Reading responses 5 out of 5
# 1. Bemused
When buying most products on Amazon, users can find recommendations or bundle ideas that they may feel inclined to include in their shopping carts. 9 times out of 10, I ignore this feature. I am not a victim of dynamic pricing and pretty bundles. That is because many online shopping enthusiasts infer that there will *always* be a better substitute than the ones the platform gives you, no matter the season. In Absurdities: "Elegant Design-Just for Her", Reagle (2015) points their mouse at a combination of frequently bought items, “men’s khaki pants ‘because you rated Star Wars Trilogy’. Other product recommendations that come by the way of Star Wars include a twelve-cup programmable coffeemaker and a nose and ear hair groomer (Reagle, 2015).” Interestingly enough, a persona has been made of the type of customer who either watches Star Wars or regularly wears business casual.

Recommending a nose and ear hair groomer is not so amusing to me (it is actually); it is the that a large company markets on consumer identity through targeting and segmenting. Not to mention, they were frameworks from my MKTG 2201 class that were highly memorable; it makes me think more about how consumers are treated on the other side of the screen. On one side, we have online users laughing together at crazy reviews, but on the other side lie firms broadly categorizing their customers. By tracking purchase history and what items similar customers are buying, companies like Amazon can analyze that data and turn anyone into a cart that needs to be filled with useless junk (I am not calling the Star Wars trilogy useless junk, as my father is an avid fan of the franchise). But on that note, when that marketing logic becomes apparent in a feature that is recommended to customers, humor also gains visibility in that as well. In this way, the "bemusement" that Reagle (2015) describes is not only about humorous combinations and comments, but also about the unexpected assumptions that are made about us, the consumer.

# 2. Artificial Intelligence

AI is better at weaving baskets than most middle school art students. Both appear to be creative in nature; asking a provocative question will often result in an even more provocative response. AI is particularly skilled at pattern recognition, which is rooted in probability and statistics. In result, any prompt given to a chatbot is not based in real meaning or truth, but is predicted. I could even ask an AI bot for help with my statistics work and include a formula as well. However, there is a high chance "I" will be wrong. The first article highlights the technical side of how artificial intelligence works, "Pre-training...involves predicting the next word in a sequence" (Newhauser, 2023). This implies that AI does not merely understand anything, and can rewrite and rework any prompt. The highest risk here is not the idea that AI can be incorrect, it is that it convinces its users that it is correct. When it comes to images, generated videos and photos have become extremely uncanny to face and cause celebrities and high profile individuals to be seen differently. Newhauser (2023) shows us that in fact, outputs are "becoming increasingly difficult for humans to distinguish from non-generated images." Here, it is hard for digital users to articulate man-made art or creations from something artificially created. The increase in skill with AI also causes real evidence and information to look false, potentially spreading misinformation.

With bots now being able to create overachieving amounts of information and splendid graphic designs, bots can not only express "themselves" creatively, but also socially. Gold (2023) reinforces Newhauser's point in that Chatbots act upon the information given by its creators. On the other hand, Gold also illustrates that because they are trained by human text, Chatbots mimic that cadence of digitally speaking as well. "What is important is that chatbots are autocomplete tools. They're systems trained on huge datasets of human text scraped from the web." Responses that are reduced, reused, and recycled may not always appear polished, but for AI Chatbox, it makes it seem much more human-like. What users must remember is that the bot is a bot, without any consciousness. This means that individuals who routinely use chatbots tend to overestimate its abilities (for now) in different ways. That may include social aspects in terms of producing rash responses, or being able to read and comprehend tweets and blog posts about itself. Altogether, both Newhauser and Gold show us the importance of understanding how AI works both regarding probability and regarding social ineptitude. Both readings suggest that the consequences of AI are not only technical and bug-based, but also in society, where users interact with systems that appear to be falsely intelligent.

# 3. Algorithmic bias
## How do algorithms exhibit biases (intentional/otherwise)?
Algorithmic biases may be believed to be derived from systems, coincidences, or from programmed machinery. However, the root behind these issues regarding algorithmic bias really lies in humans and their preexisting mentalities. Rutherford & White's observations imply that algorithms do not necessarily create new meanings, as we have learned before that AI mechanisms learn from preexisting data and patterns taught to them by their creators (2016). Here, bias is introduced by data and user behavior, but it may sometimes appear malicious. Algorithms, much like robotic machinery, do not consider "feelings" as a matter of importance. Another example of misinformation when it comes to this data includes the relation of professionalism and certain ethnic hairstyles. Because these issues arise from underlying text or captioning, the relation to negativity can be confusing and can misrepresent different groups of people. In this way, algorithms can be detrimental. Some may reflect back and try to connect to how algorithms can associate different biases together. From Hochman's article on AI and bias, it is noted that algorithms are backed by developers, policies, and platform goals. It simply depends on the firm that has an agenda to bring forward a certain ideal! Hochman demonstrates that ChatGPT and its misinformation reflect human truth and acceptability (2023). This proves that algorithmic bias is manmade, manufactured even. Though it can be deliberate and embedded because of policy, bias can be delivered in a way that seems innocent, but really is uncovered to be socially detrimental.

