Category: MCO 426

Who owns our conversations when it comes to digital media such as social platforms? According to Copyright Laws, we own the content we post on social media, but we’ve given license to social platforms to use it as is spelled out in their terms and conditions. Social platforms can use our content as they see fit.

There are centralized and decentralized platforms. Centralized platforms are owned and controlled by one single entity. These include platforms such as Facebook, Twitter/X, Instagram, YouTube, etc. As described by CMR Berkeley, centralized platforms are stored on centralized servers where the platform retains ownership and control over user data and content.

They also describe the benefits of centralized platforms as having a well-established user interface and a large user base that allows for networking. Some drawbacks are that centralized platforms can be more susceptible to censorship and privacy is often a concern, as these platforms can use user data however they’d like.

I use one centralized social media platform, Twitter (now X). Elon Musk’s takeover has shown me that we cannot depend on the goodwill of the owners of these centralized social media platforms. Elon Musk made drastic changes that led to chaos, such as a paid blue check mark system.

Journalists, government organizations, etc. lost their verification status if they didn’t pay for it. This led to imposter accounts and made it harder to tell if information was coming from a reliable source. This showed me that my experience on a centralized social media platform is beholden to the current owner.

What can we do about this? I believe that government intervention in this brings concerns about censorship and overreach. I think the easiest and most beneficial change we could make is to join decentralized social media platforms.  Decentralized platforms are not controlled by a single entity, they are distributed across multiple independent servers. Users have more control over their data and privacy and decentralized platforms are more resistant to censorship.

However, decentralized platforms must become more appealing and widespread among users. People want to use social media networks that their friends are on. As of now, decentralized platforms do not have the user base that centralized giants such as Facebook and Twitter (X) have. Since many of these platforms are still in development, they can have limited features compared to centralized platforms.

Particularly after the recent election, I noticed many of the people and groups that I follow on Twitter (X) were moving to a decentralized social media platform called Bluesky. In November 2024, Bluesky reached 20 million users. I joined this platform and have liked the experience of using a decentralized network where I have more control over my privacy and data protection. The Conversation describes how Bluesky is set up like the old Twitter and allows users to host a server where they’re able to control and store their data.

Decentralized platforms have their drawbacks though. An article from Medium describes how decentralized social media faces challenges including scalability and tough competition from centralized giants. The blockchain application that decentralized platforms use can require a learning curve that can discourage new users and mass adoption.

I believe that if these challenges can be overcome, we can encourage more users to join decentralized social networks. As we have seen from Bluesky’s growth, there is a desire and need for users to join social networks that allow them more control. We should own our conversations and decide how our data is used.

This week, I experimented with using AI text generation. I used ChatGPT and the prompt I gave it was “in 250 words, describe depression and its effects on a person.”  I chose to use depression as my topic for this assignment because it is something I struggle with in my own day-to-day life. I’ve done a lot of reading on this topic, trying to educate myself on it so that I know how to deal with it.

As someone who is admittedly pessimistic about all things AI, I was surprised at how well the response was to my prompt. I noticed that the factual details were accurate, but the AI tended to generalize in the wording. For example, one of the lines it gave was, “The effects of depression are far-reaching…” I changed this to “…can be far-reaching.”

The AI text left out how depression is different for everyone. Not everyone has the same symptoms, intensity of symptoms, or responds to the same treatments. I included these in my revisions because just because you CAN have a certain symptom, it doesn’t mean you WILL have that symptom. Here’s the AI response and my revisions.

I also added context to my revisions by including key facts from credible sources. The sources I used include the World Health Organization, Cleveland Clinic, National Institute of Mental Health, and Healthline. The facts given in the AI response matched the information about depression from these sources.

From this experiment, I learned that it’s a good rule of thumb to scrutinize the material given in an AI response. I don’t trust the software enough to just accept what it has written because it can make mistakes. Even though the material in mine was correct, there is always the chance that the material could be wrong. I also learned how AI tends to generalize and that has made me more inclined to comb through an AI text response.

 At the end of my revisions, I also added a line about my struggle with depression. I felt that adding this provided a human element rather than sounding robotic like a computer wrote it. In the end, a computer or large language model can’t suffer from depression, it is a human experience.

This week we were tasked with editing on Wikipedia. Since Wikipedia is an online encyclopedia that’s been around for a couple of decades now, I had a hard time finding something that I could contribute to. I tried to find something that I was interested in that was niche and maybe not covered as much on Wikipedia. One of my guilty pleasures is watching soap operas and I learned that Wikipedia has a vast amount of information on soap opera storylines, characters, actors, etc. Most U.S. soap operas have been on for 50+ years and Wikipedia comprises a lot of that history.

I started looking at articles about soap operas I watch, trying to see if there was anything that I could add. As someone who watches Days of Our Lives, I came across an article listing all the characters that have been added to the show in the 2020s. I noticed that a new character that recently appeared in October 2024 wasn’t on this list. Finally, I felt like I had something I could add to Wikipedia!

