Inventors ignoring the ethical consequences of their creations is nothing new as well, and gets critiqued regularly:

In England in the early 1800s, Luddites were upset that textile factories were using machines to replace them, leaving them unemployed, so they sabotaged the machines. The English government sent soldiers to stop them, killing and executing many. (See also Sci-Fi author Ted Chiang on Luddites and AI)

Most programming languages are based in English, and there are very few non-English programming languages, and those that exist are rarely used. The reason few non-English programming languages exist is due to the network effect, which we mentioned last chapter. Once English became the standard language for programming, people who learn programming learn English (or enough to program with it). Attempts to create a non-English programming language face an uphill battle, since even those that know that language would still have to re-learn all their programming terms in the non-English language. Now, since many people do speak other languages, you can often find comments, variable names, and even sometimes coding libraries which use non-English languages, but the core coding terms (e.g., for, if, etc.), are still almost always in English. See also this academic paper: Non-Native English Speakers Learning Computer Programming: Barriers, Desires, and Design Opportunities 20.3.2. Programming Adoption Through Silicon Valley# The book Coding Places: Software Practice in a South American City by Dr. Yuri Takhteyev explores how programming in Brazil differs from programming in Silicon Valley. Dr. Takhteyev points out that since tech companies are centralized in Silicon Valley, this then means Silicon Valley determines which technologies (like programming languages or coding libraries) get adopted. He then compares this to how the art world works: “If you want to show [your art] in Chicago, you must move to New York. He then rewords this for tech: if you want your software to be used widely in Brazil, you should write it in Silicon Valley. We can see this happening in a study by StackOverflow. They found that some technologies which are gaining in popularity in Silicon Valley (Python and R), are not commonly used in poorer countries, whereas programming tech that is considered outdated in Silicon Valley (android and PHP), is much more popular in poorer countries. In his book, Takhteyev tracks the history of the Lua programming language, which was invented in Brazil but became adopted in Silicon Valley. In order to gain popularity in Silicon Valley (and thus the rest of the world), the developers had to make difficult tradeoffs, no longer customizing it for the needs of their Brazilian users.

The tech industry is full of colonialist thinking and practices, some more subtle than others. To begin with, much of the tech industry is centralized geographically, specifically in Silicon Valley, San Francisco, California. The leaders and decisions in how tech operates come out of this one wealthy location in a wealthy nation. Then, much of tech is dependent on exploiting cheap labor, often in dangerous conditions, in other countries (thus extracting the resource of cheap labor, from places with “inferior” governments and economies). This labor might be physical labor, or dealing with dangerous chemicals, or the content moderators who deal with viewing horrific online content. Tech industry leaders in Silicon Valley then take what they made with exploited labor, and sell it around the world, feeling good about themselves, believing they are benefitting the world with their “superior” products.

19.2.3. How Meta Tries to Corner the Market of Social Media# To increase profits, Meta wants to corner the market on social media. This means they want to get the most users possible to use Meta (and only Meta) for social media. Before we discuss their strategy, we need a couple background concepts: Network effect: Something is more useful the more people use it (e.g., telephones, the metric system). For example, when the Google+ social media network started, not many people used it, which meant that if you visited it there wasn’t much content, so people stopped using it, which meant there was even less content, and it was eventually shut down. Network power: When more people start using something, it becomes harder to use alternatives. For example, Twitter’s large user base makes it difficult for people to move to a new social media network, even if they are worried the new owner is going to ruin it, since the people they want to connect with aren’t all on some other platform. This means Twitter can get much worse and people still won’t benefit from leaving it. Let’s look at a scene from the movie The Social Network (about the origins of Facebook), where Sean Parker (who created the music-sharing app Napster) talks to Facebook founders Mark Zuckerberg and Eduardo Saverin about their strategy to grow Facebook: In that clip, you will notice strategies for trying to use the network effect (though they don’t call it that) by targeting specific users to try to make Facebook more desirable than competitors. They also discuss how they could start running ads now (making them a million dollars). But instead, if they don’t sell ads now (running the company at a loss) then they can maximize their growth. Then, when they have grown much larger and have enough network power, users won’t quit when they start selling ads later (and they’ll make a billion dollars). So, looking back at Meta’s goal (getting the most users possible to use Meta, and only Meta for social media), let’s look at some obstacles and how Meta tries to overcome these obstacles: Obstacle: Users don’t want ads on Facebook Solution: No ads until Facebook has attracted enough users (network power) so that users won’t leave when ads are introduced (Facebook introduced ads in 2007) Obstacle: People speak different languages Solution: Increase language support of Facebook so more people can use the site Obstacle: Not everyone has the internet Solution: Give them free internet, but push them to Facebook while doing so (called Free Basic) Obstacle: A competing company social media company has a user base (e.g., Instagram, Snapchat) Solution: Try to purchase the company, or copy their features

