Data Conscience Data Conscience

Data Conscience

Algorithmic Siege on our Humanity

    • ¥3,800
    • ¥3,800

発行者による作品情報

DATA CONSCIENCE ALGORITHMIC S1EGE ON OUR HUM4N1TY
EXPLORE HOW D4TA STRUCTURES C4N HELP OR H1NDER SOC1AL EQU1TY

Data has enjoyed ‘bystander’ status as we’ve attempted to digitize responsibility and morality in tech. In fact, data’s importance should earn it a spot at the center of our thinking and strategy around building a better, more ethical world. It’s use—and misuse—lies at the heart of many of the racist, gendered, classist, and otherwise oppressive practices of modern tech.

In Data Conscience: Algorithmic Siege on our Humanity, computer science and data inclusivity thought leader Dr. Brandeis Hill Marshall delivers a call to action for rebel tech leaders, who acknowledge and are prepared to address the current limitations of software development. In the book, Dr. Brandeis Hill Marshall discusses how the philosophy of “move fast and break things” is, itself, broken, and requires change.

You’ll learn about the ways that discrimination rears its ugly head in the digital data space and how to address them with several known algorithms, including social network analysis, and linear regression

A can’t-miss resource for junior-level to senior-level software developers who have gotten their hands dirty with at least a handful of significant software development projects, Data Conscience also provides readers with:
Discussions of the importance of transparency Explorations of computational thinking in practice Strategies for encouraging accountability in tech Ways to avoid double-edged data visualization Schemes for governing data structures with law and algorithms

ジャンル
コンピュータ/インターネット
発売日
2022年
8月19日
言語
EN
英語
ページ数
352
ページ
発行者
Wiley
販売元
John Wiley & Sons, Inc.
サイズ
218.4
MB
The Smart Nonprofit The Smart Nonprofit
2022年
Human-Centered Data Science Human-Centered Data Science
2022年
(Dis)Obedience in Digital Societies (Dis)Obedience in Digital Societies
2022年
Algorithm Audit: Why, What, and How? Algorithm Audit: Why, What, and How?
2021年
Data for the People Data for the People
2017年
The Visual Organization The Visual Organization
2014年