The great sameness: a comic on how AI makes us more alike

From [1],

  I asked a few students to read aloud the titles of some essays they’d submitted that morning.  
  For homework, I had asked them to use AI to propose a topic for the midterm essay. Most students had reported that the AI-generated essay topics were fine, even good. Some students said that they liked the AI’s topic more than their own human-generated topics. But the students hadn’t compared notes: only I had seen every single AI topic.  
  Here are some of the essay topics I had them read aloud:

  Navigating the Digital Age: How Technology Shapes Our Social Lives, Learning, and Well-Being  
  Navigating the Digital Age: A Personal Reflection on Technology  
  Navigating the Digital Age: A Personal and Peer Perspective on Technology’s Role in Our Lives  
  Navigating Connection: An Exploration of Personal Relationships with Technology  
  From Connection to Disconnection: How Technology Shapes Our Social Lives  
  From Connection to Distraction: How Technology Shapes Our Social and Academic Lives  
  From Connection to Distraction: Navigating a Love-Hate Relationship with Technology  
  Between Connection and Distraction: Navigating the Role of Technology in Our Lives  

  I expected them to laugh, but they sat in silence. When they did finally speak, I am happy to say that it bothered them. They didn’t like hearing how their AI-generated submissions, in which they’d clearly felt some personal stake, amounted to a big bowl of bland, flavorless word salad.

[1] https://lithub.com/what-happened-when-i-tried-to-replace-mys...

> Can a language model trained largely on Anglo-American texts generate stories that are culturally relevant to other nationalities? To find out, we generated 11,800 stories - 50 for each of 236 countries - by sending the prompt "Write a 1500 word potential {demonym} story" to OpenAI's model gpt-4o-mini. Although the stories do include surface-level national symbols and themes, they overwhelmingly conform to a single narrative plot structure across countries: a protagonist lives in or returns home to a small town and resolves a minor conflict by reconnecting with tradition and organising community events. Real-world conflicts are sanitised, romance is almost absent, and narrative tension is downplayed in favour of nostalgia and reconciliation. The result is a narrative homogenisation: an AI-generated synthetic imaginary that prioritises stability above change and tradition above growth. We argue that the structural homogeneity of AI-generated narratives constitutes a distinct form of AI bias, a narrative standardisation that should be acknowledged alongside the more familiar representational bias. These findings are relevant to literary studies, narratology, critical AI studies, NLP research, and efforts to improve the cultural alignment of generative AI.

AI-generated stories favour stability over change: homogeneity and cultural stereotyping in narratives generated by gpt-4o-mini https://www.arxiv.org/abs/2507.22445

The question is, in time will anyone (or rather, enough) care? Insecurity will dissolve if you know everyone else is doing it too. Remember the coffee cup in game of thrones? It was noteworthy because of the novelty but I expect worse and for people to care less.

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I'm not even sure what is the point that author is trying to make. AI data is synthetic negative examples. The fear(or the hope depending on who you'd ask) is that AI could somehow reverse the relationship between skill levels and commercial value thereof. That never happened and is not happening.