Carry on Reading

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“It’s not just that we are somehow morally weaker for using AI to do our work for us, but we will be the lesser for it. On a large human scale, human knowledge will be lesser for it; we are not going to be creating new things because large language models only know about the stuff that is already out there.” Sophie Scott, BBC ‘A Good Read’ podcast. 

This quote was a reaction to people using AI to summarise texts they did not want to read or did not have time to read. It made me think of my earlier blog, Print or digital: that is the question, which I wrote in response to Pat Thomson’s thought-provoking post, “About the unread.” At the time, I was interested in access, format, and abundance, but this quote led me to reflect upon not how we read, but whether we persist in reading at all. 

The issue: Are we justified in stopping reading 

When I was younger, books were expensive, less available, and harder to replace. If I started a book, I tended to finish it, sometimes out of stubbornness, sometimes out of guilt, and sometimes because there was simply nothing else to read. Persevering with a text I did not immediately enjoy was normal, and I was usually able to enjoy what I was reading for some aspect or another anyway. However, as I get older, time has become more precious, and the vast abundance of texts, digital articles, books, reports, and novels means that not finishing feels less like failure and more like selectivity. In fact, when a text does not engage me, I increasingly feel entitled to stop and ask AI to summarise it for me. These summaries are efficient, pragmatic and time-saving. However, Scott argues that creativity is born from texts we struggle with, and that if we bypass that conflict, we lose the most essential part of what makes us human: our personal, unique interpretation. 

Solution 1: AI as a legitimate tool for selective survival 

Firstly, should we accept AI summaries as a rational adaptation to contemporary academic life? Reading everything in depth is no longer feasible, and strategic skimming has long been part of scholarly practice. In this sense, AI simply accelerates an already familiar behaviour, as noted by Baron (2015), who argues that skimming and summarising have always been part of academic practice. From this perspective, AI tools allow readers to manage overload and prioritise what deserves deeper attention. For scholars balancing teaching, research, administration, and care, AI can function as a filter, not a replacement for reading, but a way of deciding what is worth reading and what is not. In this way, and used critically and transparently, AI could help us survive abundance without drowning in it. 

Response 2: Reading as creative misinterpretation 

On the other hand, Scott argues that creativity does not emerge from efficiency but from conflict. She points out that reading is not a neutral act of extraction, but it is interpretative, emotional, and often messy. Indeed, when we misunderstand a text, we read something into it that the author might not have intended. This misinterpretation can be considered creativity (Wolf, 2018). Therefore, when we struggle with unappealing or difficult texts, we are not failing but creating meaning. Additionally, Scott says that when AI summarises a text for us, it not only removes productive misreading but also delivers clarity without confusion, coherence without resistance, and excludes the reader’s imaginative labour. It is this labour where new ideas, connections, and even writing voices are formed.  

A question to readers 

So, my question to you is, in an age where texts are endless and time is not, how do we decide what deserves to be read and what can be safely summarised? And more provocatively, what kind of reader, writer, and thinker are you? 

Blog written by Dr Lesley Fearn

 

Dr Lesley June Fearn is a secondary school English teacher in southern Italy. She is also an affiliate researcher at the Open University’s (UK) Faculty of Well-being, Education, and Language Studies (WELS), where her research centres on linguistics and sociocultural theory. 

Generative AI: Friend or Foe? 

image by Emiliano Vittoriosi on unspalsh

During a meeting in July of this year, we, the editing team of this blog, discussed the topic of generative AI in education. We all had completely different perspectives. Jane and Azumah were wary. Jonathon was interested, but I loved it because it made my professional life much easier (I recently read that other teachers felt the same (BBC News). So, we decided to each write a blog post to report our viewpoints and to start a conversation. So, six months after our original discussion, I would like to add to and respond to Jonathon and Jane’s blog questions: ‘What is all the fuss about?’ (Hughes, 2023) and ‘How far is AI plagiarism?’ (Cobb, 2023). 

How far is AI plagiarism? 

We cannot possibly know where generative AI models such as ChatCPT are getting their information from (Pride, 2023). However, as academics, we must acknowledge the information we obtain from any source. Most guidelines, including the OU, advise scholars to cite and reference the material they use from generative AI. Additionally, various AI plagiarism detectors, such as AI Content Detector, can help teachers detect the use of AI tools in assignments or tests, but they are often inefficient. On the other hand, plagiarism detectors are not always necessary because research has shown that students choose not to use AI tools in essay writing because they not only waste a lot of time producing good prompts, but they waste even more time reworking the essay, making the language neutral and believable (Alexander et al., 2023).  

What is all the fuss about? 

Although generative AI models afford considerable advantages to the world of education for English-speaking users, non-English users are underprovided. This fact could potentially widen the education gap. Therefore, the United Nations Educational, Scientific and Cultural Organization (UNESCO) (Fengchun & Wayne, 2023) urges responsible and fair access to AI technology to limit educational divides within and among countries. Moreover, many communities lack the resources and infrastructure to access AI, resulting in increased AI data wealth over the past few years, primarily concentrated in the global north. This growing divide could significantly disadvantage data-poor communities, who ‘have been further excluded and put at long-term risk of being colonised by the standards embedded in the GPT models.’ (Fengchun & Wayne, 2023, p.14). Therefore, we must know how these powerful tools can benefit our professional practices. Additionally, guidance and training are needed regarding how AI uses our data and its effects on other social and cultural communities.  

Using AI  

My respect for AI developed from how much it relieved my workload. For example, I am an English teacher working in Italy, and I often use ChatCPT to correct my writing in Italian, which is not my mother tongue. Before I discovered this tool, I would have to ask a friend to check my writing, but ChatCPT does it in a split second and helps language learning. However, generative AI has no concept of social and cultural contexts, so the user needs to keep that in mind. Nevertheless, Kasneci et al. (2023) claim that generative AI can revolutionise language learning and teaching. Apps such as Memrise already offer one-to-one conversation lessons with ‘virtual’ teachers. However, there is still much work to be done. 

 Zhai (2022) points out that the language ability of AI far exceeds a human being’s proficiency in a foreign language. But AI models cannot yet think critically or be creative in the same way as humans. So, to take advantage of generative AI in the classroom, we need to improve our students’ critical thinking and creativity skills. Until now, the attraction for AI has been mainly superficial, but there is a growing awareness of some of the complexities involved. 

In conclusion, generative AI tools might not be as damaging to our practices as initially thought, but they could be harmful on a much deeper level. We need to rethink our curricula as educators to favour creativity and raise awareness of how the data we feed into AI models is used. In light of these reflections, if you are a PG student, how aware are you of generative AI tools? Do you use any in your professional practice, and what advantages do they bring? 

by Lesley Fearn

Dr Lesley June Fearn is a secondary school English teacher in southern Italy. She is also an affiliate researcher at the Open University’s (UK) Faculty of Well-being, Education, and Language Studies (WELS), where her research centres on linguistics and sociocultural theory.