# 4. Digital Language and Generations
### We return to a thread we begin the course with, how different generations have inhabited the digital age (McCulloch’s chapter 3); we also consider how language evolves (via an interview with McCulloch)

Internet language constantly evolves, and new forms of communication emerge from various trends or events. An example of one of these fads includes the emergence of "fairy comments" on Tiktok during 2020's Covid-19 pandemic. Guirgis from The Stanford Daily's article on Donald Trump's Instagram comments reflect cunning yet spiteful language towards the politician. One Instagram comment wrote, "'“When peter pan flew away to neverland 🦋💫💞🥰🌈 it was to get away from you 😘🧚🏼‍♀️✨😍💐.'(Guirgis, 2020)" Although this article touches on the power of younger generations and their social impact, it's also important to note that this style of language lasted for over 2 years, causing young digital natives to become more familiar with irony and other rhetorical devices all because of the internet.

Members of the Gen Alpha and Gen Z circles make use of short language as something convertible. A word could have 1 meaning, 3 meanings, or none at all. One could argue that the reason why words lose meaning is because they were so commonly used in the past. Individuals in relationships may feel that exchanging compliments may feel old because they're so used to them, and the same could be said about slang, which can now be considered as filler words. McCulloch describes that for although older generations typically consider "LOL" as a more serious form of laughing digitally, younger generations have adopted other forms of expressing that same feeling. Long gone are the days of "lol" and "LOL" and say hello to "AHSDKASDH", "LMFAO", "LMAOAOA". With this new emergence, other words grow into the maturity stage. McCulloch (2019) illustrates this in her interview with Audie Cornish, "For the youngest group of people, there's no literal meaning left to LOL at all." Though I may not use "LOL" to my parents the same way I use "...lol" with my friends,the word may lose its meaning. But for some digital natives and non-natives, it will always remain a strong form of expressing joyous feeling.

(Other) References:
Guirgis, H. by M. (2020, August 3). Tiktok ban: Trump is tired of gen Z “being mean to him.” The Stanford Daily. https://stanforddaily.com/2020/08/03/tiktok-ban-trump-is-tired-of-gen-z-being-mean-to-him/

# 5. Pushback
The phrase "I'm not like other girls" takes on its final boss challenge when facing the notion that advanced technology is detrimental to society. This ideology doesn't come from being against technological advancement, but it stems from being overwhelmed by the sheer amount of advances made every day. Morrison and Gomez' academic article (2014) frames this as "pushback" against constant connectivity. People are expected to be available and online all the time, which can make individuals feel drained, used, manipulated, and sometimes scared. Much like how in class we discuss the fears we have about AI taking over the world, it's normal for individuals to feel the same about technology as a whole. Technology doesn't present as something harmful, but rather its intensity and prevalence in our modern day lives appear intimidating. Vadukul (2025) discusses the motives and recent updates on the Luddite group, showing how the group has evolved since it was first introduced.

With the popularization of flip phones, they've inspired many to revert back to the ways of the 2000s, where technology was meant to be futuristic, fruitiger-aero, and fun. Or at least that's how I think of flip phones. However, one of the group's members struck me, saying, "I own this [Android] now with a sense of inner torture,” Ms. Watling said, “but I have to look out for my well-being as a young woman. It’s too risky for me to put my life in the hands of a flip phone”. This reflects what Morrison and Gomez' research suggests: most online users cannot fully reject technology, but they can create boundaries to control themselves and their usage. Does this mean even those who utilize their passion for social movement suffer from temptation? The article later shows how feelings of missing out from other digital applications, such as dating apps, which are obviously not included in any premium flip phone application. Ms Lane even says that one day she wants to be unreachable. By trying to solve the problem of having 1 phone by having 2, it raises the question of what is actually being fixed. In the end, both the research and the article suggest that resistance isn't always clear and that pushing back has its limits.