AI uses computer algorithms to replicate the human ability to learn and make predictions. Masayoshi Son, the founder of tech giant SoftBank and the richest man in Japan says he is devoting 97% of his “time and brain” to the scientific field of artificial intelligence. It may seem the companies he’s investing in operate in disparate industries like agriculture, transport, satellites, payments, computer chips, and eCommerce, but one common theme among all of them is artificial intelligence.
Academic publishing is right now poised to substantially leverage technologies led by artificial intelligence. With all the possible applications of AI, the industry is heavily invested in R&D to find out how publishers can improve what they do and how they get it to customers. As data is at the heart of publishing, most scientific publishers are turning into data-driven companies.
For example, a leading publisher of scientific and medical information has transformed itself into a tech company, achieved by building advanced analytics systems, utilizing big data and machine learning on top of the huge amount of data collated and published by the company in its 140-year history.
Artificial intelligence-based applications are being developed to assist authors and publishers. AI applications, with minimal human intervention, can be used in tasks like text analysis, detecting plagiarism on new manuscripts, detecting false statistical results, finding new peer reviewers, content search, semantic search, etc.
AI can bring efficiency in the processes by reducing human intervention, which also leads to reduced human bias. For example, the number of books published manually ranges from 500,000 to one million books. However, if you include self-published authors, you’re looking at close to 4 million new book titles published each year.
The amount of time required to summarize a book varies from one week for a small book to even a month for a large book. Using AI and machine learning, a text summarizer would take less than a minute to a maximum of two minutes to summarize an entire book. For publishers, these summaries will save the time and effort required to prepare massive quantities of summaries, and for their respective users, summaries will help in speeding up their buying decision process.
Further, the possibility in the future of the entire process of peer review being automated without any need for human interaction can’t be ruled out, or maybe humans can’t be entirely replaced by machines for peer reviewing, but AI could speed up the process, that’s a question for now. For example, adaptive learning — or adaptive teaching — is the delivery of custom learning experiences that address the unique needs of an individual through just-in-time feedback, pathways, and resources (rather than providing a one-size-fits-all learning experience).
It provides remediation and recommendation to the user based on the prior knowledge they have of content, the response provided in the assessment, and their confidence level. AI plays a critical role as machine learning provides publishers with the intelligence to offer adaptive learning paths to users.
Similarly, outcome-based learning is another aspect of learning that publishers can offer to their users. In this path, users or learners can take up courses with the certain goal of developing skills or gaining knowledge to achieve a certain goal.
With a rising momentum in the open access movement, one stinging issue in the traditional publishing industry has been the allegation of keeping high-profit margins. It’s not to be forgotten that profits are also made in other spheres of scientific research which might not be as visible, and the said profit provides publishers with the means to invest in new products, services, and tools for the benefit of the research community.
In traditional academic publishing, processing the articles, producing journals, and the overall survival of the organization needs monetary profit. Despite the zeal manifested in open access, traditional publishing will continue to offer value and prestige to researchers and scientists who need to publish. Traditional publishing offers high-grade editorial services, and the competitive environment in it calls for higher quality and rigorous reviewing of the published paper.
While larger organizations may be investing their money in innovations that only their size can sustain financially, smaller publishers can opt for the digital way to minimize the cost of production and delivery. Powered by digital technologies, online publishing platform helps publishers by eliminating the costs associated with producing and distributing a printed journal. Integration of AI into online publishing platforms creates a highly advanced and streamlined publishing environment with the least human interaction required.
Publishers can leverage digital publishing platforms like iPC Scholar, which provide swift and economical publishing while offering more value in terms of services. iPC Scholar allows the digital publishing of content in various forms like journals, eBooks, videos, and even learning courses. It allows publishers to diversify their content offerings, adding to sources of revenue. Actionable analytics provided in the platform gives great insights into current business and product performance which can be leveraged to offer tailored services to targeted consumers.
Having faced many challenges in recent years, academic publishing now needs to come of age; driven by data and intelligence, and the industry can fuel its own growth and reformation led by technologies like artificial intelligence. What we are seeing today is just the beginning; AI is a new-born baby (just learning to debate us humans), which in theory, will grow up to become artificial superintelligence or technological singularity, for which the limits are hard to predict.
This explosion of intelligence is a long way, but meanwhile the growth in AI will have steadily growing influence in every aspect of our lives, and all the industries. Academic publishing, the industry responsible for communication of global scientific developments including AI itself, will be at the centre of this development.
