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. 1

In her book Algorithms of oppression Noble talks about how when she searches up “black girls” results referring to pornographic things showed up. 2 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. 3  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. 4

 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. ”5 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.6 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 anecdote7 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. 


Biased Algorithms

Throughout the years, I have become interested in a variety of different topics. And whenever these interests compels me to begin some form of research, whether it be for a blog or for my own writings, my first step is always to create a new Google Account. Although I recognize that this may be perceived by some as a strange practice, I find that having these separate accounts allows for the information pertaining to my subject of interest to be neatly categorized and to not be lost in the seemingly endless sea of content that I browse through daily.

Some of you may be asking yourselves, “why would one bring up his or her numerous Google Accounts in blog post about Algorithms?” The answer is simple. Because I am constantly creating new Google Accounts pertaining to a single topic, these new accounts are not influenced by previous searches made on the same account. What this means is that I Interact with Google’s search algorithm – tailored to new users – on the daily. Therefore, I can make the safe assumption that the results I receive on these accounts are influenced solely by Google’s search algorithm.

When beginning my research on motorcycle racing for my blog dedicated to the subject, I began by searching the phrase, ‘motorcycle racing’ using Google’s search algorithm. My results did not yield information on individual racers or the most recent racing events but the Cycle World news page. While this website contained brief snippets of information pertaining to cyclists and racing events, its focus was fixed ont he motorcycles being produced by companies such as Kawasaki and Honda. Where were the links to Instagram accounts of cyclists? Where were the photographs of these cyclists on the circuit?

In her essay, Algorithms of Oppression: How Search Engines Reinforce Racism, Safiya Noble states that Google’s search algorithm yields results that favor particular organizations based on their monetary influence. Although I cannot state with impunity that Cycle World has given exorbitant amounts of funds to Google for their place on the top of my search results, their connections with different motorcycle production companies and racing events – both high grossing industries – leads me to believe that they are in the position to reinforce their standing.

However, this problem seems not only to affect racing fans but historians and students as well. When the phrase, ‘Civil Rights Movement’ is searched using Google’s search algorithm, only a text box containing general historical information on the subject appears. To make matters worse, the information provided states that the Civil Rights Movement took place starting in the 1950s and ended in the 1960s. However, this movement began as early as the 1930s during FDR’s New Deal Administration and has continued even to this day.

These examples should remind us that the results we receive using Google’s search algorithm are not always the most reliable – they are not even unbiased. We must rely on ourselves, the users, to find credible, relevant information on our subjects.

Between Past and Present: From WPA-Era Activists to Contemporary Digital Activists

Algorithmic criticism is the concept of looking at algorithms with a critical perspective. Scholars studied the idea that algorithms go beyond mathematic and impact race, class, and gender. Scholars adopted intersectional critiques to understand algorithms.

The transition from the old traditional medias and the new digital medias has been adopted by most of us, but it is not necessarily understood. We are framed and driven by algorithms in our everyday life without knowing what it exactly implies. Algorithm in marketing is seen as an objective fact; it is actually an opinion embedded in math. 8

The public is in need of algorithmic literacy 9 In other words, people are unaware of the impact of search engines, digital medias, their mechanisms, and how they are part of it.

Search engines are part of our life and most people believe that it “provides access to credible, accurate, depoliticized and neutral information”10. In fact, a search engine is a “symbiotic process”: it informs, but we also feed it with information which it will measure for our next search.  In other words, we are acting a major part in the evolution of digital media. We both feed from each other.

Unfortunately, search engines use a rank system where paid advertising creates inequalities. Indeed, the negative representation of women through the ranked brings back to life women’s discrimination of lack of status. As a matter of fact, scholars noticed a “direct mapping of old media traditions into new media architecture” 11

Search engines algorithms can lead to racism and sexism. Noble mentions that the “pornification of black women” appears as a top search result. How can this be a top-ranked research? Who decides that this was the best information to be top ranked?

We have to understand the way algorithms are built. We first curate our data. Then we should define “success” 12 We embed our values into an algorithm.

This leads us to understand that a group of people created algorithm which allowed the “pornification of black women” as being a top search result.

As a matter of fact, if we create this artificial intelligence, this means that we can change it. It is not only math. The latter is the tool to apply the will of a human.

