Activists Are Hidden (Blog Post #4)

Algorithmic criticism is the act of taking formulas that have been implanted to make life more efficient and looking into how they were made to see if any assumptions were planted without proper evidence to support it. In essence, anything can be false. In order to be better consumers of media through these algorithms, we must deny their objectivity and choose to question them. It’s crucial we see that there’s a dynamic of what makes the most profit, who is in power, what is the algorithm trying to accomplish, and is it actually the truth? 1 In the era of fake news, we must continue to be skeptical of everything. 

The Long Civil Rights Movement impacted the 1930s because it was expanding at that time. There were crucial strides in Black liberation and the beginning of the demand for new rights. None of them gained as much traction as they have now, but they were still taking place and gaining members. The NAACP’s anti-lynching campaign encouraged Roosevelt to fulfill their desires.

2

The communist led International Labor Defense also rallied for African-American rights at the time and aided them with lawyers and other essentials they needed to continue their fight for equal rights. The groundwork laid for the future is evident. The organizations and their goals from the 1930s are still implemented today. 

I do think there are connections with the digital activists and the WPA activists. Both of them are attempting to see the structures in place and ask: How can I show, through art and the things we already have, how these structures are misguided and have underlying implications?

3

. I think that any artist is in someway, an activist. And I think glitching can be considered an art or artistic in nature. So, by extension, they are activists. They may not be applying the same topics but they intend to achieve the same goal. 

All of these activists were quiet or silenced for the majority of the 1930s but they chose to keep fighting for the equal rights we are still striving for today.

Algorithms and Feminism

I was not aware of the effect of inaccurate algorithms on society. Cathy O’Neil explains algorithms in her talk “The Truth About Algorithms”. She defines an algorithm as basically mathematical opinions and all that is needed for form them is a data set and a definition of success. Cathy makes an interesting point when she explains how her definition of a successful meal differs from her sons definition. Algorithms can be racist, sexist and bias and completely untrue. It is necessary to try to develop a way for these algorithms to be fair. People can lose their jobs, lose money and much more because of a faulty algorithm. Companies are now having the idea of being transparent in their algorithms. Basically so individuals can see how the algorithm is made and on what terms and bases. But in my opinion I don’t see how this is being completely fair. People can now see what they were judged on but also is that judgement is still coming from an opinion? I am open to the idea and I understand how being transparent is better than being left in the dark.

In the 1930s and into the 1940s women were just starting to emerge as workers. The American Yawp explains how during this time women began to take roles in office and Eleanor Roosevelt was a strong first lady who took charge and strived for change. Although even with the few successes of women in office the New Deal programs were essentially built for men. The spark for change was lit in the 1930s and has continued to burn ever since. Women are still fighting for equal rights and I believe will continue until successful. Pay differences in the workplace is one of the main changes I hear about still. 

Blog post #4

The Long Civil Rights Movement (LCRM) was attempting to edit the pervasive and popular narratives about Black Americans that were foundational to their original subjugation in real time. This long running tradition of marginalized communities altering the status quo of the country from racism, sexism, and classism, towards a more inclusive future is what in part undergirds some work that digital activists engage in.

 This new wave of digital activism is publicly interrogating the conceit that the way data and information is displayed for our consumption and use is neutral rather than a direct extension of the reality in which we already exist. Cathy O’ Neil suggests that we should “stop trusting algorithms to be fair”4 because our technology is essentially a mirror of our society. People themselves are rarely fair and tend more towards being self-serving and most interested in preserving their own narratives particularly when profit making is involved.  Rather than believing that what we find first in our searches is most common or most often true, we should read more closely in order to understand “the material conditions on which these results are predicated” 5.

A certain level of interrogation is needed to untangle who has decided what we see first, how we should interact with it, and whether or not it is true. This kind of media literacy is often not taught because we have been fed notions of popularity and neutrality as the obvious default.

Interestingly enough when companies like Google are reprimanded for the product that they have created, they often relegate the blame towards the public rather than the inherit flaws in their programming and algorithms. This is the same work that oppressive institutions have been doing generations. Although you can be an accomplice in a system of which you are not an architect, the blame cannot only lie with individuals. The LCRM particularly was predicated on the notion of small legal victories to eventually change the tableau of democracy rather that a complete overhaul of the system. This of course is because it is often extremely difficult to dismantle something that you did not build.

If digital activists can continue to apply pressure to the companies that are responsible for enforcing the status quo (in the same way that the LCRM applied legal pressure to the legal establishment) perhaps we will be able to see our technology made more intersectional, accessible, and accurate.

