In the exploration of using a digital program such as Voyant Tools and other digital text analysis tools for work in the Digital Humanities, it is first and foremost imperative to recognize the fact that these are tools. They are helpful tools but they are ultimately just tools. These digital analysis tools and programs do not do the work on behalf of digital historians. Artificial Intelligence (AI) has developed exponentially over recent decades but has not (yet) reached a point for which it can replicate the complex cognitive abilities and human brain functioning required to complete the idea of traditional humanist scholarship. This can only be done by the human mind.
These text analysis tools allows historians to quickly analyze patterns in large bodies of text. The use of these tools has sparked great debate in the digital humanities as to whether its effects are more helpful or harmful. There is something to be said about the aesthetic and the experience of being immersed in a specific geographical location and physically working through texts (e.g. physical archives). A digital text analysis cannot replicate this effect nor can it guarantee maximum effectiveness. By narrowing the search through specific word identification/recognition, there is the potential for valid, important, and/or beneficial information to be lost/cut from the search. However, some of the benefits of this program can drastically improve the efficiency of historical research and analysis. These tools provide opportunities that eliminates large amounts of time consuming and tedious sorting work but cutting out the fluff (any aspect of the text that is not related to the topic of research). This may be an asset to a historian who favours efficiency but is disliked by a historian who favours experience.
Without digital text analysis tools, many historians would spend much of their valuable research time “sorting”; something easily done through digital programming. These tools also allow historians to access digitized quantifiable (often statistical) comparisons within and between texts. With the quantifiable (objective) work being performed through digital means, historians can focus more of their time and energy on the qualitative (subjective) analysis that is (as it currently exists) outside of the reach of digital programming and artificial intelligence capabilities.
These types of digital text analysis tools challenges and changes the progression of how information is acquired, processed and used. With respects to traditional historical skills this is not a new phenomenon, just a new type of technology. In more primitive times, before the introduction of print and written documentation, information was acquired processed, used, and transmitted solely through means of oral communications. When print was introduced, this drastically changed the game and information was now able to be read instead of heard. The introduction of written records negatively impacted the human capacity for memory. We see this cycle repeating itself with the introduction to more digital analysis tools and the implications it may have on human capacity for attention. This kind of analysis changes the game with respects to traditional historical reading skills. Just like the skill for hearing and oral communication was not completely lost with the introduction of print, the skill for reading and attention is not completely lost with the introduction of digital analysis. Digital text analysis tools may be a helpful aid, but the paired need for human scholarship helps to support why digital text analysis tools are beneficial to the work of digital historians and the digital humanities as a whole.