Technology has always played a major role in scientific breakthroughs, and artificial intelligence is expected to take it a step further and raise the bar of scientific research, to new levels. This technology offers the solution to all the complex research challenges scientists have had to encounter in the past and especially in the present. Now, they can address such challenges much more effectively and timely than humans. In a digital age where a universe of information is present, with most of it residing in cyberspace, humans don’t have to cope with the task of manually analyzing the vast amounts of available data to spot patterns, detect anomalies and derive useful insights. Instead, AI tools are being used to make such tasks easy and efficient.
Giovanni Colavizza, a data scientist doing research at the Alan Turing Institute in London on full-text analysis of scholarly publications, wrote in the International Journal of Science that modern AI tools are equipped with “state-of-the-art information retrieving” capabilities. The article states that a plethora of scientific literature is available on the internet with 1 million new research papers being published every year. Given such an incredible publication pace, it’s almost impossible for scientists to sort through, analyze and assess vast quantities of research papers to test different hypothesis. This problem can be solved with cutting edge tech tools powered by Artificial Intelligence that can help scientists extract specific content as per requirement as they possess the ability to filter, rank and group search results. An example of such a technology is Iris.ai, which acts as a research assistant to help users map out and acquire relevant scientific knowledge.
AI powered tools such as Iris possesses such incredible storage and processing capacity that “she can read the transcripts of all TED talks to date in no time” and here is “how exactly Iris.ai works.” In an article “5 ways Artificial Intelligence will Disrupt Science” ai powered tools such as Iris are specially designed with the astounding capability “to map out the science around a TED talk” as it can “analyze(s) the scripts of the talks. Using Natural Language Processing algorithms, such tools can mine(…) open-access academic literature to find key papers related to the talk’s content” and elegantly visualize the groups of related research papers. For research scientists this means entering a 300–500 word description of their research topic or just the url of an existing paper for Iris to produce a map of 1000’s of matching documents as stated in “How AI Technology Can Tame the Scientific Literature.”
Iris’s cofounder Mario Ritola mentioned that their team’s future aim is to turn Iris from a research assistant to a real scientist. This means that it can generate a hypothesis by itself after analyzing and going through existing scientific papers, collect data by running experiments and simulations and write new papers based on the outcome. She also mentions about “democratizing access to scientific knowledge” and making it publicly available through the use of AI assistants that can map out relevant information by “leveraging AI.”
In fact a team at IBM has already achieved what Ms. Ritola is envisioning. They state that they have developed AI algorithms capable of making new scientific discoveries and works by bringing together text mining, visualization and analytics in order to extract facts and propose new hypotheses that are likely to be true. What this might mean is that in the near future, scientific research might get automated freeing up scientists to focus on more important tasks.
Artificial Intelligence is helping the scientific community in academic publishing as well. It can assist in peer reviews, searching and extracting published content as well as in detecting plagiarism and spotting data fabrication as mentioned in “Artificial Intelligence in Research and Publishing”. AI powered tools are also useful in scientific communication as they are not prone to the same bias as humans.
Apart from academia, Artificial Intelligence is also making an impact on scientific journalism. Bertrand Pecquerie, CEO of the Global Editors Network, says that “AI will be the catalyst of the third disruption in journalism, potentially changing the way we produce and consume news.” In today’s world “computers can tell stories without humans. News-writing bots like the LA Times’ Quakebot or Washington Post’s Heliograph are able to come up with larger amounts of news stories than humans and at a much quicker pace. They are likely to sweep into newsrooms and take over much of the media work — in the next few years.
A fascinating fact is that these bots can even mimic the voice of your famous writer while writing science papers and articles. Furthermore these bots are equipped with the capability that reporters and editors take decades to develop, i.e. “predict the most important research papers to report on, and the parts of those papers that should be focused on to find newsworthy issues.” AI can overcome the challenges and problems often faced by science writers with limited experience with the task.
We are entering a new age of scientific research where mundane research tasks will be carried out by machines letting scientists focus on bigger questions of research and development. Thus, artificial intelligence is promising to profoundly reshape scientific research and exploration. Not only will AI lead to innovations, discoveries and scientific advancements but will also speed up the research process.