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Titlebook: Understand, Manage, and Prevent Algorithmic Bias; A Guide for Business Tobias Baer Book 2019 Tobias Baer 2019 algorithmic bias.decision bia

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發(fā)表于 2025-3-21 20:07:30 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Understand, Manage, and Prevent Algorithmic Bias
副標(biāo)題A Guide for Business
編輯Tobias Baer
視頻videohttp://file.papertrans.cn/942/941284/941284.mp4
概述Teaches the many sources of algorithmic bias and shows the holistic measures you can use to manage and prevent bias.Provides practical, proven techniques to effectively combat and eliminate bias.Addre
圖書封面Titlebook: Understand, Manage, and Prevent Algorithmic Bias; A Guide for Business Tobias Baer Book 2019 Tobias Baer 2019 algorithmic bias.decision bia
描述.Are algorithms friend or foe?.The human mind is evolutionarily designed to take shortcuts in order to survive. We jump to conclusions because our brains want to keep us safe. A majority of our biases work in our favor, such as when we feel a car speeding in our direction is dangerous and we instantly move, or when we decide not take a bite of food that appears to have gone bad. However, inherent bias negatively affects work environments and the decision-making surrounding our communities. While the creation of algorithms and machine learning attempts to eliminate bias, they are, after all, created by human beings, and thus are susceptible to what we call .algorithmic bias...In .Understand, Manage, and Prevent Algorithmic Bias., author Tobias Baer helps you understand where algorithmic bias comes from, how to manage it as a business user or regulator, and how data science can prevent bias from entering statistical algorithms. Baer expertly addresses someof the 100+ varieties of natural bias such as confirmation bias, stability bias, pattern-recognition bias, and many others. Algorithmic bias mirrors—and originates in—these human tendencies. Baer dives into topics as diverse as anom
出版日期Book 2019
關(guān)鍵詞algorithmic bias; decision bias; machine bias; machine learning; artificial intelligence; debiasing; predi
版次1
doihttps://doi.org/10.1007/978-1-4842-4885-0
isbn_softcover978-1-4842-4884-3
isbn_ebook978-1-4842-4885-0
copyrightTobias Baer 2019
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 23:38:40 | 只看該作者
How Algorithms Debias Decisionsin how an algorithm works. More specifically, I will show how a . algorithm works and how it thereby can . human bias; in later chapters you then can understand more easily how algorithms can go awry (i.e., show bias)—and what the different options are for addressing this problem.
板凳
發(fā)表于 2025-3-22 04:23:12 | 只看該作者
地板
發(fā)表于 2025-3-22 05:58:22 | 只看該作者
Algorithmic Biases and Social Mediathe various biases discussed so far can interact and reinforce each other, and it illustrates how algorithmic bias can be dynamic. Rather than set in stone, the bias can develop and grow over time out of an interaction between user and algorithm—the biases of both reinforce each other until the result can be a discomfortingly strong distortion.
5#
發(fā)表于 2025-3-22 09:26:27 | 只看該作者
Assessing the Risk of Algorithmic Biasn many situations, algorithms make better decisions than alternative approaches: they make less errors (especially because human decisions often are even more biased) and can be both faster and cheaper. Introducing an algorithm to make decisions may come at the price of new biases, however.
6#
發(fā)表于 2025-3-22 16:01:20 | 只看該作者
How to Use Algorithms Safelyher approaches (such as even more biased humans). This situation can be compared to a life-saving medicine with serious side-effects. Just as the doctor will try to find ways to alleviate the side-effects of a medication, in this chapter we will discuss what steps you can take to protect yourself from algorithmic bias.
7#
發(fā)表于 2025-3-22 20:12:59 | 只看該作者
How to Detect Algorithmic Biasesers showing up in some report. Even if no bad intentions are involved, a poorly calculated or interpreted number can seriously mislead you. This chapter is a comprehensive review of how best to monitor algorithms for biases from a user’s perspective.
8#
發(fā)表于 2025-3-22 22:08:26 | 只看該作者
Biases Introduced by the Algorithm Itselfst specific profiles of instances. Much of this can be considered noise, but every once in a while, such an algorithmic bias can be magnified, reinforced, or even whipped up by the context of how the algorithm is used, in which case the effect of such an algorithmic bias might grow out of proportion.
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發(fā)表于 2025-3-23 02:19:16 | 只看該作者
10#
發(fā)表于 2025-3-23 07:43:11 | 只看該作者
Bias in Human Decision-Makingtanding algorithmic biases is therefore to understand human biases. And while colloquially "bias" is often deemed to be a bad thing that considerate, well-meaning people would eschew, it actually is central to the way the human brain works. The reason is that nature needs to solve for three competin
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