លើកស្ទួយសាលារៀន,
ជំរុញចិត្តអ្នកសិក្សា
មជ្ឈមណ្ឌលឌីជីថលសម្រាប់សាលារៀន ក្នុងការដាក់បង្ហាញបណ្តុំឯកសារ គ្រប់គ្រងបញ្ជីសៀវភៅ និងផ្តល់ធនធានសិក្សាប្រកបដោយគុណភាពដល់សិស្សានុសិស្ស។
Gouverner par les données ? Pour une sociologie politique du numérique
Theviot, Anaïs
Gouverner par les données ? Pour une sociologie politique du numérique - Lyon ENS Éditions 2023 - 1 electronic resource (288 p.) - Gouvernement en question(s) .
Open Access
This book is an invitation to enter the black box of algorithms, not from a technical point of view but from the perspective of political sociology. Does the proliferation of data available online, coupled with the progress of artificial intelligence, impact the way we govern? Can algorithms ‘predict’ citizens' behaviour? How are these so-called predictive algorithms made, and by whom? Are they neutral and objective? What are the social, ethical and political issues involved in using data? And what are the commercial and market strategies at work? Can we still protect our data? Behind the processing of data, there are many different visions of the world at work. The point is to consider the algorithm as a political and social object, produced by actors as the result of private and now public commissions as well. These lines of code and complex calculations cannot be dissociated from the conditions of their production: they are embedded in a specific organisational and professional set-up and carried by political intentions and goals. Based on a series of case studies and through the contribution of extensive and unpublished empirical investigations, this volume provides a context for how our data are used and how this may influence governance and decision-making. The strength of this book, at the crossroads with economic sociology, law, political science and computer science, is to lay down the foundations for a political sociology of data and the digital age with the aim of surpassing and deconstructing the myths and beliefs conveyed by big data.
All rights reserved
French
books.enseditions.44773 9791036205989 9791036205965
10.4000/books.enseditions.44773 doi
Sociology
personal data protection governance predictive algorithm myths big data
Gouverner par les données ? Pour une sociologie politique du numérique - Lyon ENS Éditions 2023 - 1 electronic resource (288 p.) - Gouvernement en question(s) .
Open Access
This book is an invitation to enter the black box of algorithms, not from a technical point of view but from the perspective of political sociology. Does the proliferation of data available online, coupled with the progress of artificial intelligence, impact the way we govern? Can algorithms ‘predict’ citizens' behaviour? How are these so-called predictive algorithms made, and by whom? Are they neutral and objective? What are the social, ethical and political issues involved in using data? And what are the commercial and market strategies at work? Can we still protect our data? Behind the processing of data, there are many different visions of the world at work. The point is to consider the algorithm as a political and social object, produced by actors as the result of private and now public commissions as well. These lines of code and complex calculations cannot be dissociated from the conditions of their production: they are embedded in a specific organisational and professional set-up and carried by political intentions and goals. Based on a series of case studies and through the contribution of extensive and unpublished empirical investigations, this volume provides a context for how our data are used and how this may influence governance and decision-making. The strength of this book, at the crossroads with economic sociology, law, political science and computer science, is to lay down the foundations for a political sociology of data and the digital age with the aim of surpassing and deconstructing the myths and beliefs conveyed by big data.
All rights reserved
French
books.enseditions.44773 9791036205989 9791036205965
10.4000/books.enseditions.44773 doi
Sociology
personal data protection governance predictive algorithm myths big data