can advise on them in my work, and this variance of experience has become a frustrating part of the deal.

I manage a team of writers and creatives at work, and we are expected to be familiar with the tools, despite complex and sometimes hostile feelings about the political and environmental implications of this sector. That’s quite a pickle, organizationally, managerially. Borrowing from Haraway, I thought, okay, what if we take these tools seriously as a team of writers and creatives and put our professional standards up against them?

Among other exercises, I did a couple of comparisons on my team that help create discussion around the “plausibility” question. People dismiss LLM outputs as being merely plausible answers, rather than accurate or factual ones. And that’s correct; they are, and that’s the design. In many cases, plausibility is fine. Take Wikipedia, for example, which we understand to be a pretty good source, a plausible source, unless you’re writing a formal paper requiring original sources.

I digress. Ultimately, we needed to understand together that LLMs are not a WYSIWYG tool and talk through the implications.

I asked everyone to run the same paper through their LLM of choice, prompting it for a plain language summary. We then copied and pasted it into a shared doc, and compared and contrasted for discussion. Upon discussion, we had several takeaways, including that they were all similar in spirit but sometimes varying wildly in style and approach.

Knowing that algorithms are responsive and not static, we did it again later in the day and copied and pasted our outputs into the shared doc. We compared and contrasted the difference between AM and PM. Again, it was similar in spirit but varied in style and approach. Some changed dramatically. One team member whose morning summary had been jokey and conversational received a much more staid and serious version in the afternoon.

At the time, I asked Claude to explain the variance: “Even with the same prompt and source material, LLMs don’t produce identical outputs each time. This is by design — there’s a degree of randomness (called “temperature”) in how the model selects words, which means each run produces a slightly different path through the text.”

Anyway, this got our gears turning on how (and whether) to approach LLMs as a team and as individuals and led to good group discussion. (It’s important to create space for criticism and critical approaches here.) It also gave us more confidence as a team responding to this new layer of complexity in our work, and helping our professional contacts and peers think about how to approach the tools and when and whether to use them. There will be tasks where AI-based tools are “good enough,” and tasks where they are not.

The swirl of mystery and speculation around this sector has people up in arms, and it’s useful to have approaches that give people firsthand experience and to see how the experience works for others. The god trick of the singular interface turns out to be a bear for navigating it in the workplace, where our work is foundational, prosocial and specific.

Fri, 06 Mar 2026 13:27:57 -0500

A smart take on nonconsensual deepfakes, considering them not just as a social issue but as a cybersecurity issue, as they’re often connected to broader financial and social harassment campaigns.

Fri, 06 Mar 2026 00:19:00 -0500

WaPo on the many issues of LLM house writing styles. I have much to add. Here are some notes on applying a writing skill to override house style on Claude.

Wed, 04 Mar 2026 10:25:49 -0500

You might call this a taste test: Obsessed with the story about the McDonald’s CEO and how his LinkedIn-style videos selling the McD’s franchise have escaped containment, leading to one of the funnier CEO/product marketing dynamics in recent history. Burger King’s CEO swooped in, holding widely-marketed listening sessions with customers and to demonstrate his love for the Whopper in contrast with the deeply weird McD’s videos. Must read: Internet long-hauler Katie Notopoulos on how direct-to-public marketing works when the public is more familiar with the product than the org’s leaders.

My teenager thinks fast food is cool and subversive (cue the sound of one hundred moms groaning) and she and her friends regularly talk shop. They are Taco Bell fans and think burger stops are kind of gauche. Not gauche: Baja Blast.

In the meantime, the fast food sector is becoming a playground for AI approaches, causing a lot of nervous discussion on social media and in tech spaces.

Wed, 04 Mar 2026 08:40:43 -0500

Ryan Broderick is currently my fav reporter on the Internet culture beat, and on this podcast he’s talking about Epstein and why he was interested in putting his resources to developing the early internet (spoiler: for crimes).

Tue, 03 Mar 2026 13:22:34 -0500

Ruling: AI art is not copyrightable.

Tue, 03 Mar 2026 10:59:00 -0500

Apparently one thing LLMs excel at is deanonymization at scale. The original promise of pseudonymity online was social and normative, over and above any question of technical depth: decent people don’t try to unmask you, because why. What strikes me today is how what used to be unacceptably antisocial behavior online is now both automated and unremarkable.

