Mrs. Laura Smalley

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While Laura Smalley obviously suffered during her childhood as a slave, those recollections seem to be more distant to her. What she really recalls is the preachers, who “preached better then… now they [preach] by scripts most of the time. But then… they just preach, preach by the spirit”, or how they would cut and dry grass to make good bedding. The larger sufferings still remain, but Mrs. Smalley couldn’t remember any abuse that she herself took. 1 Nor could she talk about slaves being sold like cattle, stating “us children never did know that, you know. We heard talk of it, but then I reckon that was after, after slavery I reckon.” It seems that slaves placed a high value on their children, on their community, and sought to shelter their children from its horrors. Of course, the horrors still shone through to her, such as when the plantation’s mistress beat a woman slave in the peach orchard and snuffed out a pipe on her skin; young Laura recalls having to grease her back afterward. 2

Laura was immune to monumental things like the end of Reconstruction, the labour reforms of Teddy Roosevelt, World War I, or the Great Depression’s onset, existing as mere gaps in memory. The tectonic shifts in America reached Laura and her community much slower than I would’ve expected; when the Civil War ended, her master didn’t even tell his slaves that they were free for six months (nor did any slave owner in Texas until Juneteenth). Even the race riots in the area passed by Laura; I was surprised that she was swift to recall “when colored folk [killed] one another for a while… Women killing other women about they husbands”, making me think the events are related. 3 4

No community is immune to every social or political change, so I quickly deduced that the omissions of major happenings were Mrs. Smalley’s error. Throughout the interview, she came off as addled, and I frequently sympathised with the interviewers who kept angling their questions for meaningful answers– only for Laura to confess she knew nothing about what they were asking. Though I found value in hearing just what daily life consisted of for those enslaved– the oral account allowed for inflections and repetitions of speech to tell the story, elements I appreciated– there is a big asterisk next to that value concerning Laura’s advanced age.

I was fascinated by the interviewers’ frequent interjections. The Faulks remained professional, but when Mrs. Smalley went into detail about the treatment of some slaves, they never failed to exclaim ‘Good God’ or an assenting grunt. They added a very human element to their part, making the interview a true conversation. It made a difference to Laura, too, as she eventually grew more comfortable in how she spoke. While a transcript would clarify much of Laura’s dense dialect, it would take away her progression of comfort as the interview continued, the dynamic between interviewer and interviewee. It speaks to the ethos of the FWP that the Faulks turned the interview into a conversation, that they and the best of their peers wanted their history to be a dialogue. 5

Fountain Hughes’s Narrative

For this assignment, I listened to an interview with Fountain Hughes, conducted by Hermond Norwood. Over the course of the thirty minute interview, I was able to notice the value of his experience, and the ways that his experiences did and did not align with my expectations for his narrative.

Here is the timeline that I created based on Fountain Hughes’s interview.

Learning from a narrative

I believe that there is a lot of value within Fountain Hughes’s experiences. Through this interview, historians receive a firsthand account of what it was like to be an enslaved person in the United States during this time. Something that stood out as particularly poignant during the interview was how Fountain discussed slavery in terms of the 1940s. He speculates that some people now “would rather be slaves.”5

Fountain notes that he would rather kill himself than go back to being a slave. He notes that they were treated like dogs, and would never go back to that existence. This directly contradicts the narrative of the jovial slave that was spread by people in the argument that slavery wasn’t as bad as it seemed. Fountain Hughes claimed to be more than one hundred years at the time of this interview and had not been enslaved for more than eighty years. Still, the trauma of slavery stuck with him so strongly that he would not hesitate to resist in the most severe and permanent manner.

