# Reading Responsive Set 2
## Oct 31 Tue - TikTok, fakes, and appropriation

"White women are depicted in pornography as “objects,” Black women are depicted as animals" states Cherid (2021) whilst describing the representation of black women in media. Maha Ikram Cherid's article talk about cultural appropriation, blackfishing, and the commodification of blackness. Cherid (2021) states how cultural appropriation is “the act of taking or using things from a culture that is not your own, especially without showing that you understand or respect this culture” (Cambridge Dictionary, as cited in Cherid, 2021). She provides examples of this where non-indigenous people wear native headdresses as "fashion" to go to music festivals like Coachella, using traditional clothing in a disrespectful way. She also mentions blackfishing and the commodification of blackness in media where popular celebrities such as Ariana Grande would appropriate black women's features and looks. "The commodification of Black culture is a superficial show of tokenized representation that serves to obscure the ways in which this process has not only failed to create deep social changes but has effectively enacted existing power dynamics" (Cherid, 2021).

Similarly, Leo Kim's article "On techno-orientalism" describes a phenomenon called Asian-fishing where people in media would try to look more Asian and claim an Asian identity such as in fake Asian social media profiles run by non-Asian individuals. He describes how prejudices have led to dehumanization of Asian bodies and how technology has led to posthuman stereotypes; Techno-Orientalism is “Asia and Asians in hypo-or hypertechnological terms.” It would present “a broader, dynamic, and often contradictory spectrum of images, constructed by the East and West alike, of an ‘Orient’ undergoing rapid economic and cultural transformations” (Kim, 2021).

Last, Rebecca Jenning's article explains how there are CGI influencers who change their appearance using technology to portray either a likeness of a celebrity or another person or, like Diana Deets, try to look younger for seeminly "wrong" reasons in order to get "clout".

Going off of these readings, I am reminded of Paige Neimann who initally gained popularity online for her likeness to Ariana Grande during early 2017. I remember this being a fun and interesting thing which ended up being weird when she continued this false persona and started posting inappropriate pictures of herself on the platform OnlyFans while still portraying Ariana Grande. Ariana Grande was even against this because she thought it was strange, and she even changed parts of her "iconic" look by changing her hairstyle/makeup so Paige would not be able to look like her anymore. People online so not support Paige because she continued this portrayal, even now, for the attention.

Ariana Grande (left) and Paige Neimann (right)

Even though Ariana Grande has responded negatively to this, Paige still continues so a question that I thought of was what are the implications for celebrities and their image in the digital age, where individuals can easily imitate them and profit in "wrong" ways?

## Nov 03 Fri - Finding someone & living alone

"Robots are not yet replacing our jobs. But they’re supplanting the role of matchmaker once held by friends and family"(Thompson, 2019).Derek Thompson talks about the shift from traditional matchmaking in person to online dating describing it as an increase in individualism and high expectations. He talks about how Americans are "marrying later", but explains how this shift is not necessarily bad. This idea also relates to Chamie (2021)describing how there are also more people living alone and and there is an increase in loneliness and depression, likely a result of the digital age.

The article by OkCupid describes the discrepancies on their platform's profiles which do not truly represent how these users are in real life, one of which includes height and how old the picture is. Not everyone is inclined to use dating apps because they have not found success with them, so Vinter (2023) describes the increased demand for in-person dating and how offline connections are seen as more "genuine".

From these readings, I look back on my personal experience and how I have seen so many people experience this shift to online dating, being unsuccessful with the platforms, then once again shifting back to meeting people in person through school or social events. I also have noticed that much of the time, once people have retried offline dating, they tend to go back online to find people and it becomes a cycle. I have also noticed that the "types" of people strictly using online dating and strictly dating offline are very different, and the people loyal to using certain online dating platforms are also different; each platform has its own miniature filter bubble so people tend to shift around the different "groups" trying to find new people and I believe this technological shift is lessening the differing connections people form while online dating. A question I thought of was how might this change in the future if people are still unsatisfied with online dating and offline dating? Is it possible to meet a wider variety of other people while still being able to have that matching algorithm?

## Nov 07 Tue - Ads & social graph background

The terrifying thought of having big companies tracking your every move has become a reality with the world of cookies and online advertising. Robe Stokes (2014) covers ideas of web advertising which includes direct response sales and branding. Online advertising provides an environment for advertisers to advertise in a variety of different ways which include pop-ups, map advertisements, interstitial banners, and banner ads. Stokes states how ad servers are essential because they provide publishers and advertisers with resources for tracking, and reporting, allowing for reliable targeting based on factors such as user profiles. Technology also makes advertisements more appealing because engaging users can interact with certain advertisements such as playable segments for games and videos. Stokes highlights how online advertising allows better connection with target consumers.