Over the last couple of weeks, I asked a couple of chatbots what could be known about me from this pseudonymous site, where I am more intentional about what I choose to reveal and conceal. It pulled the obvious but also drew conclusions based on a few geographic points I’d made in context that were both revealing and correct. I also noticed that it only drew from the top two pages of information - anything beyond page two of posts wasn’t part of the compute. Archives are for humans?

People assume that there is some computer magic on the backend where the LLMs connect all your account logins behind the scenes, but no, in fact it does all this through inference, by linking your digital trail, your friends, your breadcrumbs of likes and hearts and follows, and obvs your posts, into a picture of who you are, practically and demographically.

Mon, 02 Mar 2026 17:15:17 -0500

Developing a new pet theory that you could theoretically crank AI outputs toward your vision by having an organized link blog revolution.

Mon, 02 Mar 2026 16:32:17 -0500

The Guardian has a long-running series where readers answer one another’s questions, which gives a pretty good point-in-time survey of how people of a certain demographic are feeling on a given subject. This week’s question is on AI futures: “what would happen to the world if computer said yes?”

Mon, 02 Mar 2026 14:48:10 -0500

Reading about a new “slow” RSS app called Current.

Mon, 02 Mar 2026 10:56:06 -0500

Some analysis on Anthropic and the Pentagon. Per @manton, it feels a little bit like the company isn’t fully on board with the product they produce. I find it interesting that the feds appear to be toying with the idea of nationalizing AI companies alongside other nationalization efforts.

Sat, 28 Feb 2026 10:58:00 -0500

Like Rickrolling on steroids: I didn’t even know P2P music file downloads were still a thing, but of course, and the scene had a big week recently when somebody trolled SoulSeek by generating a bunch of popular songs sung in Homer Simpson’s voice, then quietly polluted the platform by offering the AI generated Homer files up to other users. Someone then set up a digital radio station of all the Homer Simpson songs called D’oh Radio. Here’s more reporting from Gizmodo.

There is a long tradition of Simpsonifying things that go online, so this is the latest iteration. We observed Homer covers going viral on social in 2024 and 2025.

Sat, 28 Feb 2026 10:43:00 -0500

A new report shows that “just 100 users were responsible for almost 70 per cent of online conspiracy posts from influential accounts they examined in Canada.” Relatedly, a White House staffer is reportedly behind a massive Trump account on Twitter. This practice is a common information strategy by bad actors called astroturfing.

Sat, 28 Feb 2026 09:39:28 -0500

A guy put his life savings up against DOGE and won big on the new, anarchic betting markets online. This line hooked me: “Crucially, he’s been around long enough to see promises collide into reality and to know basic federal-budget math.”

Fri, 27 Feb 2026 16:20:00 -0500

Second wavers in tech and engineering talked a lot about the “god trick” of presenting knowledge and information, particularly around math and science, in a way that suggests its objectivity is eternal, immortal, unknowable. Work by Safiya Umoja Noble and others extended this lens to Internet search and architecture, finding that the search algorithm was a series of business decisions wearing neutrality to create a customer service experience. Websites do this (so does this blog). LLMs take that same trick and compress it further.

It’s an old idea, and one I’ve been drawing from while I tinker with Claude. The “god trick” is baked right into the AI interface: one input, one output, an authoritative-seeming answer, offered without named perspectives behind it, trained on text produced overwhelmingly by a narrow demographic who has historically had access to both literacy and publishing, by programmers and new media drawing from the same well. Smushed together, it gives the impression that consensus and authority exists where there are many loose ends and competing ideas in play. Sometimes that’s fine.

I’ve begun to recognize how LLMs can work like autocorrect for ideas, drawing from ranked search sources first before fanning out to more obscure sources, trying to determine and assert what’s important to me, a user known by demographics and data. It feels like a big linguistics machine, which is pretty cool in some regards, but also aggressive in others. The math doesn’t always work to connect me to what I want to find because I am situated in my individual context in ways LLMs are not able to understand, with my memory, in my body, with my unique experiences, which shape and translate meaning for me as I interact with the world (and the web).

Fri, 27 Feb 2026 12:35:50 -0500

An open letter from employees of Google and OpenAI in support of Anthropic, against the DoD: notdivided.org

Thu, 26 Feb 2026 16:43:00 -0500

McKenzie Wark for Verso Books on Donna Haraway, in 2015: “Creating any kind of knowledge and power in and against something as pervasive and effective as the world built by postwar techno-science is a difficult task. It may seem easier simply to vacate the field, to try to turn back the clock, or appeal to something outside of it. But this would be to remain stuck in the stage of romantic refusal. Just as Marx fused the romantic fiction that another world was possible with a resolve to understand from the inside the powers of capital itself, so too Haraway begins what can only be a collaborative project for a new international. One not just of laboring men, but of all the stuttering cyborgs stuck in reified relations not of their making.”