Related Terms# Here are a few more terms that are relevant to capitalism that we need to understand in order to get to the details of decision-making and strategies employed by social media companies. Shares / Stocks Shares or stocks are ownership of a percentage of a business, normally coming with getting a percentage of the profits and a percentage of power in making business decisions. Companies then have a board of directors who represent these shareholders. The board is in charge of choosing who runs the company (the CEO). They have the power to hire and fire CEOs For example: in 1985, the board of directors for Apple Computers denied Steve Jobs (co-founded Apple) the position of CEO and then they fired him completely CEOs of companies (like Mark Zuckerberg of Meta) are often both wage-laborers (they get a salary, Zuckerberg gets a tiny symbolic $1/year) and shareholders (they get a share of the profits, Zuckerberg owns 16.8%) Free Market Businesses set their own prices and customers decide what they are willing to pay, so prices go up or down as each side decides what they are willing to charge/spend (no government intervention) See supply and demand What gets made is theoretically determined by what customers want to spend their money on, with businesses competing for customers by offering better products and better prices Especially the people with the most money, both business owners and customers Monopoly “a situation where a specific person or enterprise is the only supplier of a particular thing” Monopolies are considered anti-competitive (though not necessarily anti-capitalist). Businesses can lower quality and raise prices, and customers will have to accept those prices since there are no alternatives. Cornering a market is being close enough to a monopoly to mostly set the rules (e.g., Amazon and online shopping) 19.1.2. Socialism# Let’s contrast capitalism with socialism: Socialism, in contrast is a system where: A government owns the businesses (sometimes called “government services”) A government decides what to make and what the price is the price might be free, like with public schools, public streets and highways, public playgrounds, etc. A government then may hire wage laborers at predetermined rates for their work, and the excess business profits or losses are handled by the government For example, losses are covered by taxes, and excess may pay for other government services or go directly to the people (e.g., Alaska uses its oil profits to pay people to live there). As an example, there is one Seattle City Sewer system, which is run by the Seattle government. Having many competing sewer systems could actually make a big mess of the underground pipe system.

For an example of public shaming, we can look at late-night TV host Jimmy Kimmel’s annual Halloween prank, where he has parents film their children as they tell the parents tell the children that the parents ate all the kids’ Halloween candy. Parents post these videos online, where viewers are intended to laugh at the distress, despair, and sense of betrayal the children express. I will not link to these videos which I find horrible, but instead link you to these articles:

Before we talk about public criticism and shaming and adults, let’s look at the role of shame in childhood. In at least some views about shame and childhood1, shame and guilt hold different roles in childhood development: Shamehame is the feeling that “I am bad,” and the natural response to shame is for the individual to hide, or the community to ostracize the person. Guilt is the feeling that “This specific action I did was bad.” The natural response to feeling guilt is for the guilty person to want to repair the harm of their action. In this view, a good parent might see their child doing something bad or dangerous, and tell them to stop. The child may feel shame (they might not be developmentally able to separate their identity from the momentary rejection). The parent may then comfort the child to let the child know that they are not being rejected as a person, it was just their action that was a problem. The child’s relationship with the parent is repaired, and over time the child will learn to feel guilt instead of shame and seek to repair harm instead of hide.

Dogpiling: When a crowd of people targets or harasses the same person. Public Shaming (this will be our next chapter) Cross-platform raids (e.g., 4chan group planning harassment on another platform) Stochastic terrorism The use of mass public communication, usually against a particular individual or group, which incites or inspires acts of terrorism which are statistically probable but happen seemingly at random. See also: An atmosphere of violence: Stochastic terror in American politics

Bullying: like posting public mean messages Impersonation: Making an account that appears to be from someone and having that account say things to embarrass or endanger the victim. Doxing: Publicly posting identifying information about someone (e.g., full name, address, phone number, etc.). Revenge porn / deep-fake porn Etc.

Some ad hoc crowdsourcing can be part of a social or political movement. For example, Social media organizing played a role in the Arab Spring revolutions in the 2010s, and Social Media platforms were a large part of the #MeToo movement, where victims of sexual abuse/harassment spoke up and stood together.

