Module 2:
This module and the reading of the works of R. S. Delemos and D. Gunter expanded my understanding of how the publishing industry is being reshaped by digital culture and technological innovation. From Delemos’ discussion of TikTok, I learned that platforms like “BookTok” have transformed book marketing into a highly interactive, community-driven process. Rather than relying solely on traditional advertising or publisher promotion, authors, especially self-published ones, can gain visibility through viral trends, reader reviews, and emotionally engaging content. This showed me that audiences now have significant influence over what becomes popular, and that authenticity and relatability are key to success in digital spaces. Gunter’s article introduced me to the growing role of artificial intelligence in scholarly publishing, which I had not previously considered in depth. I learned that AI can streamline processes such as manuscript screening, editing, and data organization, making publishing more efficient. However, it also raises important concerns about bias, accuracy, and the potential loss of human oversight. This made me reflect on the ethical responsibilities involved in using AI technologies. Overall, these readings helped me see that both social media and AI are not just tools, but powerful forces shaping how knowledge and creative work are produced, shared, and valued. They encouraged me to think more critically about the future of publishing and my own role as both a consumer and a potential content creator.
Module 3: From Wu, Ouyang, Ziegler, Stiennon, Lowe, Leike, and Christiano’s study on recursively summarising books with human feedback, I learned how advanced AI systems can be trained to perform complex, long-form tasks by breaking them into smaller parts and using human feedback to guide learning. Their recursive summarization method showed that combining human evaluation with model training can improve AI’s ability to handle tasks that are difficult for machines alone, like producing high-quality summaries of entire books. This helped me see how human-AI collaboration can enhance performance and maintain quality in generative tasks rather than relying solely on automated processes.
The article by Chubb, Reed, and Cowling made me think about how the stories we tell about AI influence public understanding and expectations. They argue that dominant narratives about AI tend to be polarized, either overly optimistic or overly dystopian, and that many important, nuanced perspectives are missing. This helped me recognize that the way AI is discussed culturally affects how society perceives its risks and opportunities, and that more inclusive, grounded stories are needed to shape informed public discourse. Exploring NovelAI gave me insight into how AI tools are already being used creatively to assist with storytelling and image generation, highlighting how generative AI can support writers and artists in creative processes. Finally, Benson’s discussion of AI in fiction and war showed how speculative narratives help us imagine potential futures of AI, but also how they may distract from more immediate, real-world challenges.
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