How AI Skills Are Revolutionizing Research

Gone are the days when searching for information involved rummaging through stacks of books or spending hours sifting through library catalogs.

In fact, even using familiar search engines has been revolutionized thanks to artificial intelligence. 

This transformation has made expertise in AI, particularly machine learning, a hot commodity in the job market, which we can see as more and more job seekers proactively highlight their AI, natural language processing, and machine learning skills on their resumes and LinkedIn profiles.

Many companies have already started to implement AI to make any kind of search quicker, more accurate, and efficient. While traditional search engines relied solely on matching keywords to page rankings, today's AI-powered algorithms go even further. They consider the context of your query, understand the intent, and even have the power to extract information from images. 

But what about using AI within research? In this article, we'll look at how artificial intelligence has changed the research process and made it more accurate and straightforward than ever before.

The Evolution of Search Algorithms

Traditional search engines such as Google and Yahoo typically relied on matching keywords to find the information you need. We've been searching for information this way for two decades now, and, while this approach works (to a certain degree), it’s also very limited due to a lack of understanding of the search query.

Artificial intelligence algorithms solve this problem. Thanks to AI’s ability to understand the context of searches, more accurate results can be obtained. Already, Google and Bing are beginning to implement AI into their search engines so that they can offer more relevant results — even if the query was very vague. 

For example, a typical search on Google involved typing your query in the search bar and getting a list of results. You would need to skim over each result, consider if it’s useful, and click on the links to be taken to those pages. Then you would have to read over each page to find your answer. 

Nowadays, the process is much simpler. All you need to do is open Google Gemini, ask your question, and get a detailed answer along with links to useful sources and additional references that it used when formulating the answer. 

What Are AI Skills?

While artificial intelligence has greatly simplified the research process, effectively harnessing its potential requires users to have certain AI skills. 

For example, some of the most important AI skills include how to formulate precise queries, interpret AI-generated results, and validate information against reliable sources. 

Other nice-to-have skills include using and finding prompts, figuring out which AI tools are best for different purposes (i.e. DALL-E for images, Jasper for writing text), and identifying any potential biases in AI outputs. 

As AI continues to evolve, so too will the skills needed to use it successfully. Let’s take a look at using AI for research… 

AI for Academic Research

One aspect of being a scholar or working in academia is spending a lot of time on research. Thankfully, artificial intelligence has taken some of the hard work out of the process. 

For example Google Scholar is a useful tool when writing research papers. Although it was launched in 2004, it was recently infused with artificial intelligence capabilities to understand context in search queries and find the most relevant results.

There's also Scite, which is convenient for going through large texts of academic information. Just type in your question and it’ll find the relevant information, rank it by context, and compose a concise answer. The main difference between Scite and ChatGPT is that the former will not only answer your question, but also list where it got the information from and leave links to relevant publications.

Last but not least, AI can help with writing citations and organizing sources. R Discovery is an AI-powered research assistant designed to help users find scholar articles, case studies, peer-reviewed journals, and more. Even better, it sends personalized recommendations so that you won’t miss out on the latest developments in your field.

Smarter Virtual Assistants

How often have you used the likes of Siri, Google Assistant, or Alexa to quickly search for information, find a recipe, check the weather, call your friends, or add an event to your calendar? Voice assistants have practically become part of our daily lives and are a great tool for basic tasks — but now, they’re going one step further. 

Until recently, the functionality of assistants was very limited and could not compare with independent search for information, but with the advent of artificial intelligence, everything has changed.

Nowadays, voice assistants use artificial intelligence algorithms to search for information and provide more accurate and relevant answers. Researchers can take this one step further by leveraging voice assistants as research collaborators, capable of assisting in literature reviews, data collection, experiment design, and even the analysis and interpretation of results.

Enhanced Image Searching

In the early years of the internet, we searched for information by relying only on text queries — but, with the advent of artificial intelligence, this too has changed.

Thanks to sophisticated AI algorithms, image search has brought in a new era of visual information search. Researchers can now upload images and uncover hidden patterns, identify rare species, or analyze complex visual data with speed and accuracy. This can be used in microscopy and genomics, as well as when analyzing diagnostic images such as X-rays, MRIs and CT scans.