When social media users work together, we can consider what problem they are solving. For example, for some of the Tiktok Duet videos from the virality chapter, the “problem” would be something like “how do we create music out of this source video” and the different musicians contribute their own piece to the solution. For some other examples: In the case of a missing hiker rescued after Twitter user tracks him down using his last-sent photo, the “problem” was “Where did the hiker disappear?” and the crowd investigated whatever they could to find the solution of the hiker’s location. In the case of Canucks’ staffer uses social media to find fan who saved his life, the “problem” was “Who is the fan who saved the Canucks’ staffer’s life?” and the solution was basically to try to identify and dox the fan (though hopefully in a positive way). In the case of Twitter tracks down mystery couple in viral proposal photos, the problem was “Who is the couple in the photo?” and the solution was again to basically dox them, though in the article they seemed ok with it.

Another strategy for content moderation is using bots, that is computer programs that look through posts or other content and try to automatically detect problems. These bots might remove content, or they might flag things for human moderators to review.

If you are running your own site and suddenly realize you have a moderation problem you might have some of your current staff (possibly just yourself) start handling moderation. As moderation is a very complicated and tricky thing to do effectively, untrained moderators are likely to make decisions they (or other users) regret.

Another category is content that users or advertisers might find offensive. If users see things that offend them too often, they might leave the site, and if advertisers see their ads next to too much offensive content, they might stop paying for ads on the site. So platforms might put limits on language (e.g., racial slurs), violence, sex, and nudity. Sometimes different users or advertisers have different opinions on what should be allowed or not. For example, “The porn ban of 2018 was a defining event for Tumblr that led to a 30 percent drop in traffic and a mass exodus of users that blindsided the company.”

In order to make social media sites usable and interesting to users, they may ban different types of content such as advertisements, disinformation, or off-topic posts. Almost all social media sites (even the ones that claim “free speech”) block spam, mass-produced unsolicited messages, generally advertisements, scams, or trolling. Without quality control moderation, the social media site will likely fill up with content that the target users of the site don’t want, and those users will leave. What content is considered “quality” content will vary by site, with 4chan considering a lot of offensive and trolling content to be “quality” but still banning spam (because it would make the site repetitive in a boring way), while most sites would ban some offensive content.

Another form of digital self-harm is through joining toxic negative communities built around tearing each other down and reinforcing a hopeless worldview. (Content warning: sex and self-harm)

People historically came to cosmetic surgeons with photos of celebrities whose features they hoped to emulate. Now, they’re coming with edited selfies. They want to bring to life the version of themselves that they curate through apps like FaceTune and Snapchat.

When physical mail was dominant in the 1900s, one type of mail that spread around the US was a chain letter. Chain letters were letters that instructed the recipient to make their own copies of the letter and send them to people they knew. Some letters gave the reason for people to make copies might be as part of a . Chain letters were letters that instructed the recipient to make their own copies of the letter and send them to people they knew. Some letters gave the reason for people to make copies might be as part of a Some letters gave the reason for people to make copies might be as part of a pyramid scheme where you were supposed to send money to the people you got the letter from, but then the people you send the letter to would give you money. Other letters gave the reason for people to make copies that if they made copies, good things would happen to them, and if not bad things would, like this:Other letters gave the reason for people to make copies that if they made copies, good things would happen to them, and if not bad things would, like this:

When content goes viral there may be many people with a stake in it’s going viral, such as: The person (or people) whose content or actions are going viral, who might want attention, or get financial gain, or might be embarrassed or might get criticism or harassment, etc. Different people involved might have different interests. Some may not have awareness of it happening at all (like a video of an infant). Different audiences might have interests such as curiosity or desire to bring justice to a situation or desire to get attention for themselves or their ideas based on engaging the viral content, or desire to troll or harass others. Social networking platforms might have interests such as increased attention to their platform or increased advertising, or increased or decreased reputation (in views of different audiences). List at least three different scenarios of content going viral and list out the interests of different groups and people in the content going viral.

Since a recommendation algorithm may base its decisions on how users engage with content, the biases of users play into what gets boosted by the algorithm. For example, one common piece of advice on YouTube is for creators to put their faces on their preview thumbnail, but given that many users have a bias against Black people (whether intentional or not), this advice might not work: In preparation for this video, and in just wanting to test out how to improve my channel’s reach, I took my Black face off of pretty much every thumbnail of any video that I’ve made up until this point. And the result was a clear uptick in views on each video that i did this for. Additionally, because of how YouTube categorizes content, if someone tries to make content that doesn’t fill well in the existing categories, the recommendation algorithm might not boost it, or it might boost it in ill-fitting locations. [Two problems happen with Black people trying to make educational content for Black audiences:] Black viewers of educational channels are funneled into white content spaces and Black content creators of educational content are funneled into really non-educational and in many cases toxic anti-Black content spaces.

