This blog presents my reflections on a Digital Humanities Lab Activity assigned by Prof. (Dr.) Dilip Barad Sir, Department of English, Maharaja Krishnakumarsinhji Bhavnagar University (MKBU).
👉The blog is divided into three sections. The first section explores the comparative analysis of human-written and AI-generated poetry, examining their differences in creativity, emotion, language, and literary expression.
👉The second section documents the CLIC (Computer-Assisted Language Instruction and Communication) Activity assigned as part of the Digital Humanities Lab, where I reflect on the learning process, digital tools, and key insights gained through the practical exercises.
👉Section 3 Voyant Tools Experience explores my analysis of Kazuo Ishiguro’s An Artist of the Floating World using Voyant Tools and its features such as Cirrus, Trends, Contexts, and Bubblelines.
I have divided this blog into 3 sections
👉Section 1: Human vs. Machine Poetry
👉Section 2: Dickens Project and The CLiC Activity Book
👉Section 3 : Voyant Tools Experience
Section 1: Human vs. Machine Poetry
The Poetry Turing Test: A Challenge to Literary Judgment
The central experiment of the lecture adapts Alan Turing's test for artificial intelligence into the domain of poetry. Participants are asked to identify whether anonymous poems have been written by humans or computers, yet their judgments repeatedly prove unreliable. What initially appears to be a test of machine intelligence gradually becomes a test of human literary perception. The experiment reveals that readers often associate coherence, emotional tone, or stylistic familiarity with human authorship while dismissing unconventional language as mechanical.
However, when experimental poetry by writers such as Gertrude Stein is mistaken for machine-generated language, these assumptions collapse. The lecture therefore exposes the instability of literary judgment by demonstrating that readers evaluate texts according to preconceived expectations rather than objective standards. In this sense, the Poetry Turing Test is less an assessment of artificial intelligence than an exploration of the interpretative habits through which readers construct ideas of creativity and humanness.
Creativity Beyond Pattern Recognition
One of the most significant issues raised by the lecture concerns the nature of creativity itself. The speaker explains that algorithms such as Racter and Ray Kurzweil's RKCP analyse linguistic structures from existing texts and generate new compositions by reproducing statistical patterns. Although these poems occasionally persuade readers that they are human creations, the lecture carefully notes that the algorithms possess no understanding of the meanings they manipulate. Their operation depends entirely upon recognising relationships between words rather than experiencing emotions or comprehending ideas. This distinction invites a deeper philosophical question: should creativity be defined by the originality of the final product or by the conscious experience behind its production? From my perspective as a student of English Literature, genuine literary creativity cannot be reduced to successful imitation.
Human poetry emerges from historical memory, emotional experience, ethical reflection, and imaginative consciousness dimensions that remain inaccessible to computational systems. Artificial intelligence may simulate the external features of poetic language with remarkable accuracy, but simulation should not be mistaken for authentic artistic creation.
Rethinking Authorship in the Digital Age
The lecture also challenges conventional notions of authorship by demonstrating that readers often appreciate poems without knowing who created them. This observation resonates strongly with Roland Barthes' influential essay The Death of the Author, in which he argues that the meaning of a literary work should not depend upon the identity or intentions of its creator. During the Poetry Turing Test, participants respond solely to the language of the poems, unknowingly placing Barthes' theoretical argument into practice. Yet artificial intelligence introduces a new dimension to this debate. Whereas Barthes sought to liberate interpretation from the authority of the author, AI raises the possibility of texts being produced without any conscious author at all.
This development complicates traditional literary criticism by forcing scholars to reconsider whether intentionality remains essential to literary meaning. The lecture therefore illustrates that Digital Humanities does not merely provide new technological tools; it fundamentally transforms the theoretical questions that literary studies must address.
Artificial Intelligence as a Reflection of Human Culture
Perhaps the most compelling argument in the lecture is the metaphor of artificial intelligence as a mirror rather than an independent creator. The speaker argues that AI reflects whatever literary tradition humans choose to provide as training material. When algorithms analyse the poetry of Emily Dickinson, William Blake, or Gertrude Stein, they do not invent new literary worlds but reproduce the stylistic patterns already present within those texts. Consequently, AI should not be understood as replacing human creativity but as extending and reflecting it.
This perspective shifts the focus away from technological achievement and towards human cultural production itself. The lecture suggests that every AI-generated poem is ultimately rooted in human language, human history, and human imagination. Machines therefore reveal as much about humanity as they do about computation, functioning less as autonomous artists than as sophisticated mirrors that reproduce our own linguistic and cultural practices.
👉As part of this task, we were required to complete two online tests on AI-generated and human-written poetry. The objective was to identify whether each poem was written by a human or a computer based on its language, style, and emotions.
Click below for Test Link
Test:1
Human Or Machine: Can You Tell Who Wrote These Poems?