Thu, 26 Feb 2026 11:14:05 -0500

New research shows that social media advertising suppresses voting in targeted communities, and is the first to quantify the effect of this kind of microtargeting on voter turnout.

Thu, 26 Feb 2026 10:40:51 -0500

Sharing Digital Animal, a new, curated playlist of songs about all the angst and joys of living with modern technology.

Wed, 25 Feb 2026 12:46:47 -0500

I’ve been spending more time in tech spaces online and getting good information from folks like @manton, creator of Micro.blog. Like this reflection on how to think about AI now that vibe coding works. Something I’m thinking about: there’s an emerging tension between those who see value in being able to immediately prototype an idea and the people downstream who have to manage the outputs/code over time. The ability to proof every idea sounds like a superpower until you’re the one driving and maintaining the results.

Wed, 25 Feb 2026 10:17:14 -0500

Making the rounds on Twitter today, an AI programmer pulled together a dashboard comparing how LLMs respond when given a series of nonsense prompts. There is a notable difference in quality even between Claude’s Opus and Sonnet, in my experience. The lesser GPTs will take a wobbly claim as truth and run with it.

Tue, 24 Feb 2026 19:20:57 -0500

Some additional discussion of LLM models, including open weight and “staggered openness,” where orgs “release previous versions of proprietary models once a successor is launched, providing limited insight into the architecture while restricting access to the most current innovations.”

Tue, 24 Feb 2026 19:13:28 -0500

“Open source,” “open weight,” and “proprietary” describe different relationships between LLM model producers and users, governing what you see, modify and control. Comparing them isn’t necessarily about “best,” but whether you’re optimizing for transparency, compliance or performance. Massive investment in proprietary models means the best-resourced research teams, the largest training runs, and the most sophisticated safety work tend to happen behind closed doors.

Tue, 24 Feb 2026 18:56:39 -0500

A new report from Pew on how teens view and use AI says that more than half of teens turn to chatbots for help with school, and some are turning to AI for emotional support and companionship.

Mon, 23 Feb 2026 15:33:06 -0500

“A brief history on writing, a forgotten technology: how the challenges we face in today’s digital age can be traced back to one of the most significant yet underrated innovations of all time.”

Mon, 23 Feb 2026 13:05:00 -0500

“Digital silence” is a new ethic emerging on the visual web, where travelers are no longer posting about their travels. Reading along, thinking of how I rarely post about family out of respect for their privacy, and recently took several road trips without a single post.

Mon, 23 Feb 2026 09:49:22 -0500

“History was unmade last year, as engineers began the massive project of ripping the first-ever transoceanic fiber-optic cable from the ocean floor.”

Wed, 18 Feb 2026 10:42:02 -0500

“Because RSS is an open protocol, and because there are so many different possible ways to follow and read the news, RSS readers ought to be a UI playground in the way Twitter clients once were, where innovation and experimentation are normal and celebrated.”

Fri, 06 Feb 2026 09:54:01 -0500

The article argues that Silicon Valley’s shift from long-term employment to talent migration has created a model where workers maximize their individual compensation through frequent job changes, fundamentally altering tech industry culture and economics for the worse.

Closer to the machine

Mon, 02 Feb 2026 15:36:00 -0500

There is something about the AI moment that reminds me a lot of when the internet was new. A lot of what was imagined and promised about the internet was never realized. But much was.

I’ve been reading Ellen Ullman’s memoirs - “Life in Code” and “Close to the Machine” - and her observations about proximity to technology feel relevant here. Being close to the machine means understanding its actual capabilities and limitations apart from the prevailing sales narratives. It also means a kind of loneliness, because you are working in a space that others don’t yet see clearly or fully understand.

I suspect people thinking seriously about AI right now will experience something similar: a stretch of hostility and discomfort while the rest of the world catches up and the consumer market level-sets on the promises being made. In the interim, the hype will not match the reality, and the reality will sometimes exceed the hype in ways no one predicted. And for a while, how it works and why it matters won’t be legible to everyone at once.