Content recommendations can go well when users find content they are interested in. Sometimes algorithms do a good job of it and users are appreciative. TikTok has been mentioned in particular as providing surprisingly accurate recommendations, though Professor Arvind Narayanan argues that TikTok’s success with its recommendations relies less on advanced recommendation algorithms, and more on the design of the site making it very easy to skip the bad recommendations and get to the good ones.

Some users might not be able to see images on websites for a variety of reasons. The user might be blind or low-vision. Their device or internet connection might not support images. Or perhaps all the images got deleted (like what happened to The Onion). In order for these users to still get the information intended from the images, the image can come with alt-text. You can read more about alt-text in . You can read more about alt-text in this New York Times feature Reddit unfortunately doesn’t allow alt-text for their images. So while we were going to have a programming demo here to look up the alt-text, there is no alt-text on images uploaded to Reddit to look up, meaning this site is unfriendly to blind or low-vision users.

If a building only has staircases to get up to the second floor (it was built assuming everyone could walk up stairs), then someone who cannot get up stairs has a disability in that situation. If a physical picture book was made with the assumption that people would be able to see the pictures, then someone who cannot see has a disability in that situation. If tall grocery store shelves were made with the assumption that people would be able to reach them, then people who are short, or who can’t lift their arms up, or who can’t stand up, all would have a disability in that situation. If an airplane seat was designed with little leg room, assuming people’s legs wouldn’t be too long, then someone who is very tall, or who has difficulty bending their legs would have a disability in that situation.

Social engineering, where they try to gain access to information or locations by tricking people. For example: Phishing attacks, where they make a fake version of a website or app and try to get you to enter your information or password into it. Some people have made malicious QR codes to take you to a phishing site. Many of the actions done by the con-man Frank Abagnale, which were portrayed in the movie Catch Me If You Can

There might be some things that we just feel like aren’t for public sharing (like how most people wear clothes in public, hiding portions of their bodies) We might want to discuss something privately, avoiding embarrassment that might happen if it were shared publicly We might want a conversation or action that happens in one context not to be shared in another (context collapse) We might want to avoid the consequences of something we’ve done (whether ethically good or bad), so we keep the action or our identity private We might have done or said something we want to be forgotten or make at least made less prominent We might want to prevent people from stealing our identities or accounts, so we keep information (like passwords) private We might want to avoid physical danger from a stalker, so we might keep our location private We might not want to be surveilled by a company or government that could use our actions or words against us (whether what we did was ethically good or bad)

One thing to note in the above case of candle reviews and COVID is that just because something appears to be correlated, doesn’t mean that it is connected in the way it looks like. In the above, the correlation might be due mostly to people buying and reviewing candles in the fall, and diseases, like COVID, spreading most during the fall. It turns out that if you look at a lot of data, it is easy to discover spurious correlations where two things look like they are related, but actually aren’t. Instead, the appearance of being related may be due to chance or some other cause. For example: Fig. 8.3 An example spurious correlation from Tyler Vigen’s collection of Spurious Correlations# By looking at enough data in enough different ways, you can find evidence for pretty much any conclusion you want. This is because sometimes different pieces of data line up coincidentally (coincidences happen), and if you try enough combinations, you can find the coincidence that lines up with your conclusion. If you want to explore the difficulty of inferring trends from data, the website fivethirtyeight.com has an interactive feature called “Hack Your Way To Scientific Glory” where, by changing how you measure the US economy and how you m

Online advertisers can see what pages their ads are being requested on, and track users across those sites. So, if an advertiser sees their ad is being displayed on an Amazon page for shoes, then the advertiser can start showing shoe ads to that same user when they go to another website. across those sites. So, if an advertiser sees their ad is being displayed on an Amazon page for shoes, then the advertiser can start showing shoe ads to that same user when they go to another website. Additionally, social media might collect information about non-users, such as when a user posts a picture of themselves with a friend who doesn’t have an account, or a user shares their phone contact list with a social media site, some of whom don’t have accounts (about non-users, such as when a user posts a picture of themselves with a friend who doesn’t have an account, or a user shares their phone contact list with a social media site, some of whom don’t have accounts (Facebook does this).

