A needed book, though be aware that this is very much an academic book (I'm from the STEM side of things, but I'm dimly aware that humanities publish books not papers) and occasionally reads like a grant proposal ("In this work, I show that...")

Noble's thesis is that we port our biases into our technology and information systems, and though the promise of the internet is democracy, in practice it is driven by advertisers gaming the system with AdWords, hyperlinking, etc. We'd like to think Google is rad for all the free tools, but a business needs to make money, and we are the product.

I do feel this could've dug deeper- there were a lot of "my work demonstrates..." sentences and I expected qualitative data, but I recognize that's my own STEMy expectations. Noble does highlight further places that can be built on this preliminary look at SEO and systemic biases (in particular, the influence of pornography on various web things like streaming and e-commerce) but I'm left wanting more. ( )

Como o Google fomenta e lucra com o racismo

Pesquise no Google por “garotas negras”: o que você encontra? Termos sexualmente explícitos provavelmente aparecerão como os principais resultados. Mas, se você digitar “garotas brancas”, os resultados serão radicalmente diferentes. Os sites pornográficos sugeridos e frases como “por que as mulheres negras são tão atrevidas?” ou “por que as mulheres negras são tão zangadas?” apresentam um retrato perturbador da feminilidade negra na sociedade moderna.

Em Algoritmos de Opressão, Safiya Umoja Noble desafia a ideia de que mecanismos de pesquisa como o Google oferecem igualdade de condições para todas as formas de ideias, identidades e atividades. A discriminação de dados é um problema social real; Safiya Noble argumenta que a combinação de interesses privados na promoção de certos sites, juntamente com o status de monopólio de um número relativamente pequeno de mecanismos de pesquisa na internet, leva a um conjunto tendencioso de algoritmos de busca que discriminam pessoas negras, especificamente mulheres.

Através de análises textuais e de mídia, bem como de uma extensa pesquisa sobre publicidade on-line, a autora expõe uma cultura de racismo e sexismo. À medida que os mecanismos de pesquisa e suas empresas crescem em importância, operando inclusive como um importante veículo para o aprendizado do ensino fundamental e médio, a compreensão e reversão dessas tendências inquietantes e práticas discriminatórias é de extrema importância.

Um relato original, surpreendente e perturbador do preconceito na internet.

Rating: 4.5* of five

The Publisher Says: Run a Google search for "black 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 society.

In Algorithms of Oppression, Safiya Umoja Noble challenges the idea that search engines like Google offer an equal 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 discriminate against people of color, specifically women of color.

Through an analysis of textual and media searches as well as extensive research on paid online advertising, Noble exposes 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 disquieting trends and discriminatory practices is of utmost importance.

An 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 21st century.

I RECEIVED A DRC FROM THE PUBLISHER VIA EDELWEISS+. THANK YOU.

My Review: The world, as the Internet has shaped it, took a promise of information access and educational opportunity unparalleled in human history and screwed it up to the point it reinforces the evils and stupidities it could so easily have alleviated.

The problem, it transpires, is both blindness..."*I* am no racist, or a sexist! Why, some of my best friends..." is not new, nor is it uncommon in any society...and neither is hubristic malevolence (Cambridge Analytica, for example). We're two decades in to a giant, uncontrolled social experiment. Voices like Author Noble's are still notable for their infrequence of prominence in the rarefied world of Congressional hearings and the European Union's creation of the GDPR.

The issues that Author Noble raises in this book need your attention. You, the searcher, are the product that Google and the other search engines are selling to earn their absurd, unconscionable, inadequately taxed profits. Every time you log on to the internet, Google knows...use other search engines, never click on any links, and Google still knows you're there. That's the Orwellian nightmare of it...like East Germany's Stasi, they're everywhere, in every website you visit. Unlike the Stasi, they are possessed of the capacity to quantify and analyze all the information you generate, and sell it to anyone who can use it. For you or against you, as long as the check clears, Google and its brethren couldn't care less.

(There are links to information sources in the blogged version of this review at Expendable Mudge Muses Aloud.) ( )

A thorough overview of the systematic biases in Google in particular, and many other web technologies in general, that adversely impact Black women in particular, and other marginalised groups in general. Because the general idea of this wasn't new to me some of the writing sometimes felt a bit repetitive but it was really good to have all the examples and the narrative tying it all together. And important that libraries don't get off scott-free, with biases embedded in their own classification systems! ( )

Although a solid summary of the larger problem of subtle bias in search engine results, this book promised much more in the way of explaining the source of that bias. Although the author recognizes and criticizes "the idea that it is not the search engine that is the problem but, rather, the users of search engines who are. It suggests that what is popular is simply what rises to the top of the search pile," she does not provide any information to distinguish between the two alternatives. She assumes that the problem is Google, and not Google users, without providing any foundation for that assumption, and frames the entire book in terms of this undefended conclusion. For example, she sees no difference between page results and query auto suggestions, but my understanding at least is that users are much more influential in the latter than the former.

I had hoped for some actual technical discussion of how page results are generated, and what aspects are under the control of Google and which are merely aggregating the preferences of actual users, but that never comes. It does not help that, for a book published in 2018, the bulk of her examples are ancient, often from 2011. The Internet, and Google with it, has changed drastically in the last seven years, but her discussion barely recognizes the fact. I suspect the first section of the book, with the very outdated examples, was the core of her 2012 dissertation, which has here been included with very little change or update. Later chapters attempt to bring in more recent issues, but they feel like quick glosses meant to fill out the need to expand the dissertation to book length, and lack the more serious consideration that went into the earlier section. In all honesty, she should have written an entirely new, current book rather than attempt to update the older material. She has the background to do that, but she is trapped by the confines of trying to publish the dissertation as is.

With more technical expertise, and data more contemporary to the date of publication, this could have been a more exciting contribution. Failing that, it is still interesting on the general points, if dusty and outmoded in the details. ( )