ai – News For Wombats

ScabGPT

Via Daily Beast and Daily Nous: The administration at Boston University has made a number of tone-deaf suggestions for how faculty can juggle students while their graduate student TAs are on strike. Among these: “Engage generative AI tools to give feedback or facilitate ‘discussion’ on readings or assignments.”

Last year, I wrote that “there will be people who lose their jobs because of generative algorithms. This won’t be because they can be replaced, but instead because of rapacious capitalism. To put it in plainer terms, because their management is a bunch of dicks.”

Dots. Connected.

Pluralism (art) and trust (AI)

Two small updates:

Does art pluralism lead to eliminativism? Co-authored with Christy Mag Uidhir and published recently in Estetika. TL;DR: Maybe.
On trusting chatbots, still in draft form but updated. TL;DR: It’s vexing.

Imagination, philosophy, and imitation games

Via Daily Nous, I came across a blog post by Justin Smith-Ruiu about creative writing as philosophy. The post is, ultimately, an argument that philosophy can be “incitement of the imagination, by creative means, to see the world in unfamiliar ways.” I agree with that! But there are digressions along the way that range from false speculation to attacks on the kind of philosophy that I (sometimes) do.

Engines of enshittification

Via Ars Technica, I’ve learned that shady Amazon sellers have been using chatbots to automatically write item descriptions. The result is hot offers on items like “I cannot fulfill that request” and “I apologize but I cannot complete this task.” This is a natural progression from Amazon product listings which were simply misdescribed by humans.

Lincoln!

My paper Generative AI and photographic transparency now has a DOI and is on-line, occupying that liminal space of published but not quite which is characteristic of contemporary scholarship. The publisher has given me a link to the published version, but it won’t let you download or print it. (As always, you can grab the preprint from my website.)

Hot takes on new things

Like pretty much everybody else, I’ve been thinking about chatbots and generative AI. Unlike other things I write about, like scurvy, this is a hot topic. It’s hard to keep up using my usual strategy of rambling here on the blog, ruminating, and letting ideas simmer. Nevertheless, there are these two papers:

Generative AI and photographic transparency: accepted and forthcoming at AI&Society
On trusting chatbots: a draft that riffs on my earlier work on Wikipedia to ask how we should think about claims that we read when interacting with chatbots

It took me years to write it

Fifteen years ago, I conducted a small study testing the error-correction tendency of Wikipedia. Not only is Wikipedia different now than it was then, the community that maintains it is different. Despite the crudity of that study’s methods, it is natural to wonder what the result would be now. So I repeated the earlier study and found surprisingly similar results.

That’s the abstract for a short paper of mine that was published today at First Monday. It is a follow-up to my earlier work on the epistemology of Wikipedia.

LLMs have the wrong ontology for scholarship

I have read suggestions that LLMs might help with the routine and tedious parts of writing, like a literature review. This is undermined by their failure to distinguish the literature (which is to be reviewed) from discourse in general.

Exchanging Marx for Lincoln

I just posted a draft of Generative AI and Photographic Transparency, a short paper that is about those things. It builds on two blog posts that I wrote a while ago, but fleshes out the discussion in several respects. Whereas the blog posts used pictures of Karl Marx as their specimen example, the paper instead considers pictures of Abraham Lincoln. The change lets me work in some quotes from William James and Oliver Wendell Holmes.

It is still a draft, so comments are welcome.

Generative AI and homogenization

Among the legitimate worries about Large Language Models is that they will homogenize diverse voices.¹ As more content is generated by LLMs, the generic style of LLM output will provide exemplars to people finding their own voices. So even people who write for themselves will learn to write like machines.