We should remember that many algorithms have been created to satisfy a neoliberal capitalist society with profits in its center. The system leads to misrepresentations and hypersexualisations of black women 13. Search engines have commercial goals first, and “labortainment” is a main source of benefits for digital media.

In other words, the latter defines “users who consent to freely give away their labor and personal data for the use of [a private company] and its products, resulting in incredible profit for the company”. 14 Users give their agreement to share their private information with digital media for profit use. Most people accept the agreements and policy without reading them.

We must be careful when using search engines, when signing online documents and much more. From commercial use, marketing targets, advertisements purposes, profits, selection, and discrimination, digital media is full of obstacles for us and we need to understand that there is more at stake than what we thought until now.

There is bias in search. It is a fact. What is even more shocking, is that norms reflect racist and stereotypical ideas. Content is screened and assessed using those norms. As a result, racism, sexism, and abuse of humans is normalized in a way that it is considered as perfectly acceptable.

We must learn from algorithm literacy and change the “consciousness embedded in artificial intelligence”, to become better consumers of digital media (Noble, 2018).

The 1930s were also marked by their own challenges. They were years of movements and dynamism, when the Long Civil Rights Era (LCR) was fighting to take the place of an old feudal system.

The New Deal helped to make the LCR era a subject for political debate. Roosevelt himself name women in key positions within the administration. Frances Perkins was the first female cabinet secretary. Mary McLeod Bethune was an African American advisor in the National Youth Administration. The First Lady Eleanor Roosevelt was herself the key advisor of the president and a major voice for economic and racial justice. 15

It was difficult for women to attain economic autonomy. While the New Deal programs helped to raise a debate about inequalities in the society, it also kept gendered assumptions. For example, “men serve as breadwinners” and “women serve as mothers, homeworkers, and consumers”.

The emergence of the LCR era was the sign that the nation was turning slightly left. Americans started to favor socialism and movements like the Popular Front brought a left-liberal cooperation with the Socialist Party of America and Communist Party USA (Ritterhouse, 2017).

Before being a party, the Popular Front was also a historical bloc. The Popular Front was an insurgent social movement forged from the labor militancy of the fledging CIO (Congress of Industrial Organizations).

The LCR era was marked by expanding democracy and guarantee the rights of citizenship to a broader segment of the American people, including people of color. 16

The Long Civil Rights Era throughout the New Deal and even later, helped to raise debates and fight inequalities. We live in a place today where we take for granted rights which were acquired thanks to people who fought for them at a time in the past. We shall always keep in mind this because we can lose our rights faster than we can obtain them.

There is actually a great parallelism between WPA-era activists and contemporary digital activists. While observing through the critical lens within algorithmic criticism, scholars put in excerpt the idea of the 1930s where we have to fight inequalities in a system where racism, sexism and much more have been normalized.

Scholars are now facing algorithms and the discrimination embedded in mathematics. Contemporary techno and algorithmic critics are working on developing tools to fight against inequalities in algorithms.

Open-source software are one of the ways found to fight against private interest of big companies who seek profits. The algorithms are public, and anyone can have access to it for free and modify it.

While Open-Source software can be a great weapon against inequalities in algorithms, scholars and algorithmic critics are still working hard to point out how we can be manipulated by this era of numbers, controlled by profits, and willingly or unwillingly mapping the mistakes of the past.

Blog Post #4: The Connections Between Modern Algorithms and The Social Security Act

As this was a very early time for civil rights the Long Civil Rights Movement is a movement brought up in Jennifer Lynn Ritterhouse’s book Discovering the South: One Man’s Travels Through a Changing America in the 1930s 17 that states that while the civil rights movement was at its peak in the 1960s the LCRM can be considered a sort of pre curser to that. What the LCRM did was simply layout the foundation for what was considered the height of the civil rights as well as modern civil rights movements. During the 1930s there was a push for a cultural lift in the United States spear headed by people like Harry Hopkins as well as The New Deal on FDR’s part. However, as discussed in The Living New Deal’s Working Together 18 the New Deal failed to address the hardships of minorities in during the Depression Era and in some ways even heightened the hardships. Therefore, movements like The Popular Front and the LCRM are mostly credited with the advancement of civil rights during the 1930’s. There simply weren’t many things that the U.S. Government was doing for the advancement of minorities. People like W.E.B De Bu Bois, Jane Adams and Marcus Garvey are essentially the first step of the 1960s civil rights explosion and that of modern times. Some contributions such as the books and papers that were written or physical organizations like the NAACP are still at the forefront of civil rights. Also, while they may not have lasted as long, things like Jane Adams’ Hull House 19 were at the time some of the best advancements for class injustice as well as other civil rights issues. With these movements and organizations, the central idea was for basic racial, class, and many other forms of equality. Also, as discussed in The American Yawp

