If you could magically change anything about how people behave on social media, what would it be?

You aren’t likely to end up in a situation as dramatic as this. If you find yourself making a stand for ethical tech work, it would probably look more like arguing about what restrictions to put on a name field (e.g., minimum length), prioritizing accessibility, or arguing that a small piece of data about users is not really needed and shouldn’t be tracked. But regardless, if you end up in a position to have an influence in tech, we want you to be able to think through the ethical implications of what you are asked to do and how you choose to respond.

What if social media sites were governed by their users instead of by shareholders (e.g., governed by the subjugated instead of the colonialists)? How would users participate in decision-making? Would non-users have a say (e.g., if the whole user base decides to harass a group of non-users)? How do you think the sites would work differently?

In what ways do you see capitalism, socialism, and other funding models show up in the country you are from or are living in?

18.3.4. Enforcing Norms# In the philosophy paper Enforcing Social Norms: The Morality of Public Shaming, Paul Billingham and Tom Parr discuss under what conditions public shaming would be morally permissible. They are concerned not with actions primarily intended to induce shame in the target, but rather actions that may cause a person to shame, but are motivated by “seeking to draw attention to a social norm violation, and to rally others to their cause.” In this situation, they outline the following constraints that must be considered when publicly shaming someone in this way: Proportionality: The negative consequences of shaming someone should not be worse than the positive consequences Necessity: There must not be another more effective method of achieving the goal Respect for Privacy: There must not be unnecessary violations of privacy Non-Abusiveness: The shaming must not use abusive tactics. Reintegration “Public shaming must aim at, and make possible, the reintegration of the norm violator back into the community, rather than permanently stigmatizing them.”

In South Africa, when the oppressive and violent racist apartheid system ended, Nelson Mandela and Desmond Tutu set up the Truth and Reconciliation Commission. The commission gathered testimony from both victims and perpetrators of the violence and oppression of apartheid. We could also consider this, in part, a large-scale public shaming of apartheid and those who hurt others through it. Unlike the Nuremberg Trials, the Truth and Reconciliation Commission gave a path for forgiveness and amnesty to the perpetrators of violence who provided their testimony.

Do you believe crowd harassment is ever justified?

Have you experienced or witnessed harassment on social media (that you are willing to share about)?

In what ways do you think you’ve participated in any crowdsourcing online?

16.2.1. Crowdsourcing Platforms# Some online platforms are specifically created for crowdsourcing. For example: Wikipedia: Is an online encyclopedia whose content is crowdsourced. Anyone can contribute, just go to an unlocked Wikipedia page and press the edit button. Institutions don’t get special permissions (e.g., it was a scandal when US congressional staff edited Wikipedia pages), and the expectation that editors do not have outside institutional support is intended to encourage more people to contribute. Quora: An crowdsourced question and answer site. Stack Overflow: A crowdsourced question-and-answer site specifically for programming questions. Amazon Mechanical Turk: A site where you can pay for crowdsourcing small tasks (e.g., pay a small amount for each task, and then let a crowd of people choose to do the tasks and get paid). Upwork: A site that lets people find and contract work with freelancers (generally larger and more specialized tasks than Amazon Mechanical Turk. Project Sidewalk: Crowdsourcing sidewalk information for mobility needs (e.g., wheelchair users). 16.2.2. Example Crowdsourcing Tasks# You probably already have some ideas of how crowds can work together on things like editing articles on a site like Wikipedia or answer questions on a site like Quora, but let’s look at some other examples of how crowds can work together. Fold-It is a game that lets players attempt to fold proteins. At the time, researchers were having trouble getting computers to do this task for complex proteins, so they made a game for humans to try it. Researchers analyzed the best players’ results for their research and were able to publish scientific discoveries based on the contributions of players.

15.1.5. Volunteer Moderation# Letting individuals moderate their own spaces is expecting individuals to put in their own time and labor. You can do the same thing with larger groups and have volunteers moderate them. Reddit does something similar where subreddits are moderated by volunteers, and Wikipedia moderators (and editors) are also volunteers.

Have you ever reported a post/comment for violating social media platform rules?

Are there ways social media sites can be designed to be better for the mental health of its users?

In what ways have you found social media bad for your mental health and good for your mental health?

12.3.3. “Natural” Selection# It isn’t clear what should be considered as “nature” in a social media environment (human nature? the nature of the design of the social media platform? are bots unnatural?), so we’ll just instead talk about selection. When content (and modified copies of content) is in a position to be replicated, there are factors that determine whether it gets selected for replicated or not. As humans look at the content they see on social media they decide whether they want to replicate it for some reason, such as: “that’s funny, so I’ll retweet it” “that’s horrible, so I’ll respond with an angry face emoji” “reposting this will make me look smart” “I am inspired to use part of this to make a different thing” Groups and organizations make their own decisions on what social media content to replicate as well (e.g., a news organization might find a social media post newsworthy, so they write articles about it). Additionally, content may be replicated because of: Paid promotion and ads, where someone pays money to have their content replicated Astroturfing: where crowds, often of bots, are paid to replicate social media content (e.g., like, retweet)

12.2. Pre-internet Virality Examples

Sometimes though, individuals are still blamed for systemic problems. For example, Elon Musk, who has the power to change Twitters recommendation algorithm, blames the users for the results:

What experiences do you have of social media sites making particularly bad recommendations for you? { requestKernel: true, binderOptions: { repo: "binder-examples/jupyter-stacks-datascience", ref: "master", }, codeMirrorConfig: { theme: "abcdef", mode: "python" }, kernelOptions: { kernelName: "python3", path: "./ch11_recommendations" }, predefinedOutput: true } kernelName = 'python3'

What incentives to social media companies have to violate privacy?

