Efforts toward building research capacity tend to focus on developing scientists’ technical competencies through training. Therefore, to help advance scientific research, it is important to facilitate knowledge creation by building infrastructure powered by new technologies.
We have reached a point where Artificial Intelligence (AI) can significantly augment our intelligence and help us achieve better outputs at a faster pace. There is no area where AI has not been proven useful. With an eye on enhancing scientific research and upgrading technological capabilities, research capacity building has been adopted as a tool for development, with close to $1.5 trillion spent on academic research by over 8 million active researchers.To supplement these efforts, the right AI-powered tools can make a significant difference in how research is conducted and how quickly results are obtained.
It took the COVID-19 pandemic for government organisations, NGOs, and the public to understand the need for speed and accuracy in research. When millions of lives are at stake, the slow pace of research in the race to find an antiviral drug or vaccine strikes especially hard.
However, in research, where only a few landmark achievements in academic research are celebrated, many steps and processes are easily forgotten. Sometimes, these efforts take months before any results are achieved; more often than not, the results aren’t revolutionary or don’t directly contribute to the betterment of society.
Governments and corporations are waking up to the need for faster research. Researchers currently spend close to four hours a week searching through hundreds of articles. About five hours are invested in reading these articles, with half of the articles turning out to be irrelevant to the specific field of research. Technology, especially AI, can come to the rescue. There are many tools that help researchers narrow down their reading and discover the relevant research much faster. These are powered by natural language processing and search based on machine learning.
During the actual research stage, AI open-source tools like Python, R, Pandas, and Spark, as well as proprietary AI tools like Mathematica, Matlab, and SAS, can be very useful in statistical machine learning. A number of research labs are making use of advanced AI concepts such as computer vision, robotic arms, IOT, and speech and audio to assist in gathering data and running experiments based on various hypotheses; collecting, analysing, and illustrating research output; and arriving at conclusions.
Finally, for researchers, the publication and dissemination of their research is the final—and most important—stage. This stage is time-consuming and tedious, yet critical. It determines how and to what extent the research will reach the right audience. There are many AI tools that can be used by researchers to write manuscripts, correct grammar and syntax, and format as per target journal standards, in addition to automated solutions for styling figures, tables, captions, and citations.
Since its inception, CACTUS has been partnering with researchers to assist them in their research journey. Enabling researchers and innovators to find analogous concepts and novel ideas from different industries and fields has been our constant endeavour. The organisation has also entered the AI and deep-learning space to develop innovative products for publishers as well as business and tech solutions for stakeholders in the research landscape. With the aim of putting the researcher at the centre of research, we have rolled out a powerful initiative called R. Having developed several AI-powered tools that simplify the life of the researcher and helps them focus on actual research, we believe it won’t be long before AI is fully integrated in the researcher ecosystem.
The author is Nishchay Shah, Chief Technology Officer, Cactus Communications.
Article originally published by TechGig on https://content.techgig.com/implementation-of-technology-in-advancing-scientific-research/articleshow/77958300.cms (September 7, 2020)