Crunching for clarity

Fri, 30 Jan 2026 12:12:00 -0500

In 1999, academic and theorist Judith Butler famously won an award for the worst academic sentence, raising good questions about how we read difficult texts, who gets to access academic ideas, and the role of academic and plain language in and around the academy:

The move from a structuralist account in which capital is understood to structure social relations in relatively homologous ways to a view of hegemony in which power relations are subject to repetition, convergence, and rearticulation brought the question of temporality into the thinking of structure, and marked a shift from a form of Althusserian theory that takes structural totalities as theoretical objects to one in which the insights into the contingent possibility of structure inaugurate a renewed conception of hegemony as bound up with the contingent sites and strategies of the rearticulation of power.

This was my era in college, and I remember feeling challenged and overwhelmed as an undergrad trying to read theory for the first time. So today, I asked Claude.ai to put it in plain language, just to see what would happen. Here’s the after:

Scholars used to think that capitalism shaped society in consistent, predictable patterns. But newer thinking focuses on how power works—how it repeats, overlaps, and gets reshaped over time. This brought time into the picture and moved away from older theories that treated social structures as fixed. Instead, recognizing that structures can change opened up a new way of understanding power: it's tied to specific moments and strategies, and it's always being renegotiated.

The real problem is that it's not our quagmire

Fri, 23 Jan 2026 12:37:00 -0500

Tiktok is not much better or worse than other major social platforms, I say. The primary arguments against TikTok, including data collection, algorithmic manipulation, potential foreign government access, addiction and influence on public opinion, apply with equal or greater force to American platforms. Meta has faced billions in fines for allowing privacy violations, enabled documented election interference, and its algorithms have been linked to mental health harms and the amplification of extremist content globally, including perpetuating a genocide in Myanmar. Google and other domestic platforms vacuum up vastly more user data with fewer restrictions.

The distinguishing factor isn’t the behavior but the ownership: TikTok’s parent company ByteDance is subject to Chinese law and intelligence relationships, while Meta and Google are subject to U.S. law and intelligence relationships. That’s a legitimate policy distinction, but rarely articulated honestly. Instead, the debate has been framed around purportedly unacceptable harms that American tech companies perpetrate routinely, creating a kind of security theater that lets domestic platforms escape equivalent scrutiny while positioning a foreign competitor for a forced sale or ban.

Affinity as an organizing principle

Fri, 16 Jan 2026 16:55:00 -0500

Reading this blog post by a political scientist explaining the problem with our fractured information landscape, and how calls for more information and media literacy are not likely solutions:

“In short, decades of research have demonstrated that our political beliefs and behavior are thoroughly motivated and mediated by our social identities: i.e., the many cross-cutting social groupings we feel affinity with. And as long as we do not account for this profound and pervasive dependence, our attempts to address the epistemic failures threatening contemporary democracies will inevitably fall short. More than any particular institutional, technological, or educational reform, promoting a healthier democracy requires reshaping the social identity landscape that ultimately anchors other democratic pathologies.”

As always, this drives me back to Haraway’s cyborg, a useful metaphor for thinking about our political, environmental and social tangle and how it butts up against emerging tech and science. (In Haraway’s context, it was the rise of STEM as a driving force in academia at the dawn of the computer age.) Bagg’s argument lands in familiar territory for anyone who’s wrestled with the cyborg metaphor. Both reject the assumption that better information alone will save us from ourselves, whether from context collapse or the dualisms (binaries, heh) that structure how we think about technology, nature, humanity and politics.

Bagg arrives at something parallel from political science: We trust information that affirms the groups we belong to.

Business and marketing, for what it’s worth, tell us the same thing from a slightly different angle: you’re most likely to convert on a recommendation from a trusted friend.
The next best thing in our current digital media landscape: a trusted influencer you identify with, which is why TikTok increasingly feels like QVC.

The problem isn’t that people lack access to truth, it’s that they’ve lost affinity with the experts, institutions and collaborative practices that produce real expertise. We’re arguably in era so thick with marketing that we are locked into performing respectability and purity aesthetics as our primary approach to the world and one another, instead of prioritizing social health and good function.

Both perspectives point toward the same conclusion: you have to recognize shared affinities through the slow work of creating conditions where people want to trust each other across differences.

Sat, 10 Jan 2026 15:51:33 -0500

I too have been challenged by defining “federation” to non-technical audiences, so it was fun and instructive to see others give it a go.

