Importance of artificial intelligence in academic publishing industry

Importance of artificial intelligence in academic publishing industry

The denomination “artificial intelligence” was proposed by John McCarthy at a conference at Dartmouth in 1956. The term has become prominent in the field of many industries because AI and machine learning has the potential to perform tasks quickly that typically consumes more time by a human. The effective technology of AI is paving a way to operate several processes conveniently. Nowadays, AI-based technology is dominating the field of academic publishing industry. Intelligent techniques are being developed and executed to aid both authors and publishers to tackle issues allied to peer review, fighting plagiarism, and identifying data fabrication. In short, AI is shaping the world of Media and Publishing industry.

The implication of AI in research has bloomed tremendously with a focal point on automation of research techniques from generating a theorem to conduct experiments. In fact, with the help of AI, the researchers are now being able to solve complex problems related to biomedical sciences, drug combinations, and predicting diseases. Currently, some of the intelligent technology has already been flourished, and scientific and technical publishers are some of the current rulers of it. Beyond creating content that is customized for the audience, AI can help content creators to gain more data and relevant details for research concerning information which is tiresome to be found even by the most experienced of authors in the Publishing sector.

Editorial staffs are often responsible for controlling their own reviewer lists, which comprises finding new reviewers. But currently, the smart software can spot new potential reviewers from web sources that editors may not have ever discovered. Multiple of the current plagiarism algorithms match text verbatim. The use of synonyms or paraphrasing can disappoint these services. However, new software can locate components of whole sentences or paragraphs very much like a human mind. It can even identify and indicate papers with similar-sounding paragraphs and sentences.

In relation to wrong statistics, if scientists provide inappropriate statistical tests to their data, this can result to false conclusions. AI helps to identify the most appropriate test to achieve reliable results. In case of data fabrication, AI can often spot if data has been modified or if new data has been generated with the aim of achieving a desired outcome.

Presently, many of the publishers have gone online with user-focused digital platform. Many publishers are already using many open search technologies like Solr, ElasticSearch, LucidWorks, OpenSearch and so on. Publishing workflow includes all teams – Publishers, Editors, Production, Legal, Developers, and Marketing. Each team has their own internal workflows and processes. Replacing some of the manual processes with automation can reduce time to market. AI will increase the overall capacity to publish quality works by finding new reviewers, creating automated reviews, etc.

Speaking about the future, while machine learning and deep learning can act as a vital tool to go a long way to assist in the Media and Publishing industry, still it cannot understand human behavior to give informative answers. Now, researchers are working to develop AI for better functioning in future, where AI might have answers to that too. For the best, AI is all about making the best out of information and research on content. It aids to add context to come to a relevant decision.

The end of this decade will see the massive impact that AI is creating in the digital publishing industry. What is there today is just the beginning of it. The capabilities are vast and experience for an audience will be ever evolving.


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