

choice quote from Elsevier’s response:
Q. Have authors consented to these hyperlinks in their scientific articles?
Yes, it is included on the signed agreement between the author and Elsevier.
Q. If I were to publish my work with Elsevier, do I risk that hyperlinks to AI summaries will be added to my papers without my consent?
Yes, because you will need to sign an agreement with Elsevier.
consent, everyone!
I’ve often called slop “signal-shaped noise”. I think the damage already done by slop pissed all over the reservoirs of knowledge, art and culture is irreversible and long-lasting. This is the only thing generative “AI” is good at, making spam that’s hard to detect.
It occurs to me that one way to frame this technology is as a precise inversion of Bayesian spam filters for email; no more and no less. I remember how it was a small revolution, in the arms race against spammers, when statistical methods came up; everywhere we took of the load of straining SpamAssassin with rspamd (in the years before gmail devoured us all). I would argue “A Plan for Spam” launched Paul Graham’s notoriety, much more than the Lisp web stores he was so proud of. Filtering emails by keywords was not being enough, and now you could train your computer to gradually recognise emails that looked off, for whatever definition of “off” worked for your specific inbox.
Now we have the richest people building the most expensive, energy-intensive superclusters to use the same statistical methods the other way around, to generate spam that looks like not-spam, and is therefore immune to all filtering strategies we had developed. That same blob-like malleability of spam filters makes the new spam generators able to fit their output to whatever niche they want to pollute; the noise can be shaped like any signal.
I wonder what PG is saying about gen-“AI” these days? let’s check:
Who would have thought that A Plan for Spam was, all along, a plan for spam.