Summary of material:
1.
After reading “The Social Contract Is Breaking, and AI Is Holding the Hammer,” I realized something I hadn’t fully understood before: some leaders are openly celebrating using AI as a way to justify layoffs, almost bragging about replacing people because machines don’t need raises or rest. It made the shift in workplace values feel a lot more real to me. To add personal context to this I have seen so many people close to me loose their jobs due to the influx of AI.

From “Behind the Curtain: A White-Collar Bloodbath,” I learned that major AI executives believe we could lose up to half of all entry-level white-collar jobs in the coming years. I knew AI would change things, but I didn’t realize just how quickly or how deeply those changes could hit professional work.

Reading “Companies Are Blaming AI for Layoffs. The Real Reason Will Piss You Off” taught me that most companies investing in AI aren’t even getting measurable returns, yet they’re still using AI as the public excuse for firing people. That surprised me, and honestly, it made me question how much of the “AI job loss” narrative is genuine versus a convenient cover.

Finally, from the BBC piece “How AI Uses Our Drinking Water,” I learned that every AI query including using chatbots like this one—uses real, drinkable water because of how data centers cool themselves. I had no idea my everyday interactions with AI had a literal water footprint, and it made the environmental cost feel much more personal.

2.
Across all four articles, I felt the same overall message emerge: AI is rapidly reshaping our world in ways that are far more disruptive, unequal, and hidden than most people realize, and each piece highlighted a different angle of that uncomfortable truth. The articles about the social contract breaking and the white-collar “bloodbath” both stressed how companies are using AI not just as a tool, but as a justification to rethink or even throw out their responsibility to workers, and I think they made that point clearly by showing how openly some leaders talk about replacing employees. The article about companies blaming AI for layoffs pushed the same idea even further, arguing that AI is often just a convenient excuse for corporate decisions driven by money, not technology, which came across as strong even if it could have used more inside evidence. And the BBC piece on AI’s water use added a surprising environmental layer, reminding me that AI has real physical costs we rarely think about. Although each article focused on a different issue, they all succeeded in showing that AI’s impact is bigger and messier than the hype suggests. Still, they also shared a common gap: none offered much in the way of solutions, leaving me aware of the problems but still wondering what can actually be done about them.

AI experiment:
Both VandeHei and Allen (2025) and Mattlar (2025) address how AI is impacting jobs, but they approach it differently. They agree that AI is being used as a justification for layoffs and is reshaping the workforce, yet they differ in emphasis: VandeHei and Allen highlight a near-future, large-scale disruption of white-collar jobs, while Mattlar focuses on how many companies are using AI as a scapegoat, even when their investments show little measurable return (Mattlar, 2025). I find Mattlar more persuasive because he combines data and practical advice for workers, making his argument grounded in current realities. The main takeaway from both articles is that AI poses real risks but also reveals how corporate narratives shape public perception; workers should adapt by learning AI tools and documenting their value, and society needs more transparency and planning around AI’s deployment (VandeHei & Allen, 2025; Mattlar, 2025).

References:
Mattlar, J. (2025). Companies are blaming AI for layoffs. The real reason will piss you off. Medium. https://medium.com/@mattlar.jari/companies-are-blaming-ai-for-layoffs-the-real-reason-will-piss-you-off-149639ce47cf

VandeHei, J., & Allen, M. (2025). Behind the curtain: A white-collar bloodbath. Axios. https://www.axios.com/2025/10/29/ai-jobs-apocalypse-navigate

In-text citation (paraphrase):
(ChatGPT, 2025)

In-text citation (direct quote):
(ChatGPT, 2025, November 20)

Reference list entry:
ChatGPT. (2025, November 20). Response to a question about AI, layoffs, and the articles by VandeHei & Allen and Mattlar. OpenAI. https://chat.openai.com

Talk about these three things:
a. What did you learn about using AI that you might not have known?

I learned that AI will be very literal. If you ask for information, you are going to get overloaded with it. Is it all credible? Now this is what I thought, and I learned a long way. AI can overload you with information even after you have completed the research. My take on using AI is to slow down, think, and then use the tool to add extra detail, but not for all details.

b. What did you think about the responses you received? Good, weird, helpful, annoying,
incorrect, or whatever.

I found it to be overwhelming. A lot of information was provided. I had to use the tool to reduce what was given because, if I hadn’t, there would have been multiple points for just one.

c. What was your emotional reaction to using this tool?

I had no emotional reaction using the tool.

d. Where do you think we are headed and how to we manage it?

AI can be used in significant ways, but if people rely on it as the only way of life, we are headed towards lazy times, in which people will use less of their brains and begin to depend on AI. Especially the kids who are growing up to be new doctors, nurses, lawyers, and these are scary thoughts.