Algorithms of Oppression
2018 book by Safiya Umoja Noble Algorithms of Oppression: How Search Engines Reinforce Racism is a 2018 book by Safiya Umoja Noble in the fields of information science, machine learning, and human-computer interaction.[1][2][3][4] Overview[edit] Algorithms of Oppression is a text based on over six years of academic research on Google search algorithms.
AmIUnique
On this page, you will find links to tools that can help improve your privacy on the Internet. With respect to fingerprinting, the best solutions that exist today are to simply block tracking scripts. We cannot recommend spoofers because there is a risk that fingerprinters can detect such spoofing techniques quite easily, which would quickly identify you as a liar. Because the number of spoofers is likely low, your other discriminating data (e.g. fonts and plugins) should be more than sufficient to fingerprint and track you.
Weapons of Math Destruction
Weapons of Math Destruction is a 2016 American book about the societal impact of algorithms, written by Cathy O'Neil. It explores how some big data algorithms are increasingly used in ways that reinforce preexisting inequality. It was longlisted for the 2016 National Book Award for Nonfiction,[1][2][3] has been widely reviewed,[4] and won the Euler Book Prize. Overview[edit] O'Neil, a mathematician, analyses how the use of big data and algorithms in a variety of fields, including insurance, advertising, education, and policing, can lead to decisions that harm the poor, reinforce racism, and amplify inequality. According to National Book Foundation:[1]
Books – Virginia Eubanks
Automating Inequality:How High-Tech Tools Profile, Police, and Punish the Poor Available January 16, 2018. Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems—rather than humans—control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor.
Furious blame game after 16,000 Covid cases are missed due to Excel glitch
An Excel bungle that led to thousands of cases being lost in government systems masked daily cases in the UK hitting 11,000. A clearer picture of the country's outbreak has emerged after some 16,000 confirmed infections had to be added to the daily totals running back more than a week. Counted by the date specimens were collected, rather than the date the government published them, the UK had 11,404 cases on September 30, almost as many as were reported in the next two days combined.