Cleo Abrams then describes first party and third party cookies, and how cookies improve the targetability of advertisements similar to the idea described by Stokes where you will be suggested ads for items that you were previously looking at, specifically, items that you seem to like.

The evolution of online advertising seems ot be quite dynamic, and within a decade, it has evolved so much. At the same time that ads started becoming more personalized, privacy became more of an issue because these companies are seeing everything you do online with technologies like cookies. Nowadays, online advertising seems to me much more prevalent than physical advertisements, but I have also seen a rise in ad-blockers, because these "interactive" advertisements can be quite annoying. I believe it may be an issue if all advertisements become online advertisements, and this is quite possible in the digital age, because people can just block them all. In a way, I think the physical advertisements are more effective, but I do want to see what other ways advertising will transform in the future.

## Nov 10 Fri - Manipulated

In the digital age, even feedback is not genuine, how will user's know what products and content is worth it?

Forsey (2018) describes Instagram pods and how users are almost "cheating" the algorithm by forming groups to get more engagement and get their posts closer to the top of the page chronologically. The idea of pods is a short term solution for engagement and page "growth".

Going off of the idea of faking engagement, Reagle (2015) talks about online reviews which is user generated content to give feedback for online products and content. A lot of the time, reviews are not all genuine. Some people fake reviews on their own or with bots for their own personal gain or sometimes for the downfall of people and products they do not agree with.

The exploitation of user generated reviews is a cause for concern because nowadays, fake reviews and comments, at least the ones from bots, have been more and more difficult to recognize. These readings remind me of our talk about media literacy and detecting fake news because people are now having to detect fake reviews in order to figure out if a product purchased online is genuinely good or bad. There is still the issue of reviews where there is no text content, and just a star rating. This is seemingly impossible to detect whether or not the reviews are real. I believe to combat this, people should focus less on educating themselves on how to spot a specific fake review, but more on understanding how the algorithms work on the platforms they are buying from or apart of.

In my own experience, I used to browse a website called DHGate (similar to Temu). I noticed how almost every product has seemingly real and overwhelmingly positive reviews.

Example of a **fake** review that I found:

I know that this was a fake review likely uploaded by a bot because I have always see identical reviews on other product pages, or even the same one, with just a few words changed. They also always reference how the seller or merchant is very *honest* or *kind* because that seems to be an algorithmic key words.

Another **fake** review:

These are two reviews directly below--- The photos, location, and usernames are all different but the reviews itself are identical. In a way, these reviews are still similar to the first one, mentioning the same points with different wording. They were also all published on the same day. I have also noticed that with this website, the products that get shown the most are typically the ones with the most key words (more bots), and understanding this algorithm allows me to search for honest reviews.

## Nov 17 Fri - Artificial intelligence

Robots taking over the world may now be more fact than fiction as AI presence is prevalent in art, writing, and many others.

Heilweil (2023) explores the rapidly growing field of generative AI, showing how widespread artificial intelligence is nowadays. Some uses include preventing exam cheating to creating odd depictions and mimicking human speech. Heilweil emphasizes how AI models such as ChatGPT and Stable Diffusion are accessible and how they can transform tasks like book writing and code generation, comparable to if it was written by humans. Heilweil highlights the potential of generative AI as well as its limits, using the technology's capacity to mimic human writing and illustration as an example, will not be truly accurate to what a human may want something to look or sounds as it can have errors and defects. Heilweil highlights concerns on the negative impact of AI on the labor market, specifically, the possibility of job loss.

Vincent (2022) talks about the negative reaction to Stable Diffusion's Version 2 upgrade, which limits the program's capacity to produce NSFW material and imitate the styles of particular artists. Upgrades like better in-painting and upscaling were included, but the upgrade also limits the creation of pornographic content and artwork that mimics the looks of famous people or artists. He talks about misuse issues such as producing non-consensual pornography and child abuse imagery, and Stability AI confirms that NSFW content has been removed from training data. Despite user dissatisfaction the company suggests that in the future, training datasets will allow artists to opt-in or out to address concerns.

Gold (2023) addresses the unique characteristics of artificial intelligence using Sydney, Microsoft's Bing chatbot. She focuses on Sydney's unpredictableness as a result of long chats and she compares it with Spotify's AI DJ. Similar to Asimov's Three Laws, Gold highlights the need for more specific guidelines in AI research, emphasizing the significance of clearer principles in the evolving field of AI.

From the readings, I was drawn to the connection between human art and AI art and there were many negative implications brought up in the readings, but I particularly thought about Adobe Photoshop's new feature of [AI generative fill](https://www.adobe.com/products/photoshop/generative-fill.html) where people can easily alter photos, remove unwanted items, and "continue" a photo seemingly better and quicker than any human can. This feature can be thought of as a creative tool rather than replacing human creativity, but ethical concerns are very clear where it will be difficult to see if a photo is "authentic" or real when Adobe's AI art looks like reality.