Blog Post #4

Algorithmic criticism is the process of people realizing that algorithms, specifically those of popular search engines have specific biases based on those who created these algorithms. Cathy O’Neil, in her video The Truth About Algorithms states,”To build an algorithm we need only two things; a historical data set and a definition of success.” 6 We can see how this presents a problem when the people creating the algorithms have a different definition of success than their audience. Scholars in this field have suggested that the majority of the people creating these algorithms come from similar social and economic backgrounds which influence these search results and in turn influence the people using the search engines. To combat this people not only need to diversify the field that is programming these algorithms, but become less reliant on immediate search results. These algorithms are not only biased towards socio-economic means but also fall into the hands of advertisements and properties that provide the greatest profits for the people creating these search engines. Becoming technologically aware of the bias of these search engines and not taking the first page of google as solid fact will be a huge step in combating biased algorithmic programming. This problem can be related to the 1930s and the feminist and popular front movements which sought to combat bias in American social perspectives towards women and people of color. The members of these organizations in the past strove to change the American mentality and to prove that women and people of color were just as deserving of voting rights and equal pay. These issues are resurfacing today in algorithmic bias. Safiya Noble writes in her book Algorithms of Oppression, “…Content is already being screened and assessed according to a continuum of values that largely reflect U.S.-based social norms, and these norms reflect a number of racist and stereotypical ideas that make screening racism and sexism and the abuse of humans in racialized ways ‘in’ and perfectly acceptable, while other ideas such as the abuse of animals (which is also unacceptable) are ‘out’ and screened or blocked from view.” 7 She points out that we are facing a new era of racial and sexual based discrimination that is determined by a certain class of people and allowing it to influence American social norms, the WPA activists of the 1930s thought that they had won the battle but it is simply resurfacing in a new way.

Bias in Algorithms

Widely unknown to the public, search engines are extremely biassed. The algorithms that were created for these search engines typically show websites that paid to be shown first or perhaps they show websites that have been most clicked on in the past, which still doesn’t take into account the relevancy of the information.

The algorithms of search engines tend to present racist and sexist information about women, most namely women of color. 8 Once the term “black girls” was searched in Google in the early ’10s, hypersexualized and derogatory results came up. These results speak to the algorithm that created it, instead of showing results about famous black women throughout history or the accomplishments of these women through the years, it instead showed pornographic results which implies that these women of color are shown as objects. Algorithms are developed by humans, and this bias in search results, the racism and sexism in today’s era is still prevalent.

Today’s bias in algorithms play into the Long Civil Rights Movement, where racial and gender equality have yet to be met but are on the path to be. Back in the 1930’s, women did not have the rights that they have today. Although women were starting to join the workforce as the men were off at war, they were still seen as belonging in a domestic environment. Today, women are seen doing incredible things, they’re seen in government positions, as doctors, and soldiers. But when searching for women on the internet, objectifying results still come up. And why? It’s because of the bias in today’s society towards women which is reflected in these major algorithms.

There is a way that today’s society can combat try and combat this bias. Algorithms have to be questioned 9 and users should look at what the results cater to. Do the results cater to those who pay for advertisements? Do they cater to only one race instead of including a multitude of races? Do they present gender inequality? These questions should be asked when using a search engine. It’s important to realize that finding information does not only have to be through Google Searching. There are a wide variety of public resources such as libraries, teachers, and even online databases. In questioning the method of how search results come up and in finding other ways to research information, society can be better consumers of digital media and not give into the bias of algorithmic results.

Blog Post #4

Algorithmic Criticism is “human-based criticism with computers”. It is how we research, often organize our thoughts, and how we put them into words through search engines 10. According to O’Neill’s video, algorithms are an “opinion bedded in-math that can be sexist, racist, and even perpetrate structural inequality.”11. Though scholars and activists suggest that ethics be built into algorithms so that they are fair, transparent, and kept accountable.


In Noble’s excerpt, the same ideals of algorithmic criticism are looked at. She discusses the prejudice against black women and how they are sexualized and even degraded through these various searches. Noble includes that “Internet users have no idea how these ideas come to dominate search results…”. However, this is due to how the algorithms have been created. Rather than they be built to provide recourse, which is the ability for people to modify the outcome, they are based on mere human judgement and there is no way around it.

During the 1930’s, movements such as the Long Civil Rights Movement, Feminism, and the Popular Front impacted the era as it had much to do with politics, race, gender, and social class. The Long Civil Rights Movement placed emphasis on the fact that the Civil Rights movement started well before the 1960’s. The movement not only aimed to create equal rights for African Americans but, in turn served a purpose in the Feminist movement. Women of all backgrounds sought for equal rights; which included being able to enter the workforce and exercise their right to vote.
As a result, these movements paved the way for many of us today, especially women and people of color. More women have entered the workforce and both men and women can freely exercise their right to vote. The LCRM granted African Americans equal rights that only their white counterparts could exercise.

