Exploring Digital Humanities: Human vs. Machine Poetry & CLiC Corpus Stylistics

This blog is written as a task assigned by the head of the Department of English (MKBU), Prof. and Dr. Dilip Barad Sir. For comprehensive background reading on these concepts, click here to visit the professor's blog.

Human vs. Machine Poetry Test (My Experience)

It is incredibly hard to differentiate whether a poem is written by an AI tool or by a human, and it is certainly not as easy a task as we might assume. I recently took an online test prepared by Prof. Dilip Barad, and it turned out to be a deeply challenging task to differentiate between human ingenuity and algorithmic generation.

Apart from the classic poems I already knew by memory, I was completely in doubt as to whether a given poem was written by a machine or an actual, breathing poet. If you want to challenge your own literary instincts, you can also take the test HERE.

This is one tolll named Pengram which helps you identify whether the content is written by AI or a human being; tools like these helps you when it is hard to do it ourselves. In essence, this activity flourished me with a novel perspective on creative writing. I came to know that modern-day machines are capable enough to deceive any avid reader. What we think is written by a deeply emotional poet might actually have been synthesized by a computer. In this age of Artificial Intelligence, this blurring of lines has become the new normal.

The CLiC Activity Book & Corpus Stylistics

The CLiC web app has been developed as part of the CLiC Dickens project, which demonstrates through corpus stylistics how computer-assisted methods can be used to study literary texts. This digital tool leads to profound new insights into how readers perceive fictional characters.

In my experience, this tool is of immense value for both students and teachers. You can search for any specific keyword, motif, or phrase pertaining to your interest within the massive literary databases they provide. It makes textual analysis and research significantly more productive. I find this website incredibly resourceful for deep literary mapping.

Our group was assigned a thematic study on education, women, and governesses in the 19th century. Examples of famous literary governesses include Rebecca Sharp in Thackeray’s Vanity Fair, Jane Eyre in the novel by Charlotte Brontë, Agnes Grey in Anne Brontë’s novel, Madame de la Rougierre in Le Fanu’s Uncle Silas, the unnamed governess in Henry James’s The Turn of the Screw, Miss Wade in Dickens’s Little Dorrit, and Jane Fairfax in Jane Austen’s Emma. Given her interest in the grand country house and estate as the setting for several novels, Jane Austen’s writing frequently features the governess as a highly significant character.

I followed the instructions given in the activity book and chose Activity 15.4: Children’s feelings about governesses. Below are the results I retrieved from the site. The tool is highly specific, landing you directly at the exact passages where the word "governess" is utilized in the selected text.

Figure 1: Concordance lines generated by CLiC for the term "governess" across the corpus.

Figure 2: Textual highlight showing exact placement and context of the targeted word.

Figure 3: Exploring specific chapter views within 'The Secret Garden' using CLiC's subset filters.

Apart from this particular text, I explored various analytical features on the site and found them all to be highly specific and commendable. I also explored Voyant Tools, which stands as another remarkable feat in the application of digital tools within the humanities.

Learning Outcomes

Engaging with these digital platforms provided several concrete takeaways:

• This activity made me aware of analytical tools that I was previously completely unaware of, sparking a deep curiosity to explore more such digital tools in the future.
• I developed a profound understanding of the capabilities of artificial intelligence in creative writing by critically analyzing human-versus-machine poetry.
• I successfully utilized the Pengram tool to critically evaluate and differentiate between human-authored and AI-generated content.
• I gained technical proficiency in using the CLiC web app for corpus stylistics, specifically conducting thematic analyses of character motifs (such as the 'governess') in 19th-century literature.
• The exercise heavily enhanced my research productivity by teaching me to synthesize quantitative corpus data with qualitative literary interpretation.
• I recognized the evolving, complex challenges regarding content authenticity and authorship in the age of AI.

Works Cited

Barad, Dilip. "What If Machines Write Poems." Dilip Barad's Blog, 1 Mar. 2017, blog.dilipbarad.com/2017/03/what-if-machines-write-poems.html. Accessed 3 Aug. 2026.

Mahlberg, Micaela, et al. CLiC 2.1: Corpus Linguistics in Context. University of Birmingham and University of Nottingham, 2020. https://clic.bham.ac.uk/. Accessed 3 Aug. 2026.

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