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the central message was to give the people clearly being discriminated against some form of control in their government. The example given in the book states that even though the heavily African American community of agricultural workers still had to pay taxes they would not receive the benefits of the Social Security Act. The reason for this being that “…(white southern lawmakers were) afraid that economic security would allow black southerners to escape the cycle of poverty that kept them tied to the land as cheap, exploitable farm laborers…” 21. This clearly was wrong and many of the civil rights leaders of the time vouched for some representation as many white southern lawmakers only advocated for discrimination.

In many ways this has not changed today with other issues that are at the forefront of politics. The way that many people saw the treatment of African Americans in the 1930s specifically regarding the Social Security Act is largely the same when regarding biased and unfair algorithms today. Much like the little control the African Americans had over their right to social security many today argue that there is too little understanding of what happens inside of an algorithm. This, much like the little representation in social security, results in zero control over large part of the algorithm

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. Overall while people think that algorithms are something that is unbiased it has been shown that many can give unintentional bias or even intentional. It has been exposed that many of the algorithms that can decide very crucial things in people’s lives are unreachable in how they are made. This results in people not actually knowing how or why they were denied insurance, for example 23. One example that has recently plagued many early detection police algorithms has to do with African American crime rate. Obviously African American are not more likely to commit murder. However, due to the statistic of African Americans making up 13% of the population while making up 50% of all homicides in the United States many algorithms have mistakenly understood this as “African American are more likely to commit crim.” Clearly this is not the case, this is a biased and bigoted thought but because the algorithm only sees the statistic it has been known to sort of “let go” of other races. This clearly is a problem and many situations like this is what has caused many activists to call for access to these crucial algorithms. The lack of access and thus lack of control has proven to be a problem time and time again and thus needs to be addressed in the future.

Algorithmic Oppression and the Long Civil Rights Movement

Before our readings on Algorithms and the Long Civil Rights Movement, I had never thought that discrimination could cross over into the digitized, artificial intelligence world. Of course, as a white woman, I have been ignorant to the ways this has impacted specifically women of color. However, upon reflection I can now see even more ways this occurs than just the example, given in Safiya Noble’s work, of the google search results of the phrase “black girls” turning up unwanted pornographic searches. I have noticed when I search for makeup products the first results are always aimed at white woman, and even if these companies offer products for darker complexions, they are not nearly as advertised as much or in the same way they are for lighter complexions. That experience especially stood out to me when Noble explained that “search results reflect the values and norms of the…company’s commercial partners and advertisers and often reflect our most demeaning beliefs, because these ideas…are normalized and extremely profitable.”24 Reading this allowed me to understand better the meaning behind the Long Civil Rights Movement and why the fight for African American civil rights continues in modern America.

The 1930’s were particularly difficult for women and people of color as many of the New Deal programs were directed towards men and left out, or discriminated against, racial minorities. Although this time period provided hard times, particularly for minorities, it did shine a light on many inequalities within the United States. One example of this was shown through the Social Security Act which blatantly discriminated against African Americans. Southerners were “afraid that economic security would allow black southerners to escape the cycle of poverty that kept them tied to the land as cheap, exploitable farm laborers.” When Roosevelt agreed with this, he removed domestic workers and farm laborers, which were primarily black men from the South, from the Act.25 This relates almost perfectly back to algorithmic criticism. Just like how Southern politicians were profiting from cheap labor in the 1930s, companies are profiting from the objectification of black women, which is only amplified through algorithmic searches.