We can trace Internet trolling to early social media in the 1980s and 1990s, particularly in early online message boards and in early online video games. In the early Internet message boards that were centered around different subjects, experienced users would “troll for newbies” by posting naive questions that all the experienced users were already familiar with. The “newbies” who didn’t realize this was a troll would try to engage and answer, and experienced users would feel superior and more part of the group knowing they didn’t fall for the troll like the “newbies” did. These message boards are where the word “troll” with this meaning comes from. One set of the early Internet-based video games were Multi-User Dungeons (MUDs), where you were given a text description of where you were and could say where to go (North, South, East, West) and text would tell you where you were next. In these games, you would come across other players and could type messages or commands to attack them. These were the precursors to more modern Massively multiplayer online role-playing games (MMORPGS). In these MUDs, players developed activities that we now consider trolling, such as “Griefing” where one player intentionally causes another player “grief” or distress (such as a powerful player finding a weak player and repeatedly killing the weak player the instant they respawn), and “Flaming” where a player intentionally starts a hostile or offensive conversation.

Trolling is when an Internet user posts inauthentically (often false, upsetting, or strange) with the goal of causing disruption or provoking an emotional reaction. When the goal is provoking an emotional reaction, it is often for a negative emotion, such as anger or emotional pain. When the goal is disruption, it might be attempting to derail a conversation (e.g., concern trolling), or make a space no longer useful for its original purpose (e.g., joke product reviews), or try to get people to take absurd fake stories seriously.

Since we have different personas and ways of behaving in different groups of people, what happens if different groups of people are observing you at the same time? For example, someone might not know how to behave if they were at a restaurant with their friends and they noticed that their parents were seated at the table next to them. This is phenomenon is called “context collapse.”

When someone presents themselves as open and as sharing their vulnerabilities with us, it makes the connection feel authentic. We feel like they have entangled their wellbeing with ours by sharing their vulnerabilities with us. Think about how this works with celebrity personalities. Jennifer Lawrence became a favorite of many when she tripped at the Oscars, and turned the moment into her persona as someone with a cool-girl, unpolished, unfiltered way about her. She came across as relatable and as sharing her vulnerabilities with us, which let many people feel that they had a closer, more authentic connection with her. Over time, that persona has come to be read differently, with some suggesting that this open-styled persona is in itself also a performance. Does this mean that her performance of vulnerability was inauthentic?

4Chan has various image-sharing bulletin boards, where users post anonymously. Perhaps the most infamous board is the “/b/” board for “random” topics. This board emphasizes “free speech” and “no rules” (with exceptions for child pornography and some other illegal content). In these message boards, users attempt to troll each other and post the most shocking content they can come up with. They also have a history of collectively choosing a target website or community and doing a “raid” where they all try to join and troll and offend the people in that community.

2003 saw the launch of several popular social networking services: Friendster, Myspace, and LinkedIn. These were websites where the primary purpose was to build personal profiles and create a network of connections with other people, and communicate with them. Facebook was launched in 2004 and soon put most of its competitors out of business, while YouTube, launched in 2005 became a different sort of social networking site built around video.

As you can see in the apple example, any time we turn something into data, we are making a simplification.1 If we are counting the number of something, like apples, we are deciding that each one is equivalent. If we are writing down what someone said, we are losing their tone of voice, accent, etc. If we are taking a photograph, it is only from one perspective, etc.

Can you think of an example of pernicious ignorance in social media interaction? What’s something that we might often prefer to overlook when deciding what is important?

On the other hand, some bots are made with the intention of harming, countering, or deceiving others. For example, people use bots to spam advertisements at people. You can use bots as a way of buying fake followers, or making fake crowds that appear to support a cause (called Astroturfing).

In this example, some clever protesters have made a donkey perform the act of protest: walking through the streets displaying a political message. But, since the donkey does not understand the act of protest it is performing, it can’t be rightly punished for protesting. The protesters have managed to separate the intention of protest (the political message inscribed on the donkey) and the act of protest (the donkey wandering through the streets). This allows the protesters to remain anonymous and the donkey unaware of it’s political mission.

When one of us ran the program, who made those reddit posts (me? you? the bot?)? Notice that there are at least three times of actions for posting reddit post with this bot, one is when the code was originally written, another is when the code was modified, and and the other is when the code is run. These could even be done by different people. How do you divide out responsibility for a bots actions between the person writing the code and the person running the program?

采取与宇宙自然循环和谐一致的非受迫行动。试图强迫某件事发生可能会适得其反。 拒绝儒家对仪式/仪式的关注。喜欢自发性和玩耍