The WPA- era was known to be one of the motivating factors in reinvigorating the economy. Today, digital activism has used technology as a platform for mass mobilization and political action. It has allowed for significant changes into this new age of technology. Calling out the wrongdoings of this country and doing more to promote and bring awareness to ethics and social justice. Like the WPA- era activists, who worked to employ job- seeking individuals to perform public work projects, digital activists use internet platforms like social media to create movements that have proven to be a tool to spread an agenda or political message. Movements like #BlackLivesMatter and Arab Spring Uprising are just a few examples.

References:

Cpotter. (2016, October 24). Toward Algorithmic Criticism. Retrieved from https://blogs.newschool.edu/digitalhumanities/2016/10/24/toward-algorithmic-criticism/

O’ Neil, Cathy. (2019, October 9). The Truth about Algorithms. Video retrieved from http://jessicadoeshistory.com/cnd/exhibits/show/fall-2019/critical

Noble. (n.d.). Algorithms of Oppression Excerpt. Retrieved from https://www.dropbox.com/sh/l0nncfvgpnd5s59/AABVeDfbIkwnJdX6YEjXGHkBa/Readings?dl=0&preview=Noble%2C+Algorithms+of+Oppression+excerpt.pdf&subfolder_nav_tracking=1

Blog Post #4-Critical DH

A legacy from the 1930s activists that has carried into today is the fight for gender and racial equality. The Long Civil Rights Movement, or Long Civil Rights Era as it is depicted in Ritterhouse’s introduction, asked the question of whether African Americans would be a present part of the democracy of the country in the future. 12 This was the beginning of the decades-long fight for equality as 1930s era regulations consistently kept African American people out as beneficiaries of governmental organizations.

Algorithmic criticism is said to be an important concept for the consumers of digital media, as we need to remain aware of what these programs are actually computing. O’Neill, in the video reviewed in class, referenced the idea that algorithms are generated by the opinion of a human which is then embedded into code. As a result of the human component, the algorithm is inherently biased.

In O’Neill’s Ted Talk, she mentions a current issue surrounding the normalized use of algorithms in the hiring process within the country’s biggest companies. Her example, Fox News, spoke to a problem in which their computer program is set to hire professionals who exhibit certain qualities and skills that they deem desirable. However, this has caused friction in the case of gender equality because Fox has promoted largely men in their recent history, which led the algorithms to weed out potential female employees, as they were not the ones promoted, thus they did not have the sought after traits. This concept of equality was a large focus with the Feminism and Popular Front groups as well as the issue of racial equality.

Similarly, Noble, in Algorithms of Oppression, speaks to this same issue, but highlights its presence in popular entries in search engines. In this piece, African American women are said to face discrimination for both their race and their gender, and that this is evident when searching for a simple term about their defining characteristics, and the result is not much more than questionable and offensive results. 13 An important note that the author makes is that we as consumers do not even take notice of the wrongdoings of the media in these circumstances until it is forcefully brought to our attention.

Algorithm Analysis- Blog Post #4

Algorithmic criticism is extremely important today. The internet gives us access to incredible amounts of information, and algorithms control how that information is presented to us.14 I always thought that the algorithms were presented based on the data recorded from my previous interactions with searches and which websites I visited, so finding out that really the algorithm isn’t so much individualized as it is democratic, and focused on general search results from everyone who uses Google, was a little jarring.15 Media and the depictions of minorities, specifically black men and women, have always been skewed. In the 1930’s, the NAACP used media to gain support for an anti-lynching bill, (that disgustingly ended up failing to pass) and this led to the NAACP becoming the top organization in regards to the interests of African Americans. However, at the same time, racist political cartoons, commentary, and advertising were commonplace.

Today, the concerns and difficulties that people of color face have a much more public platform, and in general, people are paying more attention. So why is it when Noble searched “black girls” on Google, the first page was all pornography?16 Is this a representation of the greater public’s opinion on black women? Or is this just a disturbing side effect of the use of artificial intelligence in data gathering for search results? It’s extremely disturbing that searching the word “Jew” on Google brings up antisemitic websites, and it’s not that this is an issue that Google cannot avoid. France and Germany both have laws in place that ban the sale of Nazi memorabilia. When you Google Jew in France, the antisemitic sites don’t come up in the search results (this is still a fact- I asked my French step dad). So it is possible to make sure that certain results don’t appear. Why hasn’t this technology been applied in the United States? As usual, search results, internet presence, and advertising is portrayed through the male gaze. There is very little intersectionality online, and there was very little intersectionality in the WPA era. At this point, in 2019, I’m really questioning what has to happen in order for the concerns and portrayal of minorities online and in algorithms to be accurate and not based off some inaccurate stereotype.