The trust gap

Fri, 09 Jan 2026 14:30:00 -0500

I suspect these three trends are connected: Women reportedly use AI at significantly lower rates than men—25 percent lower on average—in part because they’re more concerned about ethics, including privacy, consent and intellectual property. At the same time, countries with more positive social media experiences tend to be more open to AI, while Americans’ distrust is shaped by years of watching tech platforms erode trust. Meanwhile, one of the largest social platforms has turned its AI chatbot into a harassment tool—generating roughly one nonconsensual sexualized deepfake image per minute, disproportionately targeting women and girls.

When platforms enable abuse at scale, it makes sense that people most likely to be harmed would be most attuned to ethical concerns, and would thus be the most cautious about AI adoption.

Fri, 09 Jan 2026 13:16:10 -0500

“It’s really a software maturity story,” Sag says. “But that’s not very sexy.”

Wed, 10 Dec 2025 08:50:42 -0500

Our friend, the RSS feed.

A meta lesson about AI assistance

Sun, 07 Dec 2025 17:01:00 -0500

I just completed my first attempt at coding using AI, in this case having Claude assist me with putting together a simple client-side OPML parser using Dave Winer’s Feedland service.

Winer’s original script is pretty slick, and includes a list of all my feeds with titles, URLs, and categories; click-to-expand functionality to see the 5 most recent posts from each feed; clickable post titles that open articles in new tabs; sort options (by title or by update); and automatic updates when I change my FeedLand subscriptions.

You can check it out here: Feeds

The official documentation method didn’t initially work because Hugo (the blogging software behind micro.blog) was wrapping client-side templates around the script. The toolkit requires server-side dependencies that don’t exist on static sites like micro.blog, and we hit a cascade of missing JavaScript dependencies (jsonStringify, servercall, etc.). Each fix revealed another dependency, leading to some “sunk cost” frustrations for me. I kept trying because I wanted to see if Claude could pull it together. Through trial and error, I got to a point where the OPML file was rendered correctly without server dependencies or complex external libraries.

Time invested: ~3 hours (including wrong turns)

Time it should take: 10 minutes

AI extended my code reach beyond my practical skillset by quite a lot. I now have a dynamic and dedicated place to read and share news feeds as I wish. Though even when generative AI works and works well, I have significant concerns about the intellectual property implications of AI, and this project brought those tensions into sharp focus. The AI could only help me because it was trained on documentation and intellectual work from the open source community, contributions made freely in the spirit of knowledge sharing, not to train commercial AI systems. I tapped into their expertise by paying Anthropic $15 a month. While I’m grateful for the accessibility this provides to non-developers like me, I recognize there’s an unresolved ethical question about whether this use respects the intent and labor of the original creators. The feat is incredible; the foundation it’s built on deserves careful consideration.

After the exercise was complete, I asked Claude how I could have improved my prompting to make this process easier, and in short, Claude said I could have been a web developer. But since I’m not, here’s what it recommended:

✅ When the process isn’t working, question the process mid-stream. Most people either give up or keep following bad advice deeper into rabbit holes. Stop and question the LLM’s process and ask for alternatives to force a reset.

✅ Push for usability. Keep bringing the conversation back to what you actually need the end result to do, not what’s technically impressive or “correct.” In my case, this meant repeatedly asking “can I click through to the articles?” rather than getting lost in discussions about CORS proxies or JavaScript syntax. Focus on outcomes, not implementation details.

✅ Ask for complete solutions. Instead of trying to mentally patch together incremental changes across multiple responses, ask the LLM to provide fresh, complete code each time. This prevents copy-paste errors and ensures you’re always working with a coherent, tested solution. There’s more than one way to crack an egg, but you want the whole egg regardless.

After all that, I got it to work but can’t figure out how to make it show up in my header menu, with or without Claude. TBD.

Mon, 17 Nov 2025 09:46:10 -0500

Solarpunk is happening in sub-Saharan Africa, a movement to bring electricity to places that are impacted by “last mile” challenges in grid engineering and politics.

Thu, 13 Nov 2025 19:57:27 -0500

When AI is wrong, who pays?

Rhetoric of intertextuality

Sun, 09 Nov 2025 14:36:20 -0500

“… every text is connected to other texts by citations, quotations, allusions, borrowings, adaptations, appropriations, parody, pastiche, imitation, and the like. Every text is in a dialogical relationship with other texts. In sum, intertextuality describes the relationships that exist between and among texts. What follows is a discussion of the strategies of intertextuality.”

What is this site and why am I doing it?

Sun, 09 Nov 2025 14:12:00 -0500

In recent history I stopped posting on most social media and moved to the fediverse. I still browse the social platforms to keep up with trends and friends, but I only post on my private IG and here.

