Ethical Data and Information Management: Concepts, tools and methods
By Katherine O’Keefe and Daragh O Brien
Contents:
About the authors xii
Acknowledgements xiii
List of abbreviations xiv
I ntroduction: why write a book on information ethics? 1
What will we cover in this chapter? 1
Introduction 1
The tools of data gathering 2
The tools of data analytics 4
With great power comes great responsibility 8
The data-driven dilemma 9
The innovator’s dilemma 11
Societal value versus individual rights – the root of our own
dilemmas 12
Introducing the rest of the book 14
Chapter summary 15
Questions 15
Further reading 16
References 16
01 Ethics in the context of information management 19
What will we cover in this chapter? 19
Ethics and the evolution of technology 20
The evolution of privacy and technology 24
Other ethical dilemmas 25
The drive for effective ethics in information management 30
Chapter summary 33
Questions 33
Notes 34
Further reading 34
References 34
02 I ntroduction to ethical concepts and frameworks 36
What will we cover in this chapter? 36
Introduction 36
Ethical theories you should know about 39
Common elements of ethical frameworks 47
Chapter summary 50
Questions 50
Note 50
Further reading 51
References 51
03 E thics, privacy and analytics 53
What will we cover in this chapter? 53
Analytics and data science: an ethical challenge 54
What is data analytics? 55
The ethical issues in data analytics 55
Chapter summary 75
Questions 76
Notes 76
Further reading 77
References 77
04 Information ethics and artificial intelligence: concepts
and thought experiments 81
What will we cover in this chapter? 81
Introduction 82
Defining AI 83
Ethical issues in AI 84
Principles for accountable algorithms 88
Specific examples of developments
in AI with ethical impacts 89
Who benefits? Justice and human dignity
in AI development 91
What does AI tell us about us? 92
Chapter summary 93
Questions 93
Further reading 94
References 95
05 E thics in the Data Management Body of Knowledge 97
What will we cover in this chapter? 97
Introducing the DAMA DMBOK 98
Data governance 98
Data modelling 109
Data quality management 112
Data warehousing and business intelligence 116
Data science and ‘big data’ 119
Chapter summary 123
Questions 124
Notes 124
Further reading 124
References 125
06 Developing an ethical architecture for information
management 126
What will we cover in this chapter? 126
Information ethics and architecture – what is the connection? 127
Implementing ethical architecture: common challenges 150
Zachman, ethical architecture and the long-
term vision 151
Chapter summary 152
Questions 153
Note 153
Further reading 153
References 153
07 I ntroducing the Ethical Enterprise Information
Management (E2IM) framework 156
What will we cover in this chapter? 156
Building a model for ethical enterprise information
management 157
Ethics and big data 177
Conclusion 181
Chapter summary 183
Questions 183
Note 184
Further reading 184
References 184
08 I nformation ethics as an information
quality system 186
What will we cover in this chapter? 186
Ethics as a quality system 187
Applying quality management principles to ethical information
management 190
Chapter summary 219
Questions 219
Note 220
Further reading 220
References 220
09 I nformation ethics and data governance 223
What will we cover in this chapter? 223
Introduction 223
How data governance supports ethics 224
Principles and modes of governance 226
Chapter summary 251
Questions 252
Note 252
Further reading 252
References 253
10 Information ethics and risk: the rise of the Ethical
What will we cover in this chapter? 255
Introduction 256
Looking for parallel models 258
Privacy by Design 259
Privacy Engineering 260
The E2IM Ethical Impact Assessment model 263
Chapter summary 281
Questions 281
Note 282
Further reading 282
References 283
11 Making the ethical information management change 284
What will we cover in this chapter? 284
What is change management (and why does it often go wrong)? 285
The value proposition for ethical information management? 307
Chapter summary 307
Questions 308
Further reading 308
References 309
And in conclusion… 310
What is a data geek to do? 311
References 315
Index 317