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. <\/p>\n\n\n\n
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. <\/span>1<\/sup><\/a><\/span><\/p>\n\n\n\n The public is in need of algorithmic literacy <\/span>2<\/sup><\/a><\/span> In other words, people are unaware of the impact of search engines, digital medias, their mechanisms, and how they are part of it. <\/p>\n\n\n\n Search engines are part of our life and most people believe that it \u201cprovides access to credible, accurate, depoliticized and neutral information”<\/span>3<\/sup><\/a><\/span>. In fact, a search engine is a \u201csymbiotic process\u201d: 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. <\/p>\n\n\n\n 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\u2019s discrimination of lack of status. As a matter of fact, scholars noticed a \u201cdirect mapping of old media traditions into new media architecture\u201d <\/span>4<\/sup><\/a><\/span><\/p>\n\n\n\n Search engines algorithms can lead to racism and sexism. Noble mentions that the \u201cpornification of black women\u201d 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? <\/p>\n\n\n\n We have to understand the way algorithms are built. We first curate our data. Then we should define \u201csuccess\u201d <\/span>5<\/sup><\/a><\/span> We embed our values into an algorithm.<\/p>\n\n\n\n This leads us to understand that a group of people created algorithm which allowed the \u201cpornification of black women\u201d as being a top search result.<\/p>\n\n\n\n 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. <\/p>\n\n\n\n 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 <\/span>6<\/sup><\/a><\/span>. Search engines have commercial goals first, and \u201clabortainment\u201d is a main source of benefits for digital media. <\/p>\n\n\n\n In other words, the latter defines \u201cusers 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\u201d. <\/span>7<\/sup><\/a><\/span> 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. <\/p>\n\n\n\n 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. <\/p>\n\n\n\n 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. <\/p>\n\n\n\n We must learn from algorithm literacy and change the \u201cconsciousness embedded in artificial intelligence\u201d, to become better consumers of digital media (Noble, 2018).<\/p>\n\n\n\n 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.<\/p>\n\n\n\n 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. <\/span>8<\/sup><\/a><\/span><\/p>\n\n\n\n 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, \u201cmen serve as breadwinners\u201d and \u201cwomen serve as mothers, homeworkers, and consumers\u201d. <\/a><\/p>\n\n\n\n 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). <\/p>\n\n\n\n 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). <\/p>\n\n\n\n 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. <\/span>9<\/sup><\/a><\/span><\/p>\n\n\n\n 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. <\/p>\n\n\n\n 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. <\/p>\n\n\n\n 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. <\/p>\n\n\n\n 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. <\/p>\n\n\n\n While\nOpen-Source software can be a great weapon against inequalities in algorithms,\nscholars and algorithmic critics are still working hard to point out how we can\nbe manipulated by this era of numbers, controlled by profits, and willingly or\nunwillingly mapping the mistakes of the past. <\/p>\n","protected":false},"excerpt":{"rendered":" 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 … Continue reading “Between Past and Present: From WPA-Era Activists to Contemporary Digital Activists”<\/span><\/a><\/p>\n","protected":false},"author":21,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5],"tags":[],"class_list":["post-845","post","type-post","status-publish","format-standard","hentry","category-critical"],"_links":{"self":[{"href":"https:\/\/jessicadoeshistory.com\/courseblog\/wp-json\/wp\/v2\/posts\/845","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/jessicadoeshistory.com\/courseblog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/jessicadoeshistory.com\/courseblog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/jessicadoeshistory.com\/courseblog\/wp-json\/wp\/v2\/users\/21"}],"replies":[{"embeddable":true,"href":"https:\/\/jessicadoeshistory.com\/courseblog\/wp-json\/wp\/v2\/comments?post=845"}],"version-history":[{"count":16,"href":"https:\/\/jessicadoeshistory.com\/courseblog\/wp-json\/wp\/v2\/posts\/845\/revisions"}],"predecessor-version":[{"id":901,"href":"https:\/\/jessicadoeshistory.com\/courseblog\/wp-json\/wp\/v2\/posts\/845\/revisions\/901"}],"wp:attachment":[{"href":"https:\/\/jessicadoeshistory.com\/courseblog\/wp-json\/wp\/v2\/media?parent=845"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/jessicadoeshistory.com\/courseblog\/wp-json\/wp\/v2\/categories?post=845"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/jessicadoeshistory.com\/courseblog\/wp-json\/wp\/v2\/tags?post=845"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}