What I share here is separate from but related to my professional life — I’m thinking out loud and making room for rough, unfinished ideas. I write mainly for myself, but if others find it useful, that’s great. The practice of reading and reflecting makes your thinking stick, and I am from a certain time and place, so this is how I approach learning and communicating about what I’m learning. It’s a habit.

While this is my preferred approach, I acknowledge that sharing unfinished ideas publicly is risky and you have to accept accountability for the messiness that comes with that. But I also know that working through your vulnerability through the act of writing lets you tap into your most creative, innovative self and test your ideas against an evolving sense of what’s good. The potential for an audience, however real or implied, keeps you more honest and less self-indulgent. Despite the trade offs, I think it’s worthwhile.

As I add to this page, I’ll be thinking out loud about digital rhetoric and communication alongside emerging technology, and linking back to foundational ideas I see reflected online today. Occasionally I’ll say something longer.

Thu, 30 Oct 2025 21:19:54 -0500

I miss Twitter because I’m full of big opinions and inappropriate one-liners. Anyway, here’s an analysis from WIRED on the implications of this month’s AWS outage.

Fri, 19 Sep 2025 16:02:16 -0500

On the rise of faith tech.

Thu, 18 Sep 2025 11:46:23 -0500

Harvard Business Review offers this take on why it’s bad for business to automate our way out of staffing entry-level positions.

⚡ AI's last mile problem in higher ed

Sun, 17 Aug 2025 09:15:00 -0500

I graduated from college right before the 2008 recession and bounced through some unpromising temp jobs until an opportunity emerged for a permanent position. Sometimes you just need to get in where you fit in, and so I did. That’s how I came to work for a regional cable company that used federal money to expand the new national broadband network, extending out to the rural communities dotting central Indiana.

It was a front row seat to the national broadband expansion efforts of the early 2000s. Our business ran right across the state, spanning the 80 or so miles from Attica to Kokomo, which included several small cities with large manufacturers, two public research universities, and several community and liberal arts colleges. The strip of broadband fiber at the core of our service followed existing highways and electrical lines that split the corn and soybean fields from town to town, feathering out to more rural areas from there.

I worked a variety of roles there that put me face-to-face with a classic technical problem: the last mile. On many occasions, someone would come in looking pensive, and explain that the fiber had been extended all the way from town to their hamlet, and yet there was no plan to connect their property to the pole. Over time the pattern was clear: while the network was expanded, the cost of running a physical line to each individual property was too expensive and specific at scale. These customers often left without a path forward despite all their efforts and ours.

The “last mile problem” refers to the logistical challenges and high costs associated with the final leg of delivering goods or services to the end customer. It’s often the most difficult and expensive part of the supply chain, despite being a relatively short distance. The pattern shows up everywhere: public transit can get commuters most of the way most of the time, but that final leg of the journey remains specific and individual and problematic. E-commerce companies promise drone delivery solutions, scooter and bike-share apps claim to solve urban mobility gaps, but these technological optimizations remain persistently stubborn at scale, running up against the messy realities of sidewalks, intersections, and actual human behavior.

Tl;dr: I’ve been turning over this suspicion that AI automation will hit a classic “last mile problem,” especially in the public sector.

AI systems, particularly LLMs, are like those systems—they work incredibly well in their intended domain, processing and manipulating information. But because they’re fundamentally an information-only approach, that creates their own last mile problem when we try to implement them in physical and context-specific environments. Public institutions are uniquely specific — they are often the originators and producers of knowledge and the keepers of original policy, tasked with making the rubber hit the road. Additionally, the need for comprehensive data protection required by public workers and institutions fundamentally hamstring potential applications.

Actually implementing recommendations is where you hit the last mile. This is the work of public administration.

Imagine an AI application trained on every facilities management manual ever written and tuned to synthesize best practices for HVAC optimization. It can analyze years of energy usage data and recommend precise temperature adjustments for different zones of a building, but can’t feel that the third floor is always stuffy, or know that the facilities manager retired last year and took decades of institutional knowledge with him. Building A’s HVAC system was installed in 1987 and has a manual keypad. Building B’s system interfaces with the campus-wide monitoring system, but unreliably, and investigation is slated for later, someday, when resources allow. Professor Smith has taught in Room 204 for 25 years and will blow up your spot before moving to a different classroom for maintenance. Your engineers who manage these spaces are balancing human teams, who have time off and training and other priorities they manage in life. So, you need staff who understand the quirks of each area, the history of each system, the politics of which departments will accept changes and which will flood your inbox with complaints. You need someone who knows that the third floor always runs hot because of a design flaw from 1974, and that the solution isn’t more precise control but a $50,000 renovation that’s been deferred for a decade because a glittering new project across campus takes priority.

