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Data Conscience: Algorithmic Siege on our Humanity

Data Conscience: Algorithmic Siege on our Humanity

Data Conscience: Algorithmic Siege on our Humanity
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Data Conscience: Algorithmic Siege on our Humanity Paperback - 2022

by Marshall, Brandeis Hill

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Wiley, 2022-09-21. 1. paperback. New. 7.10x0.90x9.10. Buy with confidence. Excellent Customer Service & Return policy.
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Details

  • Title Data Conscience: Algorithmic Siege on our Humanity
  • Author Marshall, Brandeis Hill
  • Binding Paperback
  • Edition 1
  • Condition New
  • Pages 352
  • Volumes 1
  • Language ENG
  • Publisher Wiley
  • Publication date 2022-09-21
  • Features Glossary
  • Bookseller's Inventory # DADAX1119821185
  • ISBN 9781119821182 / 1119821185
  • Weight 1.14 lbs (0.52 kg)
  • Dimensions 9.22 x 7.38 x 0.7 in (23.42 x 18.75 x 1.78 cm)
  • Size 7.10x0.90x9.10
  • Category Computers - Data Base Management
  • Quantity available 6

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Reader reviews for Data Conscience: Algorithmic Siege on our Humanity

From the publisher

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

From the rear cover

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

About the author

DR. BRANDEIS HILL MARSHALL, PhD, is a computer scientist, tech educator, and data equity consultant. She is a thought leader in broadening participating in data science and puts inclusivity and equity at the center of her work. She obtained her doctorate in Computer Science from Rensselaer Polytechnic Institute.

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