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An algorithm, in essence, is a recipe for an outcome so desired by the person who created the recipe (Cathy O’Neil). Thus, every algorithm, no matter its nature, is subjective to the desires and goals of its creator. Algorithmic criticism has everything to do with morality, and the fight especially within research to make algorithms that will actually draw out a more focused answer to the questions posed, rather than what that most common answer is. Safiya Noble proposes the notion in Algorithms of Oppression, that it is now critical to “think about whether it truly makes sense to outsource all of our knowledge needs to commercial search engines…in lieu of libraries, librarians, teachers, researchers, and other knowledge keepers and resources.” (pg 16). This concept resonates strongly with not just drawing out the more specific knowledge we ask for, rather than the competitive answer that the engine’s algorithm drives to the top, but as well as with the ethics with which this knowledge is derived and shared. The idea of algorithmic criticism is external criticism of the results of what is output by an algorithm, is in its essence, a balance of differing opinions. Given the nature of historical research being one driven by the need to discover the truth (or the closest version of the truth to which we may get), and the biases inflicted upon these truths by the sources and the researchers themselves, it is difficult to truly change the consumption of historic media. It is still important to focus on the ethics and morality which we as historians, employ when we go looking for answers.

Noble’s chapter focusing on the re-imposition of sexism and racism in on the worlds most popular commercial search engine, highlights the longstanding strength of these ideologies, and how their being reinforced by popular majorities, against smaller parties who seek to fight it. The Long Civil Rights Movement, as well as the continuing remnants of the suffragette fights brought a strong, but somehow subtle front to the 1930s- the Civil Rights movement as we knew it to be in the 1960s was finally starting to gain speed in the 1930s, especially with opportunities for work and influence beginning to open more and more with the Federal Theater Project, eventually paving the way for such a wide variety of influential music we hear today. Women continued to fight for their rights, continuing the struggle which had initially beginning in the ‘20s, and still carries a lasting impact today, especially with jobs which had opened during the New Deal and set in place the norm of women being employed in similar spaces as men, such as is seen today. The pressures of racism and sexism however, have still not relented nearly as much as we think, and the output of search engine algorithms in present day, as noted especially in the beginning of Noble’s article, only fuel these pressing notions. Removing such significance from these digital algorithms and search engines, perhaps not so much as within popular and commercial culture, but at least in modes of historical research, can be fueled in some ways by moving back to non-digital sources.

Bibliography:

Noble, Safiya. Algorithms of Oppression: How Search Engines Reinforce Racism . New York, NY: New York University Press, 2018.


O’Neil, Cathy. “The Truth About Algorithms: Cathy O’Neil.” Vimeo, October 17, 2018. https://vimeo.com/295525907.


Ramsay, Stephen. “Algorithmic Criticism.” A Companion to Digital Literary Studies, 2008. http://www.digitalhumanities.org/companion/view?docId=blackwell/9781405148641/9781405148641.xml&chunk.id=ss1-6-7.

The Popular Front’s Legacy

Algorithmic criticism is about as varied and hard to define as algorithms themselves. There are multiple lenses one can look through when critiquing algorithms: the conformist lens, the scrutinising lens, the feminist lens, the black lens, the black feminist lens, the scholarly lens, and so on. There are as many lenses for examining algorithms as there are algorithms, I feel. One thing all those perspectives can agree on is that one should always examine the established order. This goal of defiance appears to me as a lofty goal, especially when all the institutions of the web are like the monolithic ad-buildings of Blade Runner, almost primeval in their permanence.

All this is terribly reminiscent of the aims of the Popular Front movement. Just how the socialist coalition strove to battle the status quo of capitalism, modern activists strive to battle the status quo of ad agencies and complacency with those ad agencies. With the potency of folk singers and labour activists, the Popular Front encouraged alternative thinking about our institutions, tacitly urging that Americans must interact with them and mustn’t turn a blind eye to their presence. Had ‘the communist-oriented International Legal Defense (ILD)’ chosen not to come ‘to the aid of the “Scottsboro Boys”’, yet another injustice would have been carried out and America would have been further proved as a nation that does not care to challenge its status quo. Instead, the plight of the Scottsboro Boys and efforts of the Popular Front’s law firm ‘became a national symbol of continuing racial prejudice in America and a rallying point for civil rights–minded Americans.’ (Cochran et al.) 1

