Can GPT-3 Pass a Writer’s Turing Test?

While earlier computational approaches focused on narrow and inflexible grammar and syntax, these new Transformer models offer us novel insights into the way language and literature work.

The Journal of Cultural Analytics has a nice article that asks  Can GPT-3 Pass a Writer’s Turing Test? They didn’t actually get access to GPT-3, but did test GPT-2 extensively in different projects and they assessed the output of GPT-3 reproduced in an essay on Philosophers On GPT-3. At the end they marked and commented on a number of the published short essays GPT-3 produced in response to the philosophers. They reflect on how would decide if GPT-3 were as good as an undergraduate writer.

What they never mention is Richard Powers’ novel Galatea 2.2 (Harper Perennial, 1996). In the novel an AI scientist and the narrator set out to see if they can create an AI that could pass a Masters English Literature exam. The novel is very smart and has a tragic ending.

Burrows and Antonia Archives: Centre For 21st Century Humanities

What happens to old digital humanities projects? Most vanish without a trace. Some get archived like the work of John Burrows and others at the Centre For Literary And Linguistic Computing (CLLC). Dr. Alexis Antonia kept an archive of CLLC materials which is now available from the Centre For 21st Century Humanities.

Common Errors in English Usage

An article about authorship attribution led me to this nice site on Common Errors in English Usage. The site is for a book with that title, but the author Paul Brians has organized all the errors into a hypertext here. For example, here is the entry on why you shouldn’t use enjoy to.

What does this have to do with authorship attribution? In a paper on Authorship Identification on the Large Scale the authors try using common errors as feature to discriminate potential authors.