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DTC475 - Multimodal Redesign - Algorithmic Bias in our daily lives

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     Hello all, today in this Multimodal Redesign, I will be focusing on a topic that I would like to discuss upon further - Algorithmic Bias in our dailies lives. The reason on why I choose this topic is due to how as someone who spends most of their time online and is actively engaging with algorithms constantly, I feel very strongly towards such biases existing within the system. I had previously talked about this topic in one of my unit projects, and I wish to elaborate further within this blog. According to an article written by "Knowledge at Wharton", when someone goes to shop on Amazon, about 1/3 of our decisions when on that website are influenced by Algorithms; And on the popular streaming website Netflix, this number is higher at a whooping 80%. Following up they go ahead and mention on the fact that such algorithms can have their own biases and even go rouge. As another article goes to mention, biased decisions had always existed, but with the advent of A...

Synthesis Report

 Algorithms - Many people know what it is, others may not. Most know it from the internet, from the various social medias and online platforms. In this Synthesis report, which encompasses various topics that we had studied in this semester. I will talking about the 3 following topics, that all relate to Algorithms: Algorithmic Bias, Algorithmic Oppression and the concept of having a "neutral" algorithm. Algorithms:  a process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer. This is how google defines it. We use it in our daily lives even without knowing about it, and are impacted by it on a daily basis. Everything from social medias to even grocery/shopping centers uses algorithms in order to create a "better" outcome for most people. However, most of the time the algorithm is left to their own devices and ends up being "accidently" biased towards certain minorities or groups of people due to var...

Selected Blogs

Hello all! Today I with the assignment I will select 3 blogs and comment about them. I will take 1 post from each chapter to show the changes and occurred throughout the semester. Each of these posts will have a common theme regarding internet usage and how it affects the daily lives of people. Blog 1: Reading Annotation Blog 1.3 Although this blog talks a lot more about Tribal  Sovereignty , the main subject there that is consistent with a lot of the blogs I write related to how the internet is used, how access to it affects us, and how it changes the lives of people daily. In this post I talk about how locking access of certain groups to the internet can negatively impact them, as well as my own opinions on the matters - as personally I use the internet daily and think it should be a right for all people to use. As this is one of my first blogs, I don't really have much experience writing blogs so personally I feel like it's a bit worse compared to my others later on.  Blog ...

Reading Annotation Blog 3.4

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The rhetoric of the empathy machine asks us to endorse technology without questioning the politics of its construction or who profits from it … Do you really need to wear a VR headset in order to empathize with someone? Can’t you just fucking listen to them and believe them? You need to be entertained as well? Are you sure this isn’t about you ? … I don’t want your empathy, I want justice! ” 23 Benjamin, Ruha.  Race after Technology : Abolitionist Tools for the New Jim Code , Polity Press, 2019.  ProQuest Ebook Central , http://ebookcentral.proquest.com/lib/wsu/detail.action?docID=5820427. Created from wsu on 2023-04-20 02:13:49. Now for this week's blog, it main not pertain to the main topic of this well, topic, the quote I had chosen for it really stood out to me. The paragraph that this was pulled from was referencing how Mark Zuckerberg - Founder of Facebook was talking about VR and how VR can be used as an "empathy machine". This made me feel genuine anger ...

Reading Annotation Blog 3.3

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  In forecasting who would re-offend, the algorithm made mistakes with black and white defendants at roughly the same rate but in very different ways. The formula was particularly likely to falsely flag black defendants as future criminals, wrongly labeling them this way at almost twice the rate as white defendants. White defendants were mislabeled as low risk more often than black defendants. 10 Benjamin, Ruha.  Race after Technology : Abolitionist Tools for the New Jim Code , Polity Press, 2019.  ProQuest Ebook Central , http://ebookcentral.proquest.com/lib/wsu/detail.action?docID=5820427. Created from wsu on 2023-04-08 03:25:54. Reading thought the newly assigned chapters of Race after Technology , a lot more issues with how some blatantly discriminatory designs and technology still exists. I like how this part of the chapter ties into what we talked and learnt about in the last unit, which is in regards to algorithms. From personal experience of using the internet I k...

Reading Annotation Blog 3.2

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  “Some algorithms are racist” “We have a problem: Racist and sexist robots” “Robots aren’t sexist and racist, you are” “Robotic racists: AI technologies could inherit their creators’ biases” Benjamin, Ruha.  Race after Technology : Abolitionist Tools for the New Jim Code , Polity Press, 2019.  ProQuest Ebook Central , http://ebookcentral.proquest.com/lib/wsu/detail.action?docID=5820427. Created from wsu on 2023-03-28 23:47:15. This chapter is one that contains very heavy and sensitive topics, as it mainly has to do with race and how different races are treated and seen in the modern society. As I was reading though "Race after technology", and having seen the introductory materials in this chapter, I have come to realize that this issue is not one that would be very easy to resolve; As this has been a problem for decades. Discrimination and discriminatory design will always negatively impact people, and often have very little benefits at that. Being from a minority ...

Reading Annotation Blog 2.4

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  In North American society, taking away women, African Americans, Hispanic Americans, French Canadians, Native peoples, Asian Americans, lesbians and gay men, people with disabilities, anyone who is not Christian, working class and poor people, and so forth, one is left with a very small “core.” An image that shows the complexity of these overlapping categories is that of a huge Venn diagram with many sets limited by Boolean ANDs. The white AND male AND straight AND European AND Christian AND middle-class AND able-bodied AND Anglo mainstream becomes a very small minority . . . , and each set implies what it is not. The implication of this image is that not every person, not every discourse, not every concept, has equal weight. Some discourses simply wield more power than others.28 Noble, Safiya Umoja.  Algorithms of Oppression : How Search Engines Reinforce Racism , New York University Press, 2018.  ProQuest Ebook Central , http://ebookcentral.proquest.com/lib/wsu/detail...