The Popular Front’s stance against capitalism and racism lent a stark model for activism and interrogation of what we know (as provided by institutions). The institutions of today are perhaps more furtive, but no less insidious. Advert agencies, in service of the status quo, now implement algorithms that serve to uphold complacency to such a point that ‘the clicks of users… mean that representations of women are ranked on a search engine page in ways that underscore women’s historical and contemporary lack of status in society’. (Noble) 26

Safiya Noble, in the defiant and questioning tradition of the Popular Front activists, offers some ideas as to how to subvert and interrogate our institutions. She advocates for literacy at a basic level of Internet citizenship, maintaining ‘that one need not know the mechanism of radio transmission or television spectrum or how to build a cathode ray tube in order to critique racist or sexist depictions in song lyrics played on the radio or shown in a film or television show.’ (Noble) In other words, we should place faith in our intuition and judgment over the intuition and judgment of erroneous, as Cathy O’Neil terms it, ‘opinions embedded in math’. (O’Neil) 27 28

Critical Response to Digital Technologies

Algorithm criticism is an important process to remember when engaging with sets of data. There are questions surrounding algorithms that could impact the data sets that are shown. Who created the algorithm? Why did they choose to do it this way? Who does this algorithm directly effect? These are a few things to consider when attempting to understand why a data set exists the way that it does. In Noble’s Algorithms of Oppression we see that there is a need to understand the power that creates these algorithms 1; while a private entity can create the physical code that is the algorithm, it is dependent upon the consumers and fellow google-searchers to undermine the oppressive nature of online algorithms.

Feminism in the 1930’s proved more relevant than ever after the New Deal. The political and societal understanding of the time was that the men were the sole breadwinners meanwhile the women were to tend to the traditional house duties 2 Feminism here challenged the status quo in an attempt to show the world and the American society that women were indeed capable to provide for their families; they wanted to show that they were beneficial to society outside of the household. Today feminism still promotes the equality of women but in a different sense. No longer are women expected to remain at home to raise children but they are ever present in the workplace. An issue that feminism continues to tackle today is the gender wage gap in which women are being paid less than men even though society says that they are equal and capable of the same jobs.

WPA activists share similarities with modern-day activists in the sense that they are fighting social norms by pushing boundaries. Referring to the American Yawp‘s section XII and my previous paragraph, we see that the feminist were fighting gender norms and stereotypes by forms of protests. The modern day digital activists are challenging society’s modern day stereotypes. For example, a simple google search provides a laundry list of predicted results before even finishing your search entry. These activists want to change these predictions through understanding algorithmic code and there is an attempt to move away from the racist or sexist search tools by changing the way society accepts these results.3

Stuck

The Modern Era is a living testament to the history of the 1930’s. The Long Civil Rights Movement and the impact of feminism from the 1930’s remain prevalent to social and political movements of today. The Long Civil Rights Movement set the stage for Martin Luther King Jr.’s walk, and emphasized the importance of the set up. There are decades of set up before there is actual change within a society. Then to the modern Era those changes continue to develop and grow into movements like the Me Too movement and the Black Lives Matter movement. However, these movements and changes in society and political policy can be severely hindered by technological algorithms.

Algorithms essentially create a pattern of habit and keep people in it. An Algorithm is “Opinionated math”. This habitual box keeps the system from growing and changing with the needs of the times. On top of that people are not allowed to know how the Algorithms work. If Algorithms from the 1930’s were used in the same way they’re used today in systems then the definition of rights would have never changed for the better. There is no room for growth in a closed system.

There is no room for change unless there is revision of the algorithms.

Civil Rights and Feminism were a critique of the behavioral “algorithms” of the 1930’s, and if people treated behavior in the same way people treat technological algorithms of today there would have been no change. We take our history for granted and don’t take notes.

But there is a call for the reevaluation of how and why algorithms are written and administered. People treat algorithms as TRUTH rather than what they really are, “Opinionated Math”. Math and technology is only as good as the people behind it. In the same sense they are fighting for the value of equal treatment and American values of freedom. They’re fighting in very different ways but for the same ideas. Different times same issues. Algorithmic Criticism is fighting for substantial growth, Today we are taking our knowledge of humanity and showing people the human behind the mask of math and Technology. Algorithmic Criticism reintroduces the humanities into the sphere of technology. I believe part of the reason we have had such an issue with the revision of Algorithms is due to deification of math and Technology and the disregard for the place of humanities within the system.

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