It helped reinforce my understanding of how ethics and technology intersect. The Luddites weren’t just anti-technology—they were resisting the economic and ethical consequences of industrialization, like job loss, poor working conditions, and exploitation. This challenges the simplistic view that opposition to technology is irrational or backward.

Reading this made me reflect on how similar ethical concerns arise today with AI and automation. The ethical questions aren’t just about whether we can create new technology, but whether we should, and under what conditions. Like the Luddites, modern critics of tech often ask: who gains from these innovations, and who bears the cost? This aligns with my growing view that ethical thinking must include social and economic impacts, not just individual behavior.

Throughout this course (or experience), my views on ethics have been both reinforced and expanded. I’ve always believed that ethics involves doing the “right thing,” but I now see that ethical decisions are often complex, situational, and require balancing competing interests. What was reinforced for me is the importance of empathy and fairness—considering how my actions affect others and striving for transparency.

At the same time, my understanding of ethics has evolved. I used to think of ethical behavior as primarily personal—about individual honesty or integrity—but I now see how deeply ethics is tied to systems, power structures, and social responsibility. Learning about ethical dilemmas in business, technology, or healthcare (insert your relevant field) helped me understand that being ethical isn't just about avoiding harm; it's about actively promoting justice and accountability.

Overall, I now approach ethical questions more thoughtfully, with a greater awareness of nuance, context, and the need to ask deeper questions about who benefits and who may be harmed.

The Investopedia article by James Chen explains that “cornering a market” means gaining enough control over a specific asset—like a stock or commodity—to manipulate its price. What stood out to me was the detail that while it’s technically legal in some cases, it’s often considered unethical or even illegal if it involves manipulation or deception. I didn’t know this was a real thing people tried to do outside of movies, so learning about the history of market cornering made me think more critically about power dynamics in economics and how far people will go to control outcomes.

Reading this really helped me understand something I’ve always been confused about—how social media companies actually make money. I use apps like Instagram and TikTok all the time, but I never really thought about what their business model is. After reading this, I realized that the free services we enjoy are actually funded by advertising and data, and that kind of shocked me emotionally. It made me feel a little weird, knowing that the more time I spend scrolling, the more valuable I am to advertisers.

Personally, I think this chapter explains an important truth that most users overlook. Social media platforms don’t exist to serve us—they serve their investors. That’s why they keep changing algorithms, pushing ads, or making it harder to see posts from friends.

The source Trauma and Shame explains how shame is deeply connected to trauma, especially for children who have experienced neglect or abuse. One detail that stood out to me is how children often internalize shame even when the bad thing that happened wasn’t their fault. This reinforces what the chapter said about shame making people feel like “I am bad.” I think this is important because it shows that shame can be a long-term effect of trauma, and it takes more than just reassurance to heal—it takes rebuilding a sense of self-worth.

I really connected with the section about shame in childhood. When I was in 5th grade, I went to a regional track competition to run the 100m, but I didn’t wear a sports bra—just a regular CK bra. My parents were both busy working, so my grandpa took me to the meet. I remember feeling so embarrassed and uncomfortable, especially being surrounded by older girls who were more prepared. I didn’t tell anyone, but I felt ashamed, like I had done something wrong even though it wasn’t really my fault. Looking back, I realize that what I was feeling was shame, not guilt. I wasn’t reacting to something I did wrong, but rather how I thought others saw me. This part of the chapter really helped me understand the difference between shame and guilt, and how deep that early experience stayed with me.

it really stuck with me. The author talks about finally reporting her stalker after 14 years, and how difficult the legal process was — especially because she wasn’t seen as “afraid enough.” That part hit me personally. I’ve always believed seeking legal help is important, but I also know how expensive and emotionally exhausting it can be. It made me think about how the justice system sometimes requires visible fear to validate someone's pain, which isn’t fair. Not everyone reacts to trauma the same way, and justice shouldn’t depend on performing distress.

Reading this reminded me how easily systems can miss the full picture of someone’s identity. I’ve personally seen situations where efforts to improve fairness only help in a general way—for example, including more women or more people of color—but still leave out those at the intersection, like women of color. It makes me think of how often people assume one solution fits all, when in reality, we need to consider how overlapping identities affect people’s experiences. I didn’t know the term intersectionality before this, but now I realize how important it is in making technology and policy more fair.

I browsed the Patreon website and thought it looked pretty good—it's clean, easy to navigate, and feels professional. I can see how creators would feel encouraged to use it, and how supporters like me would feel more confident putting money toward someone's work. The layout made everything feel transparent and trustworthy.

I hadn’t really thought about how many dimensions go into communication until I read this. The breakdown—especially things like synchronicity and archiving—made me reflect on my own habits. For example, I love texting because I can respond when it’s convenient, but I never considered how helpful it is that messages are automatically saved. That’s really different from face-to-face conversations, where things can be easily forgotten or misunderstood. I also realized how often I choose communication tools based on how “safe” or anonymous I feel in the moment. This made me more aware of how tech shapes not just how we talk, but how we relate to people.