Additionally, Hughes’s narrative is valuable as a man who originally lived in the South before moving to Baltimore, leading to a unique construction of southern identity. In particular, his discussion of going to church in a log cabin and being led by an older preacher in the singing of gospel songs, adds to the idea of a southern identity6

I was actually surprised by Fountain Hughes’s reluctance to talk about some of the specific hardships he endured as a result of his enslavement and status both during and after the Civil War. He says he doesn’t like to talk about it because “it makes people feel bad.”7 While the goal of chronicling the narratives of enslaved people as a part of the Federal Writer’s Project was to understand what enslaved people endured8 , one can not account for someone who doesn’t feel comfortable sharing what they went through.

Still, this interview has limitations. As a result of Fountain Hughes’s advanced age, his memory of events may not be as accurate as it once was. Also, it is limited by his previously discussed reluctance to discuss topics that he believes will bring others down. Obviously, there is no reason to believe that Fountain Hughes is intentionally telling any mistruths, but as a result of his age, some aspects of context may have been lost to time. For example, during the interview he describes an occasion when, as a youngster, he and his brother slept in an automobile. But, based on his age, Fountain would have already been in Baltimore by the time automobiles became commonplace in this country. He may have been referring to a more recent event with his brother, or he may have been intending to say they slept in a place that was “like” or “the size of” an automobile.

Finally, I was a bit surprised by how much Fountain Hughes’s depiction of his own life relied on broader events as signposts. Multiple times during the interview, Fountain remembers an event by President Garfield being assassinated, or someone’s death happening during or after the Civil War, or how hard life was when he and his family had just become free. Currently, I don’t remember my own life in these kinds of terms. Then again, I’m 21 and not 101.

Blog Post #4

Algorithmic criticism essentially dictates the AI Bias, or Black-Box Algorithms ( https://www.wired.com/story/what-does-a-fair-algorithm-look-like/?GuidesLearnMore ) when google searching a topic. The algorithmic manipulation of literacy when a google search is made consists of many different variations. For example, according to Noble, Algorithms of Oppression, when google searching “Black Girls”, all that comes up on the first page is pornography. Feminism in the 1930’s impacted the search engines in the sense that male decision making and google searches tend to shift towards sexualizing women. The blatant sexist and demoralizing male bias behind this is appalling, and unfortunately, whoever is in charge of creating these ludicrous algorithms that come up with that kind of search results does not care about knowledge and un-bias decision making, but rather only cares about a small portion of the population. Another example is when big , money making corporations have the finances to put their advertisements over simple google searches; meaning no matter what you personally want to search, you are forced to look at some business as well. Contemporary digital activists and WPA – era activists are similar in the sense that the search results have not changed much. They still prioritize the more vulgar, sexist, and racist results rather than an algorithm that takes everyone into account.

Algorithms

An Algorithm as described by Cathy O’neil is an opinion embedded in math. 7 The purpose for an algorithm is to determine success through historical data to give the best accurate outcome. Algorithmic criticism is seen through web searches and different lengths of advertising, as well as racism. To some degree, most algorithms are racist because of the data and stereotypes embedded into these equations. While reading Safiya Nobel’s Algorithms of Oppression, simple acts such as researching women becomes a an event of discrimination and judgement. 9 Search engines, such as google have created stereotypes for white and black women. Black women are loud, ghetto or angry. While white woman are portrayed as beautiful, perfect or skinny. People of color have endured a difficult and lengthy path to advocate for civil rights.

In the New Deal Era, people of color were excluded from social security and welfare. Black people struggled to be recognized and obtain rights that were given to all white Americans. Despite the fact that Black Americans are now granted the basic rights of freedom, algorithms are a subtle reminder of how racism is still alive and thriving. Using historical data set to prevent loans or credit cards based off of technological systems can be dangerous. AI software used by Google is very powerful within itself, and although the system is programed to make good assumptions based on patters, it fails to recognize the ethics that comes with it.

In order to become better consumers of digital media we must hold companies responsible and enforce action towards understanding minorities. We must ask questions and question their overall definition of success by their motives. As O’neil stated, we must hire data analyst to look over patterns and trends to ensure these softwares are meeting basic measure of success, while granting reasonable explanations that refrain from being discriminatory, racist or biased.

