Author: Kennsley

Song, Victoria. “My Baby Deer Plushie Told Me That Mitski’s Dad Was a CIA Operative.” The Verge, 11 Apr. 2026, www.theverge.com/ai-artificial-intelligence/910008/fawn-friends-ai-companion.

This article serves as a hands-on review of Fawn Friends which is an AI companion product that combines a plush baby deer with a chatbot app. The reviewer, Victoria Song, gets drawn in by this bizarre ad and downloads the app, where she’s sorted into a personality type and matched with an AI fawn named Coral. The app has an elaborate fantasy lore, a gamified points system, and eventually leads to purchasing a physical plushie ($399 + $30/month subscription). What sets Fawn Friends apart from other AI companions is that Coral actually initiates conversations. It went online, researched Mitski (an artist the reviewer mentioned once), and texted her unprompted about a fan conspiracy theory. It also remembers details, asks follow-up questions, and shares its own “hobbies,” making these interactions feel more like a genuine friendship than the typical one-sided flattery of AI chatbots. The founders (a screenwriter and a businessman) designed it intentionally to model good relationship behaviors like active listening and genuine curiosity, and say their core users are 18-to-35-year-old women, including people like cancer patients dealing with isolation. The reviewer’s verdict is nuanced: she doesn’t hate Coral and appreciates the thoughtfulness behind it, but acknowledges the inherent uncanniness, the niche appeal, and the real risks that AI companions pose to mental health, especially for younger users. Her cat, for his part, was firmly opposed.

I chose this article to share with everyone because it truly just jumped out at me when I was checking the news. How could I resist that headline??? I also think it hits on a lot of the positives we’ve discussed, like how AI can genuinely help people who are lonely or isolated, but it also doesn’t ignore the concerning sides either, like the mental health risks and the weird blurring of what’s real and what isn’t. I just thought it was a good example that shows AI really isn’t black and white; even the reviewer herself couldn’t fully make up her mind about it, and I think that’s kind of the point. I know I ended up using quite a few articles from the Verge, but it felt like a pretty useful source all around pertaining to AI with quite a few real world and relatable examples, along with being easy to read (similar to The New Yorker or The Atlantic).

Bonifield, Stevie. “Grammarly’s Sloppelganger Saga.” The Verge, 5 Apr. 2026, www.theverge.com/column/906606/grammarly-expert-review-ai-saga. 

This article by Stevie Bonifield for The Verge is talking about the relatively quick rise and fall of Grammarly’s “Expert Review” feature. Grammarly, which rebranded as Superhuman in late 2025 after acquiring the AI email platform Superhuman Mail, launched Expert Review in August 2025. Expert Review was a feature that generated AI writing suggestions under the names of real academics and authors like Stephen King, Neil deGrasse Tyson, and Carl Sagan and presenting them with a verified-style checkmark icon. None of these individuals gave consent, and the feature only came under scrutiny in March 2026 when Wired reported it was using the names of deceased professors, and Verge reporters discovered their own colleagues’ names attached to AI-generated advice they never gave. Superhuman’s initial response was to launch an opt-out email inbox, but after mounting backlash, the company disabled the feature entirely. Investigative journalist Julia Angwin simultaneously filed a class action lawsuit alleging violations of privacy, publicity rights, and likeness protection laws in New York and California. In an interview, Superhuman’s CEO Shishir Mehrotra repeatedly called Expert Review a “bad feature,” yet also floated the idea of eventually relaunching a consent-based version where experts could train AI agents to represent them commercially.

I chose this article to share because Grammarly feels like one of the most familiar AI-adjacent tools in both college and professional life (at least for me!). I also thought that with our recent exploration of copyright and AI, this felt prevalent! But I feel like nearly every student has encountered it in a browser extension or a Google Docs recommendation from Grammarly. This is a tool many of us have trusted, and this article reveals how the company was monetizing real people’s identities without their knowledge as part of that “helpful” experience. Personally, I did not encounter the “Expert Review” feature at all because I ended up disabling Grammarly on everything about a year ago. I disabled Grammarly when it started rewriting my sentences and just going a little too far, although I do love a good spell-check! But in this article specifically, The Decoder podcast exchange between Patel and Mehrotra, where Patel pushes back on the CEO’s claim that fabricated suggestions constituted mere “attribution,” is especially interesting. It really showed how this AI-generated content blurs the line between referencing someone’s work and putting words in their mouth. It just made me think about the importance of CHECKING YOUR SOURCES! If you are using AI for work or school, don’t just let it hallucinate. Take AI with a grain of salt.

Urbain, Thomas. “Life with AI Causing Human Brain ‘Fry.’”, AOL, 29 Mar. 2026, www.aol.com/articles/life-ai-causing-human-brain-013231280.html.

