REVIEW Algorithms of Oppression How Search Engines Reinforce Racism 107

CHARACTERS Algorithms of Oppression How Search Engines Reinforce Racism

REVIEW Algorithms of Oppression How Search Engines Reinforce Racism 107 ð ➚ [KINDLE] ❄ Algorithms of Oppression How Search Engines Reinforce Racism By Safiya Umoja Noble ➤ – Run a Google search for black girls what will you find Big Booty and other sexually explicit tSes a culture of racism and sexism in the way discoverability is created online As search engines and their related companies grow in importance operating as a source for email a major vehicle for primary and secondary school learning and beyond understanding and reversing these disuieting of Oppression How Search Engines Kindle trends and discriminatory practices is of utmost importanceAn original surprising and at times disturbing account of bias on the internet Algorithms of Oppression contributes to our understanding of how racism is created maintained and disseminated in the st centur. Interesting and so appreciative of Safiya who got the conversation started a few years ago about bias algorithms But this book would have been a better article because it was extremely repetitive

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Run Oppression How Search Engines PDFEPUB or a Google search for black Oppression How Epub #223 girls what will you find Big Booty and other sexually explicit terms are likely to come up as top search terms But if you type in white girls the results are radically different The suggested porn sites and un moderated discussions about why black women are so sassy or why black women are so angry presents a disturbing portrait of black womanhood in modern societyIn Algorithms of PDFEPUBAlgorithms of Oppression Safiya Umoja Noble challenges the idea of Oppression How Search Engines Kindle that s. The master algorithm seems to give its name an inglorious connotationWEIRD comes to mind White Educated Industrialized Rich and Democratized This problem of many humanities has also made it into the coding of algorithms Previously in history the problem was that many foundations for research used a too small and homogeneous pool of people and most of the study was done by white male and wealthy people so that their results were not representative for the whole populationAnd that in two ways On the one hand prejudices when they were not yet politically incorrect flowed directly into pseudo research As emancipation and euality spread it were only the indirect unvoiced personal opinions But the research leaders professors and chief executives incorporated their conscious and unconscious worldviews into the design of uestions research subjects experimental methods and so onSecondly these foundations for the research were presented to an eually biased audience as well as test subjects For a long time much of the research has been based on these 2 foundations and is it indirectly until today because new research builds on older results It is like trying to finally remove a bug in the source code that evolved over the years with the bug as a central element of the whole system That alone is not the only severe problem but the thousands of ramifications it left behind in all other updates and versions Like cancer it has spread everywhere This makes it very expensive to impossible to remove all these mistakes again A revision would be very elaborate and associated with the resistance of many academics who assume dangers for their reputation or even whole work They would see their field of research and their special areas under attack because nobody likes criticism and that would be a hard one to swallowWhat does this have to do with the algorithms The programming of software is in the same hands as in the example above Certainly not in such dimensions but subconsciously inadvertent opinions may flow into it and the way search engines generate results is even problematic Especially in the last few years deep learning AIs big data and GANs Generative Adversarial Networks have been much integrated into the development so that the old prejudices could begin evolving in the machines themselves without extra human influenceThis means that in principle no one can say any decidedly how the AIs come to their conclusions The complexity is so high that even groups of specialists can only try timid approaches to reverse engineering How precisely the AI has become racist sexist or homophobic cannot be said any and worse it can not be uickly repaired in hindsight Because the reaction patterns on a search input cannot be selected in advanceThere is a sad explanation Unfortunately people are often infested with low instincts and false destructive mentalities When millions of people have been focusing their internet activity on aggressive hostility for decades the algorithm learns to recognize their desires There is a lot of money to earn and the AI should provide the users with what they want The market forces determine the actions of the Internet giants and these give the public what it craves for Ethics and individualized advertising can hardly follow the same goals This is even the case for news media and publishers who suffer from the same problems as the algorithms With the difference that they play irrelevant rhetorical games to distract from the system inherent dysfunctionsThe same problem exists with the automatic proposal function of online trade which can inadvertently promote dangerous or aggressive behavior Or with the spread of extremist videos by showing new and similar ones that are automatically proposed allowing people to radicalize faster The AI does its job no matter what is searched forOn a small scale the dilemma has already been seen with language assistants and artificial intelligence degenerating in free interaction with humans For example Microsoft's intelligent self learning chatbot which was transformed into a hate filled misanthrope by trolls within days It is not difficult to imagine the dimension of the problem with the far spread of new technologiesOne of the ways to repair these malfunctions is time When people reset the AI's by doing neutral and regular searches That's too optimistic so it's likely we will have to find a technical solution before people get rational For both better alternatives the search ueries and the results would have to change significantly before there could be the beginning of positive developmentThe academic search results should not be underestimated These often false non scientific foundations on which many of the established sciences stand Even if the users became reasonable there would still be millions of nonsensical results and literature These fake antiuated buildings of thought on which many foundations of modern society are based must be the primary objective The results are the symptoms but those dangerous and wrong thinkings are the disease The long unresolved history behind it with all its injustices has to be reappraised because it is the reason for widespread poverty and ignorance which has its roots in wrong social models so that innocent AIs get deluded by search reuestsAnd the effects of search input and search results are mutually reinforcing The mirror that they hold for society testifies only to hidden prejudices However those feel saver in their secret corners because they are supposedly unrecognized and subtly stoked by populists additionally and for their benefit When wrong thinking has buried itself so deeply into a society it also becomes part of all the products of that cultureA wiki walk can be as refreshing to the mind as a walk through nature in this completely overrated real life outside books