Algorithmic Criticism

Algorithmic criticism is, essentially, exactly what it sounds like. Algorithms in theory make the sorting of information easier, but human operators must take caution to not assume that they are immune to both accidental and intentionally programmed bias. One of the simplest ways to counter this is to continuously monitor what content algorithms not only take in, but produce as a result. The larger problem comes in once we begin to face the societal issues: algorithms do not suggest content such as “women should not have rights” (Noble, 15) or present black girls as “the fodder of porn sites” (Noble, 18) if nobody is searching such things.

The concept of tools intended to help people from all walks of life being corrupted by prejudice is nothing new. Multiple New Deal programs from the 1930s intended to help Americans find employment amidst the Great Depression were, at best, failing to take into account the presence of women and people of color, and at work, actively working against giving them aid. Early feminist and civil rights movements put a great deal of work into attempting to counter this, much like the way modern technological movements like Black Girls Code (Noble, 28) attempt to fill the room with more diverse voices. But the 1930s were a troubling time of paradox. Even as a woman was appointed to President Roosevelt’s inner circle, which was a massive political victory, women found themselves being shut out of many of the fields that they pioneered, such as early coding and filmmaking. In the South, black men who sought work right alongside white men became victims of lynching and other hate crimes. The repercussions of gatekeeping and hate crimes have followed America into the 21st Century, but so have efforts to counter them. Every feminist movement has evolved out of the last, including that of the early 20th Century from proto-feminist writings of the 19th. Scholars such as Jennifer Ritterhouse and Jacquelyn Dowd Hall propose the term of a Long Civil Rights Movement, as a remedy to the narrative that the struggle for racial equality began and ended in the 1960s.

The Digital Age will continue to grow and shift alongside what grows from it. It would be inaccurate to say that no attempts are being made to ensure that it remains safe and indiscriminatory. Remaining vigilant is the best that contemporary techno-critics can do, alongside implementing plans to counter reactionary indoctrination.

Search Engine Bias – Blog Post #4 – Christina O’Farrell

If I was to give a definition of algorithmic criticism, I would direct someone to Cathy O’Neill’s to hear what she has to say about it. But, if I had to put it into my own words, I’d say it’s looking for the unbiased truth in algorithms. O’Neill’s TED talk was all about how algorithms are biased and how we can make our own algorithms with our own success. Scholars, such as O’Neill, have advised us (non-data scientists) to “demand accountability” from those data scientists who control the algorithms in our society. Those data scientists are the ones who set up the basic algorithms of the world, the algorithms that us, non-data scientists, have heard of, but they tend to turn out biased. The best thing to do is to try and avoid the biased algorithms and media that is presented to us.

Feminism impacted the 1930s by bringing to light the topic of equal treatment for women within the job force. More women had jobs during the ’30s, but the treatment they received was very different compared to the treatment men received. Another key thing to note that impacted the ’30s was the 19th Amendment passing and how some feminists believed their job was over. Women were elected to the Senate and FDR had women on his administration.10

In my opinion, I would say there are a few connections to draw between WPA-era activists and those today. Slavery/discrimination was an issue back during WPA and it’s still an issue today. I think today it’s much more prominent and the issues go deeper than those back then. People have more of an eye on biased situations compared to back then. Digital activists can spot bias quicker than WPA-era activists, especially in Noble’s article, Algorithms of Oppression. 11 The fact that digital activists were able to spot discrimination online through search engines blew my mind. It was something I would’ve never thought would show any kind of bias or discrimination, but I was wrong.

I believe techno-critics and algorithmic critics are applying the same ideas. They both are identifying bias’ and attacking them. They’re trying to encourage people to notice them as well and find ways to stop them. It’s a really interesting movement they’ve started by pointing out bias on search engines and other forms of technology, it really shows how much more we really need to progress to finally meet equality.