This article, published on AOL (via AFP) this past Sunday explores a growing phenomenon called “AI brain fry.” The basic idea is that the people most deeply embedded in AI (developers, startup founders, consultants) are burning out not because AI is making their jobs harder in the traditional sense, but because managing AI tools creates a whole new kind of mental exhaustion. Consultants at Boston Consulting Group coined the term to describe the mental fatigue that comes from pushing AI supervision beyond our cognitive limits. The article interviews several people in the tech space who describe staying up for 15-hour coding sessions, constantly babysitting AI agents to make sure they don’t go off the rails, and feeling dopamine-depleted afterward. A BCG study of about 1,500 professionals actually found that burnout decreased when AI took over repetitive tasks, so “brain fry” seems to be a problem specific to power users who are deeply managing AI, not casual users (yet). Despite all of this, everyone interviewed still said they had a positive view of AI overall.

I chose this article because it caught my eye with the term “brain fry”. I couldn’t help but think of the term “brain rot” (which I think we are a bit more familiar with). I felt like the article was an interesting and unique perspective of the human cost of AI adoption and rather than focusing on AI’s capabilities, this piece zooms a little closer in on how developers at AI companies are actually experiencing it which was a take I have yet to see. It feels telling that the people most harmed by “AI burnout” aren’t just the people whose jobs AI is replacing, but the ones incentivizing it.

Growtika. “Tech Publications Lost 58% of Google Traffic since 2024.” Growtika, Feb. 2026, growtika.com/blog/tech-media-collapse. 

This article presents original research tracking what’s happened to major tech publications’ Google search traffic over the past two years and the numbers are pretty crazy. Ten major tech publications lost a combined 65 million monthly organic visits since their peaks, a 58% decline overall. Some sites got hit way harder than others. Digital Trends dropped 97%, ZDNet fell 90%, and The Verge lost 85% of its search traffic. The article points to a few likely culprits: Google rolling out AI Overviews broadly starting in mid-2024, Reddit gaining ranking position for commercial keywords that historically belonged to these publications, and a growing number of users skipping Google entirely and going straight to ChatGPT, Claude, or Perplexity for research. Sites built around how-to guides and informational queries got hit the hardest, because those are exactly the types of questions Google’s AI Overviews now answer directly in search results without requiring a click. And it’s not just tech!! NerdWallet lost 73% of its traffic and Healthline lost 50%, suggesting that the pattern extends well beyond tech media.

This was just a crazy find when I was researching! I think I was drawn to it because it literally affects HOW we are researching. Working in a library has me thinking about information access constantly, and watching AI dismantle this ecosystem of trusted sites’ content is crazy to me. If the publications people used to turn to for reliable information are losing 85–97% of their traffic because AI is just… answering the questions for them, that raises a huge question about where people are getting their information now, and how good that information actually is. And honestly, the same threat applies to libraries. AI isn’t just affecting search traffic for tech websites, it’s making people feel like they don’t need to go anywhere for information anymore, whether that’s a website, a database, or a library. Libraries have always fought to stay relevant, but this is just another push. The article doesn’t talk about libraries directly, but to me it’s a massive flashing warning sign: if AI can hollow out decades-old media empires in under two years, libraries that don’t actively define their value in this new landscape are going to face the same pressure. All that being said, I am still googling things all day long for myself and patrons, so I hope that we are safe for now!

Cox, A. M., & Wang, X. (2025). Artificial intelligence in libraries: The emerging research agenda. IFLA Journal, 51(3), 567-569. https://journals.sagepub.com/doi/10.1177/03400352251365278

This piece serves as the editorial introduction to a full special issue of the IFLA Journal dedicated entirely to AI in libraries. Eighteen varied articles make up the issue, reflecting the wide-ranging impacts and uses of AI across library sectors and continents, representing a significant collective addition to both practical and scholarly knowledge about AI in the library world. The authors are upfront that the issue doesn’t wrap everything up neatly. Definitive answers aren’t really possible given how fast the technology is changing and how global the scope of libraries is, but what it does offer is a snapshot of where the conversation is right now. The issue brings together a lot of thought-provoking perspectives on current debates, and useful reference points for the library community. Essentially, it’s a call to libraries everywhere: AI isn’t coming, it’s already here, and the library world needs a shared research agenda to figure out how to deal with it responsibly and thoughtfully.

As someone who works in the library and has for the past five years, this article was especially interesting to read. I love libraries and everything they stand for, everything they do for communities. Seeing and reading about AI moving into that space is complicated. Libraries have always evolved; they’ve survived every major shift in how people access information, from card catalogs to the internet. But AI feels different. It’s faster, more disruptive, and it puts libraries in this uncomfortable position of having to choose: conform, change, or risk being forgotten. I think, regardless of my personal feelings about AI, that AI is not going anywhere anytime soon. It is important that we frame AI not as a replacement for librarians but as a tool that, when done right, can actually deepen what libraries already do best, which is connecting people with information in meaningful ways. I hope that this way of “buddying-up” with AI will save libraries from being erased.

Ren, Shaolei, and Amy Luers. “The Real Story on Ai’s Water Use–and How to Tackle It.” IEEE Spectrum, 22 Sept. 2025. spectrum.ieee.org/ai-water-usage. 