I knew I needed to find a relevant and credible source to back up this information. Wikipedia’s verifiability policy requires that any material added to Wikipedia be backed up with a credible source. This ensures that information added to Wikipedia is based on facts and not on opinions. I found an article from TV Insider. This is a website that covers news related to television. It backed up all the information I wanted to add; the character’s name, the character’s first air date, the character’s connection to other notable characters, the actor portraying the character, etc.

Next, I went to the talk page and added a new topic, explaining what I think should be added and linked to the TV Insider article. As of now, I haven’t received any replies, so I decided to do the editing. Even though Wikipedia doesn’t have firm rules, there are a lot of policies and ways that you’re supposed to do things. Trying to follow the policies and guidelines made it a bit confusing at first. I feared messing up the article. Following Wikipedia’s citation guidelines helped me and I feel like I got the hang of it.  Here is the article with my contribution added (it’s still there as of writing this).

In school, I was told not to use Wikipedia because anyone could edit information on there, and that it wasn’t reliable. In theory, anyone can contribute to Wikipedia, but they must back up what they’re saying with a reliable source. My view of Wikipedia is more positive, and I now believe that Wikipedia is a great starting point for research. As Pete Forsyth explains, Wikipedia should be seen as a platform rather than a publisher.

Instead of citing Wikipedia as a source, Wikipedia should be used “as a guide to find more reliable sources, and then citing those sources directly.” This experience has helped me to think of Wikipedia as a reference aggregator. If I’m researching a topic, I can go to the article for that topic on Wikipedia and dig into the references used in the article at the bottom of the page to use in my research.

I believe that Wikipedia can be a useful media literacy tool. When checking the validity of a claim or source, we can use the SIFT method (Stop, Investigate the source, Find better coverage and supporting evidence, and Trace claims back to their original context). Wikipedia is a tool that can be used as part of the investigative step of SIFT. This was an interesting experience, although I don’t think I’ll become a Wikipedia editor. However, I will continue to be a consumer.

For this week’s video blog, I made a tutorial on how to get started with diamond painting. Diamond painting is a craft where you put different colored diamonds (also called drills) onto a sticky surface, which creates a beautiful image once you’re finished. I hope that you’re encouraged to try diamond painting or find a craft that you enjoy!

Diamond painting has been a rewarding hobby for me. Diamond Art Club describes the six benefits of diamond painting as minimizing stress and anxiety, stimulating creativity, boosting one’s artistic confidence, fine-tuning motor skills, the ability to join a community, and unplugging from technology.

Diamond painting (and crafting in general) is part of MBAT (mindfulness-based art therapy) according to Diamond Art Club. In a paper for the National Library of Medicine, authors Beerse, Lith, Pickett, and Stanwood say MBAT “combines mindfulness practices with art therapy to promote health, wellness, and adaptive responses to stress.”

Heartful Diamonds also describes how the repetitive and rhythmic movements of diamond paintings can have therapeutic benefits since focusing on the task allows you to relax which “can help to create a sense of calm and tranquility, while also allowing you to tap into your creative side and create a beautiful work of art.”

Why Photography is Better Than AI-Generated Images:

This week I looked at three different sources of images. With my subject as desert sunsets, the first photo is the one I took on my iPhone from my backyard. The second is a stock photograph and the third is an AI-generated image that tries to follow the same subject. This experience has led me to conclude that human images/photographs are better than ones that are generated by AI.

There is a kind of relationship between an artist or photographer and their work. With the photograph I took, I had to physically go to where I wanted to take the picture, plan what time and angle, etc. I assume the photographer of the stock photograph did this as well.

But I didn’t have this personal relationship with the AI-generated photo. I typed in a prompt, and it spit out an image. I had a hard time getting the AI-generated photo to look like mine and the stock photo and I still found the result to look fake and not like an actual photograph.

This is because AI cannot mimic the process of photography. In his blog, Mindscape FX, David Wilson describes how photographs are created by light falling onto a photosensitive surface which is converted to an image either digitally or chemically.

In an article from Wild Eye, Justin Black explains that one of the things that makes photography better than AI is that it encourages us to see and explore the world. Photography captures the memories of the places we’ve been to and the experiences we’ve had. Another of Black’s points is that photography allows us to add our creative vision from start to finish. But no matter how much we add to an AI-image generator prompt, the final image is the product of AI and its training.

Natalie Zepp, who runs a photography blog and business, sums it up best by saying, “While AI can enhance certain aspects of photography, it lacks the intuition, emotion, and creative insight that are integral to the human experience. Photography is not solely about capturing images but also about conveying stories, emotions, and perspectives that are deeply rooted in the human condition.” Even as AI-generated images improve, they still won’t have the human elements that make photographs special.