Ebook: Discrimination and Privacy in the Information Society: Data Mining and Profiling in Large Databases

Vast amounts of data are nowadays collected, stored and processed, in an effort to assist in making a variety of administrative and governmental decisions. These innovative steps considerably improve the speed, effectiveness and quality of decisions. Analyses are increasingly performed by data mining and profiling technologies that statistically and automatically determine patterns and trends. However, when such practices lead to unwanted or unjustified selections, they may result in unacceptable forms of discrimination.

Processing vast amounts of data may lead to situations in which data controllers know many of the characteristics, behaviors and whereabouts of people. In some cases, analysts might know more about individuals than these individuals know about themselves. Judging people by their digital identities sheds a different light on our views of privacy and data protection.

This book discusses discrimination and privacy issues related to data mining and profiling practices. It provides technological and regulatory solutions, to problems which arise in these innovative contexts. The book explains that common measures for mitigating privacy and discrimination, such as access controls and anonymity, fail to properly resolve privacy and discrimination concerns. Therefore, new solutions, focusing on technology design, transparency and accountability are called for and set forth.

---

Vast amounts of data are nowadays collected, stored and processed, in an effort to assist in making a variety of administrative and governmental decisions. These innovative steps considerably improve the speed, effectiveness and quality of decisions. Analyses are increasingly performed by data mining and profiling technologies that statistically and automatically determine patterns and trends. However, when such practices lead to unwanted or unjustified selections, they may result in unacceptable forms of discrimination.

Processing vast amounts of data may lead to situations in which data controllers know many of the characteristics, behaviors and whereabouts of people. In some cases, analysts might know more about individuals than these individuals know about themselves. Judging people by their digital identities sheds a different light on our views of privacy and data protection.

This book discusses discrimination and privacy issues related to data mining and profiling practices. It provides technological and regulatory solutions, to problems which arise in these innovative contexts. The book explains that common measures for mitigating privacy and discrimination, such as access controls and anonymity, fail to properly resolve privacy and discrimination concerns. Therefore, new solutions, focusing on technology design, transparency and accountability are called for and set forth.

---

Vast amounts of data are nowadays collected, stored and processed, in an effort to assist in making a variety of administrative and governmental decisions. These innovative steps considerably improve the speed, effectiveness and quality of decisions. Analyses are increasingly performed by data mining and profiling technologies that statistically and automatically determine patterns and trends. However, when such practices lead to unwanted or unjustified selections, they may result in unacceptable forms of discrimination.

Processing vast amounts of data may lead to situations in which data controllers know many of the characteristics, behaviors and whereabouts of people. In some cases, analysts might know more about individuals than these individuals know about themselves. Judging people by their digital identities sheds a different light on our views of privacy and data protection.

This book discusses discrimination and privacy issues related to data mining and profiling practices. It provides technological and regulatory solutions, to problems which arise in these innovative contexts. The book explains that common measures for mitigating privacy and discrimination, such as access controls and anonymity, fail to properly resolve privacy and discrimination concerns. Therefore, new solutions, focusing on technology design, transparency and accountability are called for and set forth.

Content:
Front Matter....Pages 1-16
Front Matter....Pages 1-1
Data Dilemmas in the Information Society: Introduction and Overview....Pages 3-26
What Is Data Mining and How Does It Work?....Pages 27-42
Why Unbiased Computational Processes Can Lead to Discriminative Decision Procedures....Pages 43-57
Front Matter....Pages 59-59
A Comparative Analysis of Anti-Discrimination and Data Protection Legislations....Pages 61-89
The Discovery of Discrimination....Pages 91-108
Discrimination Data Analysis: A Multi-disciplinary Bibliography....Pages 109-135
Risks of Profiling and the Limits of Data Protection Law....Pages 137-152
Front Matter....Pages 153-153
Explainable and Non-explainable Discrimination in Classification....Pages 155-170
Knowledge-Based Policing: Augmenting Reality with Respect for Privacy....Pages 171-189
Combining and Analyzing Judicial Databases....Pages 191-206
Front Matter....Pages 207-207
Privacy-Preserving Data Mining Techniques: Survey and Challenges....Pages 209-221
Techniques for Discrimination-Free Predictive Models....Pages 223-239
Direct and Indirect Discrimination Prevention Methods....Pages 241-254
Introducing Positive Discrimination in Predictive Models....Pages 255-270
Front Matter....Pages 271-271
From Data Minimization to Data Minimummization....Pages 273-287
Quality of Information, the Right to Oblivion and Digital Reputation....Pages 289-299
Transparency in Data Mining: From Theory to Practice....Pages 301-324
Data Mining as Search: Theoretical Insights and Policy Responses....Pages 325-338
Front Matter....Pages 339-339
The Way Forward....Pages 341-357
Back Matter....Pages 0--1

---

Vast amounts of data are nowadays collected, stored and processed, in an effort to assist in making a variety of administrative and governmental decisions. These innovative steps considerably improve the speed, effectiveness and quality of decisions. Analyses are increasingly performed by data mining and profiling technologies that statistically and automatically determine patterns and trends. However, when such practices lead to unwanted or unjustified selections, they may result in unacceptable forms of discrimination.

Processing vast amounts of data may lead to situations in which data controllers know many of the characteristics, behaviors and whereabouts of people. In some cases, analysts might know more about individuals than these individuals know about themselves. Judging people by their digital identities sheds a different light on our views of privacy and data protection.

This book discusses discrimination and privacy issues related to data mining and profiling practices. It provides technological and regulatory solutions, to problems which arise in these innovative contexts. The book explains that common measures for mitigating privacy and discrimination, such as access controls and anonymity, fail to properly resolve privacy and discrimination concerns. Therefore, new solutions, focusing on technology design, transparency and accountability are called for and set forth.

Content:
Front Matter....Pages 1-16
Front Matter....Pages 1-1
Data Dilemmas in the Information Society: Introduction and Overview....Pages 3-26
What Is Data Mining and How Does It Work?....Pages 27-42
Why Unbiased Computational Processes Can Lead to Discriminative Decision Procedures....Pages 43-57
Front Matter....Pages 59-59
A Comparative Analysis of Anti-Discrimination and Data Protection Legislations....Pages 61-89
The Discovery of Discrimination....Pages 91-108
Discrimination Data Analysis: A Multi-disciplinary Bibliography....Pages 109-135
Risks of Profiling and the Limits of Data Protection Law....Pages 137-152
Front Matter....Pages 153-153
Explainable and Non-explainable Discrimination in Classification....Pages 155-170
Knowledge-Based Policing: Augmenting Reality with Respect for Privacy....Pages 171-189
Combining and Analyzing Judicial Databases....Pages 191-206
Front Matter....Pages 207-207
Privacy-Preserving Data Mining Techniques: Survey and Challenges....Pages 209-221
Techniques for Discrimination-Free Predictive Models....Pages 223-239
Direct and Indirect Discrimination Prevention Methods....Pages 241-254
Introducing Positive Discrimination in Predictive Models....Pages 255-270
Front Matter....Pages 271-271
From Data Minimization to Data Minimummization....Pages 273-287
Quality of Information, the Right to Oblivion and Digital Reputation....Pages 289-299
Transparency in Data Mining: From Theory to Practice....Pages 301-324
Data Mining as Search: Theoretical Insights and Policy Responses....Pages 325-338
Front Matter....Pages 339-339
The Way Forward....Pages 341-357
Back Matter....Pages 0--1
....