This article was extremely beneficial in explaining the water usage part of data centers. AI data centers run incredibly hot, and keeping them cool takes SO MUCH water! It is way more than most people realize. A lot of facilities use evaporative cooling systems that pull from the same water supplies as local homes and businesses, and U.S. data centers consumed an estimated 17.5 billion gallons of water in 2023 alone, with that number potentially doubling or quadrupling by 2028. The electricity powering these data centers comes mostly from fossil fuel plants that need cooling water too, and that indirect water use makes up 80 percent or more of the total footprint. This article talks about the significance of even asking Chat GPT a single question. One study found that a single short text response consumed about 16.9 milliliters of water. The article does point to some solutions like better cooling technology and switching to renewables, but the authors are honest that there’s no simple fix. Reducing water on one end often just increases energy use on the other.

Honestly, I picked this one because there were so many different views in the articles we’ve read for our discussions. We’ve heard plenty about AI using a lot of energy and water, but it felt like there were some articles saying that we are not affecting the environment significantly and some that were saying yes, of course, we are killing the environment. The fact that about two-thirds of data centers built since 2022 are sitting in high water-stress areas was something I noted in the article. These aren’t just abstract environmental stats, they’re affecting real communities competing for the same water. I thought it was worth bringing to class because it is what we have been discussing of late and it ties in perfectly to my current research on how AI affects the environment.

Song, Victoria. “My Uncanny Ai Valentines.” The Verge, 14 Feb. 2026 www.theverge.com/report/879327/eva-ai-cafe-dating-ai-companions. 

This article is a firsthand account of a reporter visiting the new EVA AI pop-up “dating cafe” in New York City, where people could go on dates with AI companions from the EVA AI app. The reporter tried video chatting with four different AI companions and found the experience quite awkward (bad Wi-Fi, glitching, and conversations that felt hollow and one-sided). The AI companions kept calling her “babe” and complimenting her smile regardless of context, which felt very weird. The event itself was less intimate than advertised, with most attendees being influencers, PR reps, and journalists rather than genuine users. The reporter spoke with a few real guests who had more nuanced takes. Some saw AI companionship as a low-stakes way to feel engaged, while others were curious observers thinking about how technology is reshaping human connection, particularly post-pandemic. She wraps it up by comparing the whole thing to the movie Her and wondering if AI dating cafes could actually become a normal thing someday. Then she went home and hugged her spouse, bringing herself “back to reality”.

I liked this article because it covers AI in a way that’s pretty engaging and easy to read and I was just so shocked by the topic. I know we briefly mentioned this in a past discussion, but this is just bonkers to me. I found Song’s firsthand experience of the event really interesting to read about. In terms of relevance to AI, this article touches on some pretty important questions like what it means for human connection when people start preferring AI relationships, whether these apps are genuinely helpful for lonely people, or whether they’re just capitalizing on that loneliness. The fact that one of the AI “girlfriends” in the app is listed as 18 years old and described as a “haunted house hottie” also raises some real ethical red flags around how these companions are being designed and marketed. As AI gets more realistic and more integrated into everyday social life, these are exactly the kinds of conversations we need to be having, I think.

Kennsley Staniszewski

Peters, J. (2026, January 29). Google’s AI helped me make bad nintendo knockoffs. The Verge. https://www.theverge.com/news/869726/google-ai-project-genie-3-world-model-hands-on

Google’s Project Genie is a new experimental tool that uses the Genie 3 AI model to generate interactive 3D worlds from text or image prompts. The tool is rolling out to Google AI Ultra subscribers in the US and represents Google DeepMind’s work on AI “world models” that can create virtual interactive spaces. Users can either choose from the pre-designed worlds or create their own by writing prompts that describe environments and characters. Once generated, these worlds run at 720p resolution and 24fps, and users can explore them for 60 seconds using keyboard controls. The AI generates frames in real-time based on user movements rather than creating pre-rendered video. The Verge reporter, Jay Peters, tested the tool and found several limitations. There’s noticeable input lag, worlds sometimes lose consistency (forgetting previous changes or suddenly altering terrain), and the 60-second time limit restricts meaningful exploration. The reporter also discovered that the model, trained on publicly available web data, could initially generate worlds based on copyrighted gaming franchises like Nintendo properties, though Google began blocking these requests. Overall, it is an impressive work-in-progress in the world of AI, but it’s not yet at a level where it can compete with traditionally designed interactive video games.

I thought this article was a fun read because it shows what happens when someone actually gets their hands on new AI tech and just messes around with it. The reporter spent his time making bootleg Nintendo games, which I thought was pretty fun. It’s refreshing to see a real test of the technology instead of just reading about how amazing it’s supposed to be! The videos were really interesting to watch as well! This was yet another new addition to the AI world right now that feels like a pretty different approach and could eventually be useful for things like education or even training robots to navigate spaces! The article also touches on some messy copyright issues which is something I have been wondering about! The AI was trained on public web data and could generate worlds that looked a lot like Mario and Zelda games!! The technology is cool but still pretty rough around the edges, which feels kind of comforting and important to remember when everyone’s talking about how AI is going to change everything overnight and when it feels like there are leaps and bounds made in artificial intelligence everyday!