As the divisions between academic disciplines become more and more blurred, within individual fields, we are seeing an increase in the use of research tools and methodologies that would not traditionally be associated with that field. This happens to be the case for many disciplines that have been traditionally grounded in the humanities.

An example of this would be the many disciplines that have been affected by the quest for artificial intelligence. Since at its core, work in AI necessarily spans multiple academic areas, it is not surprising in itself that it would serve as a breeding ground for cross-disciplinary research processes. The study of vector semantics is a good example of this. Vector semantics involves the use of mathematical and statistical modelling in order to represent the meaning of words. The motivation comes from an issue in natural language processing known as “word-sense disambiguation.” This is the problem that arises with sentences such as “he hit the ball with a bat”: a human reader would be able to use context and general knowledge of the world to make the inference that the “bat” being used is likely a piece of sporting equipment and not a flying mammal; the issue arises in ensuring that a computer also understands this. Vector semantics aims to be able to disambiguate the word “bat” the same way humans do — by considering the word in context.  

The key idea is to link the meaning of words to the environments they appear in. In this model, words are stored as vectors in a vector space, and are situated near other words that they share a common theme with and frequently appear next to. Not only does this help a computer to better understand the meanings of words using context, but it also allows for a more efficient way of finding related words for any given search term.

A more industry-driven approach to combining linguistics with statistical modelling is seen in sentiment analysis. This tool is used by brands to gauge consumer “sentiment” towards their product or service. Since consumers now can express their opinion not only through online reviews, but also via many different forms of social media, the sheer volume of data available to a marketing analyst may end up becoming impossible to process manually. Sentiment analysis softwares are able to analyse data to provide the user with the key information that they require. For example, it could tag every review with either a “positive”, “negative”, or “neutral” label depending on what it determined the general tone of the review to be. The number of reviews corresponding to each label can then be tallied, and this numerical data then becomes much easier for a human to process quickly.

Automatic speech recognition (ASR) is a technological tool that is used primarily in linguistic research.  Specifically, it is invaluable in language documentation and revitalization. This is a subfield of linguistics which focuses on documenting threatened languages in efforts to revive them. Since these languages tend to have fewer speakers, it often takes countless hours to process and transcribe oral data manually. Though ASR tools are not 100% accurate, they help speed up the documentation process significantly.

Students who are interested in studying this merge of humanities and technology have the option of pursuing the digital humanities minor that is currently being offered by Woodsworth College. As described on the program website, “Digital humanities (DH) is a discipline at the intersections of the humanities with computing. DH studies human culture— art, literature, history, geography, religion — through computational tools and methodologies; and, in turn, DH studies the digital through humanist lenses. Digital humanists can study social media phenomena or medieval manuscript archives; computationally analyze thousands of newspaper articles to trace economic developments; construct video games to study literary narratives; or resurrect historical cities through digital maps and virtual reality exhibits.” Along with certain required courses, students can choose from a range of cross-listed courses from disciplines such as book and media studies, cinema studies, computer science, English, geography, history and philosophy of science and theology, medieval studies, music, religion, and urban studies. In addition, students complete a capstone experience, in which they have the opportunity to contribute to a faculty research project or conduct their own original research.

As technology progresses and becomes integral to fields that were previously considered to be isolated from advancement, it serves as a reminder that the use of tools not native to their field can hugely benefit every academic discipline.