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Academics share machine-learning research freely. Taxpayers should not have to pay twice to read our findings
[...] In my own field of machine learning, itself an academic descendant of Gauss’s pioneering work, modern data are no longer just planetary observations but medical images, spoken language, internet documents and more. The results are medical diagnoses, recommender systems, and whether driverless cars see stop signs or not. Machine learning is the field that underpins the current revolution in artificial intelligence.
Machine learning is a young and technologically astute field. It does not have the historical traditions of other fields and its academics have seen no need for the closed-access publishing model. The community itself created, collated, and reviewed the research it carried out. We used the internet to create new journals that were freely available and made no charge to authors. The era of subscriptions and leatherbound volumes seemed to be behind us.
The public already pays taxes that fund our research. Why should people have to pay again to read the results? Colleagues in less well-funded universities also benefit. Makerere University in Kampala, Uganda, has as much access to the leading machine-learning research as Harvard or MIT. The ability to pay no longer determines the ability to play.
Machine learning has demonstrated that an academic field can not only survive, but thrive, without the involvement of commercial publishers. But this has not stopped traditional publishers from entering the market. Our success has caught their attention. Most recently, the publishing conglomerate Springer Nature announced a new journal targeted at the community called Nature Machine Intelligence. The publisher now has 53 journals that bear the Nature name.
[...] at the time of writing, more than 3,000 researchers, including many leading names in the field from both industry and academia, have signed a statement refusing to submit, review or edit for this new journal. We see no role for closed access or author-fee publication in the future of machine-learning research.
(Score: 4, Interesting) by bzipitidoo on Thursday May 31 2018, @01:23AM
Also, professional societies are very much out of step on this matter. The ACM and IEEE maintain digital libraries on their own systems, rather than disseminate the research therein to public and university libraries, as they know all too well they could easily do. Especially as they have insisted that authors turn over all copyright to them, asked for more rights than was necessary, just so they need not fear being sued for infringement under any circumstances. But they weren't supposed to do this, not this lockdown. It's total hoarding, what they do. Keeping their collections so close empowers them to gouge for access, and they do. To access the ACM's collection, if you are not affiliated with a university, you have to become a member for $100 per year, and pay an additional $100 per year for library access. Cheaper than paying $30 per paper if you look at more than 6 in a year, but that's about all that can be said for the system.
I could maybe understand a society of professional artists not getting it, but those two are the professional societies for Computer Science and Electrical Engineering, arguably the professions deepest into technology. If any group is composed of members that ought to understand the implications, it's them. I mean, freaking Father of the Internet, Vint Cerf, was president of the ACM, and under him the terms for access to ACM digital library did not change at all. Aaron Swartz seems to be one of the few who got it.
I can also understand the need to recoup costs. But I have never seen any promise that the ACM or IEEE will release their libraries once they have recouped costs. The most they do is say the money is plowed back into enhancing the library. Uh, huh. Yeah, sure, digitize every issue of their monthly publication, and all the papers in all their journals from before they went all digital, which should have been no later than the 1990s, but it took a while to dethrone King Paper. Wonder how much of the fees are wasted on overhead, for fat pay packages for the management.