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Könyv Data Conscience - Algorithmic Siege on Our Humanity Marshall

Data Conscience - Algorithmic Siege on Our Humanity

Szerző: Marshall, Brandeis Hill
Nyelv: Angol
Kötés: Puha kötésű
Kiadó: John Wiley & Sons Inc
Elérhetőség: Beszállítói készleten alacsony példányszámban
Küldés 11-15 napon belül
11 115 Ft
DATA CONSCIENCE ALGORITHMIC S1EGE ON OUR HUM4N1TYEXPLORE HOW D4TA STRUCTURES C4N HELP OR H1NDER SOC1...

Információk a könyvről

Szerző
Marshall, Brandeis Hill
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2022
oldal
352
EAN
9781119821182
ISBN
1119821185
Enbook ID
38709123
Kiadó
John Wiley & Sons Inc
Súly
516
Méretek
237 x 186 x 20

Teljes leírás

DATA CONSCIENCE ALGORITHMIC S1EGE ON OUR HUM4N1TYEXPLORE HOW D4TA STRUCTURES C4N HELP OR H1NDER SOC1AL EQU1TYData 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 regressionA 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

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