Artificial intelligence and copyright

Author: Andres Guadamuz

Abstract: Robotic artists have been involved in various types of creative works for a long time. Since the 1970s computers have been producing crude works of art, and these efforts continue today. Most of these computer-generated works of art relied heavily on the creative input of the programmer; the machine was at most an instrument or a tool very much like a brush or canvas. But today, we are in the throes of a technological revolution that may require us to rethink the interaction between computers and the creative process. That revolution is underpinned by the rapid development of machine learning software, a subset of artificial intelligence that produces autonomous systems that are capable of learning without being specifically programmed by a human.

A computer program developed for machine learning purposes has a built-in algorithm that allows it to learn from data input, and to evolve and make future decisions that may be either directed or independent. When applied to art, music and literary works, machine learning algorithms are actually learning from input provided by programmers. They learn from these data to generate a new piece of work, making independent decisions throughout the process to determine what the new work looks like. An important feature for this type of artificial intelligence is that while programmers can set parameters, the work is actually generated by the computer program itself – referred to as a neural network – in a process akin to the thought processes of humans.

Creating works using artificial intelligence could have very important implications for copyright law. Traditionally, the ownership of copyright in computer-generated works was not in question because the program was merely a tool that supported the .process, very much like a pen and paper. Creative works qualify for copyright protection if they are original, with most definitions of originality requiring a human author.

Source: WIPO Magazine

Citation: Guadamuz, Andres. “Artificial intelligence and copyright.” WIPO Magazine, No. 5/2017(October), pp. 14-19.

Stop this waste of people, animals and money

Author: David Moher et al

Abstract: Predatory journals are easy to please. They seem to accept papers with little regard for quality, at a fraction of the cost charged by mainstream open-access journals. These supposedly scholarly publishing entities are murky operations, making money by collecting fees while failing to deliver on their claims of being open access and failing to provide services such as peer review and archiving.

Despite abundant evidence that the bar is low, not much is known about who publishes in this shady realm, and what the papers are like. Common wisdom assumes that the hazard of predatory publishing is restricted mainly to the developing world. In one famous sting, a journalist for Science sent a purposely flawed paper to 140 presumed predatory titles (and to a roughly equal number of other open-access titles), pretending to be a biologist based in African capital cities. At least two earlier, smaller surveys found that most authors were in India or elsewhere in Asia. A campaign to warn scholars about predatory journals has concentrated its efforts in Africa, China, India, the Middle East and Russia. Frequent, aggressive solicitations from predatory publishers are generally considered merely a nuisance for scientists from rich countries, not a threat to scholarly integrity.

Our evidence disputes this view. We spent 12 months rigorously characterizing nearly 2,000 biomedical articles from more than 200 journals thought likely to be predatory. More than half of the corresponding authors hailed from high- and upper-middle-income countries as defined by the World Bank.

Citation: Moher, David, et al. “Stop This Waste of People, Animals and Money.” Nature 549, 23–25. http://doi.org/10.1038/549023a

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Who is Actually Harmed by Predatory Publishers?

Authors: Martin Paul Eve and Ernesto Priego

Abstract: ‘Predatory publishing’ refers to conditions under which gold open access academ-ic publishers claim to conduct peer review and charge for their publishing services but do not, in fact, actually perform such reviews. Most prominently exposed in recent years by Jeffrey Beall, the phenomenon garners much media attention. In this article, we acknowledge that such practices are deceptive but then examine, across a variety of stakeholder groups, what the harm is from such actions to each group of actors. We find that established publishers have a strong motivation to hype claims of predation as damaging to the scholarly and scien-tific endeavour while noting that, in fact, systems of peer review are themselves already acknowledged as deeply flawed.

Citation: Eve, M.P., & Priego, E. (2017). Who is Actually Harmed by Predatory Publishers?. TripleC,  15(2), 755-770 . http://www.triple-c.at/index.php/tripleC/article/view/867/1041

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