Dear Heather, all, Just a few comments below in your post.
Jeroen Bosman -------- Original message -------- From: Heather Morrison <heather.morri...@uottawa.ca> Date: 13/07/2018 17:54 (GMT+01:00) To: "Global Open Access List (Successor of AmSci)" <goal@eprints.org> Subject: Re: [GOAL] Why translating all scholarly knowledge for non-specialists using AI is complicated Further questions / comments for Jason Priem (JP) and anyone who cares to participate... JP: So the first part will be the annotation of difficult words in the text, which is just a mash-up of basic named-entity recognition and Wikipedia/Wikidata definitions. Pretty easy, pretty safe. HM: Q1: to clarify, we are talking about peer-reviewed journal articles, right? You are planning to annotate journal articles that are written and vetted by experts using definitions that are developed by anyone who chooses to participate in Wikipedia / Wikidata, i.e. annotating works that are carefully vetted by experts using the contributions of non-experts? 》》》 It is too simple to use a dichotomy of experts-non experts. This is a graded difference. Also it is very incorrect to suppose that Wikipedia is not also contributed to by experts. There are numerous examples of active and emeritus scholars editing lots of science articles in wikipedia. You might even find that definitions used in the journal articles themselves are sourced from wikipedia. Q2: who made the decision that this is safe, and how was this decision made? Comments: I submit that this is not safe. There are reasons for careful vetting of expertise, through a long process of education and examination, review in the process of hiring, making decisions about tenure, promotion, and grant applications, and then peer review and editing of the work of those qualified to have their work considered. Mine is not an elitist perspective. There are areas where the expertise does not lie in the academy at all; examples include traditional knowledge and native languages. If the author has not given permission, this is a violation of the author's moral rights under copyright. This includes all CC licensed works except CC-0. 》》》 Interesting but questionable angle. If this is generated on the fly just as with litteral translation tools and not published I do not see how it would be a violation. The plain language explanations could also be posted as 'comments': "we think this abstracts means ....". JP: Another set of features will be automatically categorizing trials as to whether they are double-blind RCTs or not, and automatically finding systematic reviews. These are all pretty easy technically, and pretty unlikely to point people in the wrong directions. But the start adding value right away, making it easier for laypeople to engage with the literature. HM: this does not seem problematic and seems likely to be primarily useful to scholars. I am not opposed to your project, just the assumption that a two-year project is sufficient to create a real-world system to translate all scholarly knowledge for the lay reader. JP: From there we'll move on to the harder stuff like the automatic summarization. Cautiously, and iteratively. We certainly won't be rolling anything out to everyone right away. It's a two-year grant, and we're looking at that as two years of continued development, with constant feedback from users as well as experts in the library and public outreach worlds. If something doesn't work, we throw it away. Part of the process. HM: this is highly problematic. A cautious and iterative approach is wise; however this is not feasible in the context of a two-year grant. May I suggest a small pilot project? Try this with a few articles in an area where at least one member of your team has a doctorate. Take the time to evaluate the summaries. If they look okay to your team, plan a larger evaluation project involving other experts and the lay readers you are aiming to engage (because what an expert thinks a summary says may not be the same as how a non-expert would interpret the same summary). Thank you for posting openly about the approach and for the opportunity to comment. best, Heather Morrison Associate Professor, School of Information Studies, University of Ottawa Professeur Agrégé, École des Sciences de l'Information, Université d'Ottawa heather.morri...@uottawa.ca<mailto:heather.morri...@uottawa.ca> https://uniweb.uottawa.ca/?lang=en#/members/706 _
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