Moran, Mickey. 1930s, America – Feminist Void? Accessed October 20, 2019. http://people.loyno.edu/~history/journal/1988-9/moran.htm.

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


Blog Post 4

Algorithmic Criticism is essentially math with an opinion according to Cathy O’Neil in her video, “The Truth about Algorithms.” 12.The algorithms that we, as humans, create, are embedded with biases that we may not be intentionally programming in. Algorithms are capable of having all types of biases including racism, sexism, and many other inequalities we can see in our culture today. 13 However, many professional institutions are trying to steer artificial intelligence away from the biases and inequalities, and towards a better and more equal path. Most of the institutions working on equaling artificial intelligence have even called for, “more fairness, accountability, and transparency,” (Matsakis, WIRED) in regards to new developments in artificial intelligence.

During Franklin Delano Roosevelt’s presidency, women’s labor legislations became more protected. In the Supreme Court case, West Coast Hotel Co. v. Parrish, with Franklin D. Roosevelt’s influence, Washington State’s minimum wage legislation was upheld as constitutional. This paved the way for more protected labor legislations for both women and men. Eleanor Roosevelt was one of the largest voices for women in the 1930’s. She was a very visible and vocal part of Franklin D. Roosevelt’s administration. Eleanor was always by her husband’s side. She constantly supported FDR throughout his presidency, not only with his administrative decisions, but also his lasting struggles from his severe case of polio. FDR also supported her. He fought for women’s rights and believed in equality for men and women. Eleanor Roosevelt surrounded herself with hardworking and trustworthy women. She brought women, other than the first lady, into the Whitehouse and into the United States government. Eleanor became a role model for every little girl growing up in 1930’s America. Even today people still look up to her and believe in the things she stood for. She is one of many important women to fight for women’s rights early on in the history of the United States. Even through Eleanor’s efforts for equality and FDR’s contributions to women’s rights, we can till see these inequalities and biases today. Our culture today practically runs on algorithms. However, these algorithms show these inequalities and biases that FDR and Eleanor wanted to stop.

Lewis, Jone Johnson. “Slow and Steady: Women’s Changing Roles in 1930s America.” ThoughtCo, ThoughtCo, 6 Oct. 2019, www.thoughtco.com/womens-rights-1930s-4141164.


Matsakis, Louise. “What Does a Fair Algorithm Actually Look Like?” Wired, Conde Nast, 14 Feb. 2019, www.wired.com/story/what-does-a-fair-algorithm-look-like/?GuidesLearnMore.

Blog Post 4

Algorithms are sets of rules in data that are often used today but these data sets are not free from unfair use or biased use. Cathy O’neil simply defined algorithms as ‘opinions embedded in math’. She states that these algorithms are viewed as objective and unbiased because its math and numbers and those are free from bias but the way algorithms are built allows for those mathematicians and data set builders to implement their own idea of success into the algorithms.14 Because the definition of success is different for every person each algorithm can come up with different results. These algorithms in modern day use allow for inherently racist and sexist ideals to be prevalent in modern media. Search engines, like Google, in particular have been one of the most problematic in having these racist or sexist algorithms as stated in Noble’s book, Algorithms of Oppression.15 The search results for black girls and other minority women come up with results that both objectify them and have a very sexist point of view. This is something that Google’s search algorithm allows for in mass media.


Feminism in the 1930’s was one of the better things about that decade. In a time where the Great Depression struck most people very hard, feminism, coming of the heels of the success of the women’s suffrage movement, progressed forward. The monetary struggles of the 1930’s pushed women to get jobs and provide monetary support for their families which was very rare until this point. This got women out of the house and gave them more freedom socially.