Others Posting Without Permission: Someone may post something about another person without their permission. See in particular: The perils of ‘sharenting’: The parents who share too much

Some people (like many with chronic pain) would welcome a cure that got rid of their disability. Others (like many autistic people), are insulted by the suggestion that there is something wrong with them that needs to be “cured,” and think the only reason autism is considered a “disability” at all is because society doesn’t make reasonable accommodations for them the way it does for neurotypical people.

Different societies and groups of people make different assumptions about what people can do, and so what is considered a disability in one group, might just be “normal” in another.

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.

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 (Facebook does this).

There is a reason why stereotypes are so tenacious: they work… sort of. Humans are brilliant at finding patterns, and we use pattern recognition to increase the efficiency of our cognitive processing. We also respond to patterns and absorb patterns of speech production and style of dress from the people around us. We do have a tendency to display elements of our history and identity, even if we have never thought about it before. This creates an issue, however, when the stereotype is not apt in some way. This might be because we diverge in some way from the categories that mark us, so the stereotype is inaccurate. Or this might be because the stereotype also encodes value judgments that are unwarranted, and which lead to problems with implicit bias. Some people do not need to think loads about how they present in order to come across to people in ways that are accurate and supportive of who they really are. Some people think very carefully about how they curate a set of signals that enable them to accurately let people know who they are or to conceal who they are from people outside their squad.

Have you witnessed different responses to trolling? What happened in those cases? What do you think is the best way to deal with trolling?

How do you notice yourself changing how you express yourself in different situations, particularly on social media? Do you feel like those changes or expressions are authentic to who you are, do they compromise your authenticity in some way? { requestKernel: true, binderOptions: { repo: "binder-examples/jupyter-stacks-datascience", ref: "master", }, codeMirrorConfig: { theme: "abcdef", mode: "python" }, kernelOptions: { kernelName: "python3", path: "./ch06_authenticity" }, predefinedOutput: true } kernelName = 'python3'

Catfishing: Create a fake profile that doesn’t match the actual user, usually in an attempt to trick or scam someone

The 1980s and 1990s also saw an emergence of more instant forms of communication with chat applications. Internet Relay Chat (IRC) lets people create “rooms” for different topics, and people could join those rooms and participate in real-time text conversations with the others in the room.

Graffiti and other notes left on walls were used for sharing updates, spreading rumors, and tracking accounts Books and news write-ups had to be copied by hand, so that only the most desired books went “viral” and spread

Later, sometime after the printing press, Stondage highlights how there was an unusual period in American history that roughly took up the 1900s where, in America, news sources were centralized in certain newspapers and then the big 3 TV networks. In this period of time, these sources were roughly in agreement and broadcast news out to the country, making a more unified, consistent news environment (though, of course, we can point out how they were biased in ways like being almost exclusively white men). Before this centralization of media in the 1900s, newspapers and pamphlets were full of rumors and conspiracy theories. And now as the internet and social media have taken off in the early 2000s, we are again in a world full of rumors and conspiracy theories.

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. Different simplifications are useful for different tasks. Any given simplification will be helpful for some tasks and be unhelpful for others. See also, this saying in statistics: All models are wrong, but some are useful

Numbers# Numbers are normally stored in two different ways: Integer: whole numbers like 5, 37, -10, and 0 Floating point numbers: these can represent decimals like: 0.75, -1.333, and 3 x 10 ^ 8 Fig. 4.5 The number of replies, retweets, and likes can be represented as integer numbers (197.8K can be stored as a whole number like 197,800).# Click to see example Python code # Save an integer value in a variable called num_tweet_likes num_tweet_likes = 197800 # Save an integer value in a variable called max_tweet_length max_tweet_length = 280 # Save a floating point number in a variable called average_tweet_length average_tweet_length = 133.5 Copy to clipboard When computers store numbers, there are limits to how much space is can be used to save each number. This limits how big (or small) the numbers can be, and causes rounding with floating-point numbers. Additionally, programming languages might include other ways of storing numbers, such as fractions, complex numbers, or limited number sets (like only positive integers). Strings (Text)# Computers typically store text by dividing the text into characters (the individual letters, spaces, numerals, punctuation marks, emojis, and other symbols). These characters are then stored in order and called strings (that is a bunch of characters strung together, like in Fig. 4.6 below). Fig. 4.6 A physical string of the characters: “H”, “A”, “P”, “P”, “Y”, ” “, “B”, “I”, “R”, “T”, “H”, “D”, “A”, “Y”. (image source)# In our example tweet, we can see some different pieces of information that might be represented with strings: Fig. 4.7 The user name, twitter handle, and the tweet text can all be represented with strings.#

Google: “Most useful Instagram bots” Google: “Funniest Twitter bots” Read through the Reddit “botwatch” subreddit Read through a list of registered bots on Wikipedia

After the Star Wars: Last Jedi was released, there was a significant online backlash. When a researcher looked into it: [Morten] Bay found that 50.9% of people tweeting negatively about “The Last Jedi” were “politically motivated or not even human,” with a number of these users appearing to be Russian trolls. The overall backlash against the film wasn’t even that great, with only 21.9% of tweets analyzed about the movie being negative in the first place.

The photo above shows the ENIAC computer (built with US Army funds in 1945, this was the first electronic general-purpose computer), being programmed by three of the six women who were the original programmers on this computer: Kay McNulty, Betty Jennings, Betty Snyder, Marlyn Meltzer, Fran Bilas, and Ruth Lichterman.

Taoism# Act with unforced actions in harmony with the natural cycles of the universe. Trying to force something to happen will likely backfire. Rejects Confucian focus on ceremonies/rituals. Prefers spontaneity and play. Like how water (soft and yielding), can, over time, cut through rock.