Imagine this tangle of questions and contingencies times infinity on every university campus in existence. Universities are like cities—they’ve been built and rebuilt over decades or centuries, with layers of systems and fiefdoms that weren’t designed to work together. AI recommendations assume a level of standardization that simply doesn’t exist. Every AI implementation in higher ed requires navigating multiple constituencies with different priorities and power structures. It’s like trying to redesign traffic patterns in a neighborhood where the residents, business owners, commuters, and city planners all have veto power and conflicting interests.

So. When looking at efficiency efforts spinning up across the education sector, I’m feeling pensive, trying to understand how exactly the house gets connected to the pole.

The promise of new tech in higher ed needs to more deeply consider the translation costs: the human labor, institutional knowledge, knowledge documentation and local adaptation required to bridge between the usefulness of tech and specific realities of public university work. Public employees want modernization and don’t want to fall behind. We want systems that work. We are also balancing a great deal of change and pressure as a sector, with fewer material resources than ever. We need less marketing and more right-sizing in the claims around AI against the political and tech realities of public administration.

This disconnect between technological promise and implementation reality becomes even more critical as higher education faces increased political scrutiny. When tech vendors promise that AI will solve efficiency problems or reduce administrative costs, institutions are under immense pressure to deliver measurable results quickly. But the translation costs we experience don’t disappear just because the political pressure to modernize increases.

The institutions that thread this needle will be the ones that accurately assess these translation costs upfront and set expectations accordingly—not the ones that assume the technology will magically bridge the gap between digital and physical, abstract and specific.

⚡ Navigating AI in higher ed communications: A practitioner's guide

Fri, 15 Aug 2025 11:49:12 -0500

by Lauren Bruce

As communications professionals in higher education, we work for institutions built on the pursuit of knowledge and innovation, yet many of us feel uncertain about how to thoughtfully integrate one of the most significant technological advances of our time: artificial intelligence.

Over the past year, my team has wrestled with questions that didn’t exist in our profession just a few years ago. Should we use AI to draft articles and email copy? How do we disclose AI-generated content, or do we? When does AI assistance cross the line from helpful tool to ethical concern?

These aren’t abstract questions any longer. Over the last year, I had to overcome AI resistance of my own to develop practical, hands-on approaches to AI use that align with our institutional values while acknowledging the realities of modern communications work (more on that below). What I’ve learned is that the answers aren’t found in blanket policies or rules, but in applying our existing professional ethics to these new tools. Here is where I am today on the journey from AI praxis to practice.

Mission first

The foundation of responsible AI use in our field starts with a principle we already know: everything we do should advance our institution’s educational mission. Higher education exists to create, share, and preserve knowledge while fostering critical thinking and diverse perspectives, in service of students, faculty, researchers, workers and the world.

The bulk of our work comes from conversations with colleagues, understanding of our campus dynamics and processes, and professional judgment about what our community needs to hear. This inevitably means more work upfront, but it maintains the authenticity and institutional knowledge that our audience deserves, regardless of whether AI tools are part of the process.

Transparency without paranoia

Do I need to mention AI every time I use it? The answer isn’t simple, but I’ve found a helpful framework: consider whether your audience would feel misled if they knew how AI was involved in creating the content.

When I use AI to polish grammar and shape format, that feels similar to using spell-check – it’s helpful but not something that changes the fundamental nature of the content we wish to communicate. But when AI helps generate the main structure for a story about campus policy changes, that’s a different ball game. The audience expects those priorities and framing decisions to come from human judgment about what matters to our community.

Internally, we differentiate between the two by defining whether or not you are “automating” processes using AI, or “augmenting” processes using AI. Full disclosure, my area of experience is in augmentation, not automation. That said.

I’ve started recommending simple disclosures when AI plays a substantial role in content creation. A line like “This article was developed with AI assistance” maintains trust while allowing us to thoughtfully benefit from these tools. It’s not about being defensive, it’s about being transparent with the people we serve, especially as the tech and attitudes around it evolve over time. Additional qualifications can be included here, such as how the information was shaped and shared by AI or not (privacy implications abound).