WPA era activists and modern activists share a common goal of pushing for equality for everyone across the board. They both utilize the power of media to get their message out. Granted, modern activists have the luxury of the internet and have easier access to more people and this can aid their movement but WPA era activists had the same intent and utilized their own skills and resources. Algorithm critics are part of that modern activist movement as they are pointing out the biases in these algorithms that most people do not recognize and calling for that change to create a better and more unbiased future.

Critical DH

Algorithms aren’t perfect, and scholars have been criticizing them for being too broad or biased to be relied upon as much as we do today.  Cathy O’Neill mentions that algorithms can be described as “Opinions imbedded in math”. 16 Due to this, opinions that are different to the one who wrote the algorithm or control the algorithm can be snuffed out and ignored.  Some scholars have suggested that we push for understanding how the powers that control the algorithms work.  This way, we as consumers can avoid using Google, and other search engines in a way that promote these racially or sexually motivated search terms, as mentioned in Noble’s paper on the subject. 17

In the 1930s, society was undergoing intense societal change due to the Great Depression, and because of this feminism and in general the whole popular front became popular.  The popular front was made up of radicals that can range from communists to people advocating for racial desegregation.  Some folk singers, such as Woody Guthrie were associated with the communists, and it’s reflected in their songs. 

Feminists were also a part of the popular front, and they had their own impact on society back then.  Due to the lack of money, women began to work for themselves instead of relying on their men for money.  This in turn began to change the way society saw certain professions and allowed women to become more independent.  Later, when the US joined WWII, women in the industrial sector became much more common, which shows that during this time, women working in clothing factories and farms changed the way America saw working class women.

There can be connections drawn between the WPA-era activists and modern activists in a couple of ways.  For one, both activists are fighting for racial and sexual equalities in the US using art to express their ideas.  Woody Guthrie is a great inspiration to many later artists that fight for civil liberties.  Feminists are also still fighting today, what they had to fight in the 1930s.  Gender norms are being changed, and workplaces are being filled with women, rather than just men.  Women are no longer just stay at home moms, but rather they create their own businesses and careers, which seems to be a logical progression from what the feminists fought for back in the 1930s.

Blog Post 4

At a time when the federal government was first seen shifting its priorities to create the basis of a welfare system, there was also the inescapable question of who is deserving of these new rights and benefits. Franklin Roosevelt not only failed to address the difficulties that Black Americans faced, but he also continued the institutionalization of racism with federal government policies. Roosevelt rejected the proposal to abolish the poll tax and declare lynching a crime. But the most visible codification of racism in federal law came with the removal of domestic workers and farm laborers from the provisions of the Social Security Act.18

Although, the Long Civil Rights movement and the popular front impacted the 1930s by helping create a more equitable society for the marginalized when the federal government failed to do so. The activists from the LCRM and the popular front fought to expand the nation’s immaterial boundaries of who is a citizen worth fighting for and I would argue that this is the same struggle that digital activists are fighting today. Marginalized groups are still scrutinized and discriminated against, except this time it’s less identifiable who’s doing the discrimination and how.

Safiya Noble argues that the “traditional misrepresentations in old media are made real once again online and situated in an authoritative mechanism that is trusted by the public: google.”19. Noble’s keyword search of “black girls” represents how algorithms can perpetuate harmful misrepresentations and the dehumanization of people.20 Despite the fact that marginalized groups are the ones who are being exponentially affected by Google, I would argue that this is a human rights issue that everyone should be concerned about. Anyone using the internet today, whether a target of the state or not, is trading in their privacy, personal information, and most importantly their immaterial labor.

As of right now, the general public is not aware of how algorithms are made and there is a common assumption that the mathematical language of the algorithm would be a barrier to understanding it. Yet, the foundation and design of algorithms can be understood without having to learn a mathematical language. According to Cathy O’Neil, to build an algorithm you need a historical data set and a definition of success. At its core, those are the only two things that need to be understood to get a general grasp of algorithms. Algorithmic literacy must be taught to the public in order to transform artificial intelligence into a less problematic and dangerous entity.  

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