Test:2
Poem Written by a human or a computer?
Here are my result from Test 1: Human or Machine: Can You Tell Who Wrote These Poems?
Section 3 : Voyant Tools Experience
Click Here for Link : Voyant Tools
For this activity, I explored An Artist of the Floating World by Kazuo Ishiguro using Voyant Tools. The tool generated several responses that helped me examine the novel through a digital and quantitative approach. I explored different features, including Cirrus (word cloud), TermsBerry, Trends, Contexts, Bubblelines, and other visualisations, to observe the frequency, distribution, relationships, and patterns of words throughout the text. These visual representations provided a different perspective on the novel and helped me understand how frequently certain words appear and how their usage changes across the text. The experience demonstrated how digital tools can complement close reading by revealing textual patterns that may not be immediately noticeable through conventional reading.
My First Experience with Voyant Tools
My first experience with Voyant Tools was both new and interesting because I had never analysed a literary text through a digital tool before. For this activity, I Chose Kazuo Ishiguro’s An Artist of the Floating World and explored the different features available in Voyant Tools. At first, the number of graphs, visualisations, and unfamiliar options was slightly confusing, but as I explored them one by one, I gradually understood how they worked. I experimented with features such as Cirrus, Trends, Contexts, Bubblelines, and other visualisations, and each of them presented the text in a different way.
Through these features, I could see which words appeared frequently, how particular words were distributed throughout the novel, and the contexts in which they were used. The visual representations, especially the word cloud, graphs, bubbles, and lines, made some textual patterns easier to notice than they would have been through ordinary reading. At the same time, I realised that the tool does not automatically provide a literary interpretation; it gives us data and patterns, which we then have to interpret critically. Therefore, my first experience with Voyant Tools helped me understand how digital text analysis can work alongside close reading, offering another perspective on a literary text and making me more aware of the relationship between technology, language, and literary studies.
Overall, although using Voyant Tools was a little difficult for me at first, the experience became more understandable as I explored its features. It introduced me to a different way of reading and analysing literature and helped me understand how digital tools can complement traditional close reading.
Overall Learning Outcome: My Understanding of Digital Humanities
1. From Traditional Reading to Digital Reading
This Digital Humanities Lab activity changed my understanding of how literature can be studied in the digital age. I learned that literary texts can be examined not only through close reading and interpretation, but also through computation, corpus analysis, visualisation, and digital data. Digital Humanities therefore creates an interaction between human interpretation and computational methods.
2. Understanding Literature through Different Perspectives
The three sections of this blog helped me understand literature from different perspectives. The Human vs. Machine Poetry activity made me question my assumptions about creativity, authorship, and AI. CLiC introduced me to corpus-based analysis, while Voyant Tools helped me examine word frequency, distribution, context, and visual patterns. These activities showed me how digital methods can reveal aspects of texts that may not be immediately visible through conventional reading.
3. Learning to Read Data as Literary Evidence
One important learning outcome was understanding that digital data can become a form of literary evidence. The CLiC “chin” activity showed how a single word can be studied across different literary texts to explore body language and characterisation. Similarly, Voyant Tools helped me identify recurring words and patterns in An Artist of the Floating World. I learned that such patterns can help researchers develop new questions about language, character, and meaning.
4. The Importance of Human Interpretation
These activities also taught me that digital tools cannot replace human interpretation. CLiC and Voyant Tools can identify patterns, but the researcher must interpret their literary significance through context and critical thinking. The visualisations provide information, while the researcher gives that information meaning. Thus, Digital Humanities works best when computational analysis and humanistic interpretation complement each other.
5. Developing Digital and Critical Skills
These activities developed my practical skills as a literature student. I learned to work with corpora, concordances, keyword searches, textual patterns, and visualisations. At first, some tools, especially Voyant Tools, were difficult and unfamiliar. However, gradually I became more comfortable using them and developed digital literacy, critical thinking, observation, and analytical skills.
6. Rethinking the Role of Technology in Literary Studies
The activities made me think critically about the relationship between technology and literature. The poetry activity raised questions about AI and creativity, while CLiC and Voyant showed how computers can help identify linguistic patterns. I learned that technology does not simply replace traditional literary scholarship; rather, it can expand the possibilities of literary research while human interpretation remains essential.
7. My Overall Understanding of Digital Humanities
Overall, this activity helped me understand Digital Humanities as an interdisciplinary field connecting literature, technology, data, and human interpretation. I learned to move between close reading and computational analysis and to see texts through both individual details and larger patterns. Most importantly, I realised that digital tools do not provide ready-made interpretations; they offer new ways of seeing texts and asking literary questions. This experience has expanded my understanding of literary research and strengthened my confidence in using digital methods as an English Literature student.
References:
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 16 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 16 Aug. 2026.
No comments:
Post a Comment