Safiya Umoja Noble Ý 7 REVIEW

Algorithms of Oppression How Search Engines Reinforce RacismEarch engines like Google offer an eual playing field for all forms of ideas identities and activities Data discrimination is a real social problem Noble argues that the combination of private interests in promoting certain sites along with the monopoly status of a relatively small number of Internet search engines leads to a biased set of search algorithms that privilege whiteness and of Oppression How MOBI #183 discriminate against people of color specifically women of colorThrough an analysis of textual and media searches as well as extensive research on paid online advertising Noble expo. I must admit I was very eager to read this book A very necessary topic that really deserves to be tackled in a very thorough manner Racism sexism and discrimination in general are structural parts of societies in the West and we know that the net is no exception here I was really interested in finding out exactly 'how Search Engines reinforce Racism' That they do it is by now a common thing We know for instance how the alt right uses the internet and the algorithms of commercial platforms to push their racism into the world Safiaya Umoja Noble is an assistant professor in Information Studies at the university of California Los Angelos Considering this title I was expecting to readfind a methodologically well established analysis of the algorithms of Google and how it contributes to the spread an rise of racism and sexism My enthusiasm was severely tempered when I started reading and found that the used methodology was shaky at best Her methode consists out of 'Googling' words like black girls and analyzing the result of that Google session with a fixed framework of 'Black Feminism' Even though I'm greatly sympathetic to the Feminism and antiracism as a scientific field I'm missing a close analysis of the data Yes Black Girls gave pornofied results reflecting the huge commodification of women in the porn industry But similar results appeared if you search for latina girls and even white girls But maybe relevant they do not appear any at least not in Belgium The point is that methodologically speaking this is shaky Noble does not compare results with similar terms She does not even try to Google in different settings different browsers different privacy settings different computers different countries The point is you do not really know why you see what you see if you do not control your search and even then searching as a method is shaky The author clearly looks at Google as the all powerful and thus the force to blame she dismisses probably correct the idea that Google search reflects societal biases and racism Google itself is to blame because 'they are the owners of their own algorithms' True of course but she nowhere makes it stick that Google's algoritmes are build as algorithms of oppression as if they are racist themselves because of the lack of diversity on the floor What does stick is that Google is ranking things high up the list if 1 the are popular get lots of links and 2 if there are actors who are building sites with SEO in the back of their mind And 3 that Google tries to intervene the least possible I think that her argument that Google could and should edit the search results is powerful Yes Google can do that And yes they should to do that Racism is not an opinion And Google's algorithms are thus not neutral they not only show what is popular they make things popular And thus they should take up 'editorial responsability' The problem with this book is that there is 'moral claiming' than analysis of data I'm highly sympathetic to the cause I think that the concept of Algorithms of oppression has enormous potential but it deserve a much deeper analysis in how exactly 'commercial algorithms' can be turned into Algorithms of oppression in the interplay between activists Google and the broad audience