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AI Can Now Help Write Wikipedia Pages For Overlooked Scientists (popsci.com)
An anonymous reader quotes a report from Popular Science: Plenty of prominent scientists have Wikipedia pages. But while checking to see if someone specific has a Wikipedia page is a quick Google search away, figuring out who should be on Wikipedia but isn't -- and then writing an entry for him or her -- is much trickier. For example, you may or may not have heard of Christina Economos. She doesn't have a Wikipedia page about her, although she's a professor at Tufts University and the New Balance Chair in childhood nutrition. But while she lacks a Wikipedia page, she does have a very short stub describing who she is professionally on a website made by a company called Primer. That little blurb, which could one day grow into a full-blown Wiki entry, was created by an AI system dubbed Quicksilver. The idea behind the project is to use AI as a jumping off point. Humans can use it to help them write Wikipedia pages for scientists who don't have them, but deserve to. For example, on Economos' Primer page, there's a link to an article from CBS Boston that mentions her -- a good potential source for a human Wikipedia editor who may want to write an entry for her.
Primer launched officially last year and uses AI to read information and generate reports; part of its focus is doing the kind of work an intelligence analyst might do. Artificial intelligence generally needs data to learn from, and so for this project, Primer used around 30,000 existing scientist Wikipedia pages to train their machine learning systems. Then they fed 200,000 names and related employment information into their AI system. Those names came from the listed authors of scientific papers focused on computer science and biomedical research provided to Primer from the Allen Institute for Artificial Intelligence. If you're curious to see a sample, you can head on over to this page, which has 100 examples of AI-generated Wikipedia blurbs.
Primer launched officially last year and uses AI to read information and generate reports; part of its focus is doing the kind of work an intelligence analyst might do. Artificial intelligence generally needs data to learn from, and so for this project, Primer used around 30,000 existing scientist Wikipedia pages to train their machine learning systems. Then they fed 200,000 names and related employment information into their AI system. Those names came from the listed authors of scientific papers focused on computer science and biomedical research provided to Primer from the Allen Institute for Artificial Intelligence. If you're curious to see a sample, you can head on over to this page, which has 100 examples of AI-generated Wikipedia blurbs.
Now AI is going to trash Wikipedia with useless stub articles based on information you can google within 10 seconds That's just what we need.
Another aspect of the project is to make it easier for scientists who are women to get the representation they deserve on Wikipedia—to empower human editors “to close the gender gap in representation of women in science,” Bohannon says. One of the ways that can happen is if a group wants to create more Wikipedia pages with a focus on women scientists, they could use data from Quicksilver, which Bohannon points out is filternable by gender.
This is yet another sexist politically-motivated project, not one that genuinely cares about scientific merit or improving Wikipedia.
For some things, automatic pages are appropriate.
There is a guy who has "written" 2.7 million Wikipedia pages. For example, he created a page for every single bird species where the pages don't already exist. That's OK because the basic information for each species is pretty formulaic - English name, Latin name, classification, habitat perhaps. Once the page exists, humans can add more "interesting" info if they have any.
This method doesn't work well for other topics, like people.