Citations:

In class discussion, October 9th, Professor Jess

Noble, Algorithms of Oppression

The Truth About Algorithms, Cathy O’Neil

Blog Post #4 – How I feel about Digital History

Algorithmics are something the everyday person overlooks all the time. We have become oblivious to them, most of the time not even realizing they exist. However, there are some people who do and point out the many problems with them that the average eye over looks. Those people are the Algorithmic Critics, they criticize the everyday algorithms and see if they are actually benefiting us. There are many different things that use algorithms some are: Google, Corporations, Banks, Mathematics etc.  Even though algorithms are most of the time made out of good intentions they tend to leave out the minorities or overlook really important aspects all because of one thing that doesn’t follow the programming’s guide lines. Many things are taken into account when making an algorithm but majority of the time its what the person making it thinks will lead to success and profit. 16

In her book Algorithms of oppression Noble talks about how when she searches up “black girls” results referring to pornographic things showed up. 17 Althought back in the 1930’s there was not Google women we’re often objectified as the reason why men are so weak because of how sexual they are. This goes back to the Greek-Roman times where women were seen as evil because of this, often depicted as monsters that lore men to their death with their sexual appearances. 18  Although women were not seen as evil sexual beings like in the Greek roman times they have always been underestimated. That does not help if you are also a woman of color, who tend to be treated worse. In the 1930’s women were expected to always look pretty, keep the house clean, not bring any money in or being in control of the bills, and bare/take care of the kids. The man of the household was supposed to work, then come home, eat the dinner that the wife prepared, pay the bills, and sleep. 19

 To an extent it is still like this today, although I feel throughout the years we aren’t as extreme about it as we used to be and tend to have very good support in the community when someone is mistreated. The WPA actives are close to the things we have in the present, in regard to people fighting back against women being treated unfairly. Today we still have protests of women fighting against the anti-feminists, women not being paid the same as men, and so forth. As I said before in todays age it is not as extreme as the 1930’s and I our community has a better understanding of how women are as equal as men there are just a few things we are still fighting for. However, you would think after almost 90 years we would have more equality stablished.

The Question of Algorithms

Algorithms are the equations that helps us throughout our everyday lives. They can be used when we decide what meals to cook upon their reception or what resources to pick depending on how relevant they are to us. The problem with algorithms in this day and age is that they lack transparency. A lot of what algorithms “do” are hidden behind unknown rules and digital curtains which companies do not make us privy to. Louise Matsakis writes that, “…even the people who build them aren’t always capable of describing how they work. ”20 This statement gives credence to the situation; big companies can set up these algorithms, but they cannot determine how they will work. She later espouses the idea that no one really cares about the code the big companies use, they just want the algorithms to be fair. Algorithms can be “sexist” or “racist” because they have no context and adapt to the bias of user relevance and this ties into that question of fairness, how transparent can we make these algorithms and will people be willing to accept that?

It is for this reason that scholars like Cathy O’Neil and Matsakis caution us to become better in how we consume digital media. O’Neil cautions us to not put blind faith into algorithms.21 While Matsakis wants us to question the algorithms we use in our daily lives. I found O’Neil’s description of an algorithm to be particularly interesting. Simply put, you have a historical data-set and your definition of success. The historical data-set are the things your bringing together like the ingredients in a dish, you go over which ingredients you want to use, and those you don’t. Your definition of success can be if your family likes the meal you prepared, then you have succeeded. This process can then be repeated with your successes also being added to the historical data-set. This kind of algorithm works for you and around you. The algorithms companies use and have AIs run pull from the entire culture for the historical data-set, thus a lot of biases of the past can be impressed upon the present. 

Safiya Noble brings up this exact idea in terms of feminism and black people. This historical data-set has access to the data the entire culture can provide. Thus, these algorithms end up carrying the biases of the past into now. Her personal anecdote22 at the beginning of her writing details this effectively in the sense of the sexualizing of women and how that affected her search on Google. She simply wanted to do something with her nieces but was met with pornographic results. She later goes on to discuss how the Google search algorithm has no social context. It show something that’s biased, something racist or sexist and not even have a concern or programmed thought of the consequences. So, in a vein similar to O’Neil and Matsakis, Noble cautions us about how big companies use algorithms and about their biases and fairness, but she also she carries a sense of activism. Noble brings up topics about movements to get companies to change how these algorithms function and investigates their biases. So we need to take O’Neil’s, Noble’s and Matsaki’s accounts into consideration and begin questioning the algorithms too. 


css.php