Reading about Behind the Screen really opened my eyes. I always assumed content moderation was handled mostly by AI, but Roberts shows that it’s often done by real people who have to view traumatic content day after day. That made me think about how much invisible labor goes into keeping our feeds “clean.” I feel kind of guilty now for complaining about my posts being flagged when others are doing such emotionally draining work just to protect users like me.

I’ve seen these bots in action, especially on TikTok and Instagram. Sometimes they flag completely harmless content—like one time a friend’s video got muted just because a lyric sounded suspicious. I get that bots are trying to help, but I feel like they still lack the human context to tell jokes from harm. It’s helpful for filtering spam quickly, but it also makes me nervous when something important gets taken down just because the algorithm didn’t “get” it.

After reading the Wikipedia entry on spamming, I realized how broad the definition is—it’s not just junk email but includes things like comment spam and even social media bot activity. I remember once getting dozens of fake “promo” comments under my Instagram posts in just a few hours, and it felt overwhelming and invasive. This source helped me understand why moderation tools are necessary, even though I used to think they limited free speech too much.

I found it interesting how even platforms that claim to value “free speech” still block spam. It reminded me of when I tried using a small social app with no moderation—within a week, my feed was full of scams and random ads, and I stopped using it. This helped me understand why quality control is actually important for keeping social media usable.

This NPR article by Anya Kamenetz discusses internal research from Facebook showing that Instagram negatively impacted the mental health of teenage girls. A key detail from the source is that even after learning this, Facebook continued to let teens use Instagram. This raises concerns about how much responsibility social media companies take for user well-being, especially when their platforms are shown to contribute to harm.

I really like Instagram, and I enjoy using it to stay connected with friends and explore things I’m interested in. But it’s true that social media can have a negative effect on some people’s mental health. I remember a girl from our middle school who participated in an anonymous Instagram activity where people shared harsh comments. After she read some of the things that were said about her, she became very depressed. It was really sad to see how something online could affect someone so deeply in real life.

I looked up the artist credited in the chapter—Nobu Tamura—and found his paleoart blog full of detailed and fascinating illustrations of prehistoric animals. His work helps make evolutionary timelines visually understandable, especially for non-scientists. What surprised me, though, is how different this Nobu is from the one I initially thought of—Nobu Matsuhisa, the world-renowned chef behind the luxury Nobu restaurants. It’s funny how one name can carry such different associations: one tied to ancient fossils and evolution, and the other to sushi and celebrities. This made me think more about memes in the Dawkins sense—how names, symbols, or even people’s legacies can evolve and take on new meanings over time in completely different cultural “ecosystems.”

I found it really clever and insightful that Dawkins chose the word “meme” to rhyme with “gene”. It emphasizes how he viewed cultural evolution as parallel to biological evolution. That comparison made me pause and think about how ideas—like songs, slang, or even fashion—really do spread almost like living things. I’ve seen this in how certain TikTok trends go viral: they adapt, replicate, and sometimes even “die off” if they’re not catchy or timely. It's interesting to imagine our minds as “hosts” for these cultural genes, constantly passing and mutating them. This framing made me more aware of how passively I sometimes adopt ideas from social media without thinking deeply about their origin or value.

This Wikipedia article explains that color blindness is usually a genetic condition that affects how people perceive certain colors, especially reds and greens. A key detail is that red-green color blindness is the most common type, and it’s much more prevalent in people assigned male at birth due to X-linked inheritance. The article also highlights that while there are assistive tools like color filters and apps to help distinguish colors, these tools only support daily navigation.

This article tells how some women possess a rare genetic condition called tetrachromacy, which gives them an extra type of color-detecting cell in their eyes, allowing them to see millions more colors than the average person. An interesting detail from the article is that while many women may have the genetic potential for tetrachromacy, only a small number actually use it fully to perceive extra colors in everyday life.

Reading this section made me reflect on how unfair it is that disabled people are expected to adapt just to appear “normal.” Assistive technologies are helpful, but the pressure to use them just to fit into a world that isn’t designed for them feels exhausting. I’ve seen this with friends who rely on glasses, ADHD medication, or mobility aids—society often expects them to perform at the same level as others without recognizing the extra challenges they face. It frustrates me that the burden is always on the individual to change, rather than on society to become more inclusive. This chapter made me more aware of how even supportive tools can reinforce exclusion when the ultimate goal is to “normalize” people instead of embracing difference.

After reading this part about "private messages" not actually being fully private, it made me realize that even my searches and conversations can be stored and scanned by computer programs. I’ve definitely noticed that after I search for something, like a brand or a product, I start seeing promotions for it almost immediately on social media. It makes me feel like my activities are being watched all the time, even when I don’t want them to be. I think this shows how little control we really have over our own data once we are online.

