{"id":15440,"date":"2018-05-23T10:00:03","date_gmt":"2018-05-23T04:30:03","guid":{"rendered":"https:\/\/www.enago.com\/academy\/?p=15440"},"modified":"2018-05-23T13:00:08","modified_gmt":"2018-05-23T07:30:08","slug":"researchers-boycott-new-nature-journal-on-machine-learning","status":"publish","type":"post","link":"https:\/\/www.enago.com\/academy\/researchers-boycott-new-nature-journal-on-machine-learning\/","title":{"rendered":"Researchers Boycott New Nature Journal on Machine Learning"},"content":{"rendered":"

Artificial intelligence or machine learning is where machines are programmed to simulate human traits such as problem-solving and learning. Machine learning researchers historically published their work in open access journals. However, Nature<\/em> has recently called for papers for their new journal Nature Machine Intelligence<\/em>. Despite\u00a0Nature<\/em>\u2019s high reputation, the machine learning community has opposed the new journal. They have even signed a petition to boycott<\/a> Nature Machine Intelligence<\/em>. Let us find out why they have done so.<\/p>\n

Nature<\/em>\u2019s New Journal on Machine Learning<\/h2>\n

Nature Machine Intelligence, <\/em>the new journal, aims to publish a wide range of topics involving artificial intelligence, robotics, and machine learning. They also want to enhance discussion on the impact that artificial intelligence will have on issues such as society and industry. The first issue is due to be launched in January 2019<\/a>.<\/p>\n

Most researchers aim to publish in journals with high impact factors, whether they are open-source or not. These impact factors depend on the average number of paper citations. Higher the impact factor, more prestigious is the journal. Nature<\/em> is such a journal, where researchers aspire to publish their work<\/a> at least once in their career. Hence, the publishers expected the research community to accept this new closed-access journal readily.\u00a0<\/strong><\/p>\n

The Rationale of the Researchers<\/h2>\n

The response received from the research community, especially the machine learning researchers themselves, was not quite positive. Machine learning scientists believe that research should be freely available and accessible to all for the advancement of the field. They are concerned that students and staff of institutions that cannot afford to pay the subscription fees will not have access to Nature Machine Intelligence<\/em>.<\/p>\n

Scientists are also concerned that the quality of the research submitted to the new journal will lean towards \u2018flashy\u2019 research in its early stages of development. These views initiated the boycott<\/a> of the new machine learning journal, followed by a petition against it. To date, over 2900 machine learning scientists have signed this petition which states that \u201cthey will not submit to, review, or edit for this new journal.\u201d<\/p>\n

The Rationale of the Publishers<\/h2>\n

In the previous section, we discussed the views of the researchers. The publishers, on the other hand, feel that they are justified in charging for their journal. They claim to provide high levels of author service. They want to publish an informative journal<\/a> containing content beyond primary research. For that, they need substantial editorial development, which will require money. The publishers suggest recovering costs through reader subscription access, rather than burdening the authors with a pay-to-publish model.<\/p>\n

In response to the petition, Nature Machine Intelligence <\/em>tweeted, expressing their views. According to them, Nature<\/em> MI and OA journals can co-exist within the academic community. Each of the journals can cater to the part of the research community interested to publish in it.<\/p>\n

Possible Outcomes of the Boycott<\/h2>\n