Here, it’s important to remember to only use your university-approved tools, because university enterprise AI tools are modified to meet campus rules and requirements related to data handling.

The accuracy imperative

Perhaps nowhere are the stakes higher than with accuracy. In higher education communications, we’re not just sharing information—we’re stewarding public trust in our institutions and, by extension, in higher education itself. In addition, much of the information we are communicating is original, in that it’s new information that cannot be generated using the limitless soup of generative AI.

Every piece of AI-generated content requires human verification, especially anything involving numbers, research findings, or claims about institutional achievements. This means checking sources, confirming statistics, and ensuring that quotes are accurate and properly sourced. It’s more work, but the alternative—publishing incorrect information—could undermine years of relationship-building with community stakeholders and partners.

The promise of speed and efficiency that comes with generative AI must be balanced with the work of close reading, the skill and practice of carefully analyzing a passage’s language, content, structure, and patterns in order to understand what a passage means, what it suggests, and how it connects to our larger body of work. I firmly believe that close reading, learned in the Humanities and Social Sciences, will become increasingly important to understand, shape and steer AI output, especially with regard to public communication best practices.

Inclusion as a practice

AI bias isn’t an abstract concern—it shows up in subtle but significant ways in the work. I’ve noticed that AI tools often default to formal, academic language that might exclude first-generation college students, or suggest examples and metaphors that assume certain cultural backgrounds, for example.

This has made me more intentional about prompt engineering—the way I request AI assistance. I build digital accessibility and plain language best practices into my prompts, in alignment with institutional best practices. One tip is to draft the original using my chosen, intentional language, then ask for revisions using as much of the original verbiage as possible. The difference in output is significant and it allows me to focus on higher-order communication strategy while demonstrating both accuracy and inclusive values in our output.

Privacy and the long view

Working at a public university means balancing transparency with appropriate privacy protections. We work within strict guidelines about what information can be included in AI prompts, particularly around student data, personnel information, and strategic planning discussions. Again, it’s important to only use your university-approved tools, because university enterprise AI tools are modified to meet campus rules and requirements related to data handling.

The challenge is that AI tools work best with context, but providing that context can sometimes mean sharing information inappropriately. I’ve learned to be creative about how I frame requests to AI tools—giving enough context for useful output while protecting sensitive information about individuals and institutional operations.

I focus AI prompts on publicly available information rather than including details from internal planning discussions or individual faculty concerns. It requires more thoughtful preparation, but it ensures we’re protecting appropriate confidentiality.

Speed vs. strategy

The efficiency of AI is seductive, especially when facing tight deadlines and endless communication requests. But I’ve learned that speed can’t come at the expense of quality or authenticity.

Authentic institutional voice and authority doesn’t emerge from algorithms—it requires the deliberate application of human judgment to ensure our plans and communications reflect our campus culture, embody our values, and resonate with our specific audiences. The strategic thinking we bring—our ability to read context, navigate relationships, and understand the subtle dynamics of higher education communication—cannot be automated.

Consider my own practice: I frequently engage AI as a collaborative thinking tool, particularly for structural planning and format development. However, AI’s default tendency toward comprehensive, multi-layered approaches often produces unnecessarily complex frameworks for university communication realities. This is where professional judgement becomes critical. Strong strategic foundations and institutional knowledge allow us to right-size AI’s expansive suggestions into focused, contextually appropriate communication plans that actually serve our goals and communities.

Looking ahead

What I’ve learned over this past year is that responsible AI use isn’t about following a rigid set of rules. It’s about applying the professional ethics we already have to new technological capabilities. The core principles that guide good communications work—accuracy, transparency, service to mission, respect for audience—remain the same.

What’s different is that we now have tools that can enhance our ability to live up to those principles, if we use them thoughtfully. AI can help us communicate more clearly, research more efficiently, and reach broader audiences. But only if we maintain our professional judgment about when, how, and why to use these tools.

As our field continues to evolve, I’m convinced that the communications professionals who thrive will be those who can harness the power of AI while maintaining the human insight, ethical judgment, and institutional knowledge that define excellence in our profession. The technology will keep changing, but our commitment to serving our institutions and communities through ethical, effective communication remains constant. That’s the foundation we build on, whether we’re writing with pen and paper, collaborating in a digital document, or prompting the most sophisticated AI tool on campus.

*This post reflects my ongoing learning about AI ethics in communications practice and was generated using the assistance of AI (Claude, Gemini). Cross-posted on LinkedIn.

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