After reading this part about "private messages" not actually being fully private, it made me realize that even my searches and conversations can be stored and scanned by computer programs. I’ve definitely noticed that after I search for something, like a brand or a product, I start seeing promotions for it almost immediately on social media. It makes me feel like my activities are being watched all the time, even when I don’t want them to be. I think this shows how little control we really have over our own data once we are online.

This article explains how a teenager posted a TikTok video that unintentionally disrupted thousands of scientific studies. The video showed how easy it was to sign up and get paid for surveys on a platform called Prolific. After it went viral, a huge number of young users rushed to join, which suddenly changed the demographic data of many studies and made some results unreliable. It shows how social media can unexpectedly influence scientific research.

This reminded me of when I used to see random charts online like "ice cream sales and shark attacks go up together" and I thought they were funny but kind of believable at first. After reading this, I realize how easily we can be tricked by spurious correlations. It makes me want to double check data more carefully now. It’s actually kind of shocking how something that looks real can be totally misleading.

This article discusses a comedian who impersonated the FBI on Twitter and made a joke about the MLK assassination. It raises the question of whether something is just a joke or actually offensive. One detail that stood out to me is how the line between trolling and harmful speech can get blurry when people use humor to talk about serious historical events. It connects to how trolling sometimes hides behind "just joking" but can still cause real emotional harm.

This section reminds me of times when I’ve seen people post obviously fake or mean comments just to make others upset, especially in livestream chats or game forums. I used to think they were just joking, but now I realize it was trolling. It’s interesting to learn that some people do it to feel powerful or smart. I’ve even seen people try to “troll the newbies,” which I didn’t know was an actual term before reading this.

This source shows how text analysis was used to find out that Trump himself likely tweeted only from the Android phone, and those tweets were more emotional and negative. One detail that stood out to me is how the Android tweets had more angry words and were posted at different times compared to the iPhone tweets. It’s interesting how data and tone analysis can help reveal who is really behind a social media account.

I think the authenticity of Trump’s tweets really depends on who actually typed them. If it was him personally, it feels more real and emotional, even if it’s angry or negative. But if the tweet came from a staff member using an iPhone, it feels more like a planned message from the campaign. So yes, the tone and who wrote it really changes how I see the post. The emotional expression, like anger, also makes it feel more personal and probably more like it came from Trump himself.

This Wikipedia source talks about the history and development of text messaging (SMS). One interesting detail is that SMS was first designed for 160-character messages because of the technical limit of early systems. I didn’t know that before, but now it makes sense why early text messages were always super short.

Social media gives me a lot of fun because I can see different people sharing their life or opinions, like instagram and the red note, this two are my fav. But yeah, I also feel like some spam messages or weird posts I saw online might be generated by Python or other coding tools, not real people. It’s kind of cool but also sometimes annoying.

This blog helped me understand why floating point math can be tricky in programming. One detail that stood out to me was the example about the inaccurate timestamp, where rounding errors caused time data to be slightly off. I didn’t realize that something so small could affect how events are logged or displayed. It made me think about how important precision is when dealing with data in real world programs.

When I first started learning Python, I remember being really confused about why lists start at 0. It felt so unnatural at first, but now it just feels normal. I didn’t realize it was because of historical reasons, so learning that made things make more sense. Also, seeing how lists can be combined or grouped really reminded me of working with social media data in class. Once data is grouped, like replies, retweets, and likes, you can analyze patterns, trends to predict behavior. It’s interesting how something as simple as a list can be used for really powerful things once it's organized and connected with other data.

This article was really interesting and also kind of shocking. I didn’t know that people actually sit in front of a bunch of phones just to fake app downloads. Like ylt said, it’s strange how humans are being used to act like bots. I agree that it’s hard to tell the difference between real automation and people just following instructions. Toffeevv also made a good point—this doesn’t just happen in small companies, but even big ones like Apple. It makes me feel like the app store rankings can’t really be trusted if things like this are happening behind the scenes. It also shows how messy the line is between tech, business, and ethics.

I never realized bots could seem so real on social media. It makes me wonder how many accounts I’ve interacted with that weren’t actually people. It also makes me a little uneasy, especially when bots are used to push certain opinions or make things trend. It feels like it’s getting harder to know what’s authentic online.

Reading about Confucianism reminded me of when I visited Confucius’s residence. Standing in the place where he once lived made me reflect on how incredible it is that his ideas have lasted for thousands of years. It’s especially powerful that his students respected him so much that they recorded his words and turned them into a book that still influences people today. I think this shows the strength of a teacher-student relationship in Confucianism and how deeply valued wisdom and learning are in this tradition.

I think here is talking about the moral and ritual foundations of Confucianism. I appreciate how it emphasizes harmony through personal conduct and ceremonies. It might be interesting to add how Confucian values have influenced modern East Asian societies, especially in education, family structure, and governance. Also, comparing how each key figure Confucius interpreted these values differently could deepen my understanding.