Data centric Living Algorithms Digitization and Regulation 1st Edition by Sridhar 0367554178 9780367554170

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ISBN 10: 0367554178

ISBN 13: 9780367554170

Author: V. Sridhar

This book explores how data about our everyday online behaviour are collected and how they are processed in various ways by algorithms powered by Artificial Intelligence (AI) and Machine Learning (ML). The book investigates the socioeconomic effects of these technologies, and the evolving regulatory landscape that is aiming to nurture the positive effects of these technology evolutions while at the same time curbing possible negative practices. The volume scrutinizes growing concerns on how algorithmic decisions can sometimes be biased and discriminative; how autonomous systems can possibly disrupt and impact the labour markets, resulting in job losses in several traditional sectors while creating unprecedented opportunities in others; the rapid evolution of social media that can be addictive at times resulting in associated mental health issues; and the way digital Identities are evolving around the world and their impact on provisioning of government services. The book also provides an in-depth understanding of regulations around the world to protect privacy of data subjects in the online world; a glimpse of how data is used as a digital public good in combating Covid pandemic; and how ethical standards in autonomous systems are evolving in the digital world. A timely intervention in this fast-evolving field, this book will be useful for scholars and researchers of digital humanities, business and management, internet studies, data sciences, political studies, urban sociology, law, media and cultural studies, sociology, cultural anthropology, and science and technology studies. It will also be of immense interest to the general readers seeking insights on daily digital lives.

Data centric Living Algorithms Digitization and Regulation 1st Table of contents:

1 Data-centric living

An introduction

1.1 Introduction

1.2 The Implications and challenges of digitization and datafication: Access and beyond

1.3 Motivation and structure

1.4 Part I: Challenges of digitization and datafication

1.4.1 Algorithms and their impact on society

1.4.2 Digitizing governance and welfare systems

1.4.3 Datafication in finance and healthcare

1.5 Part II: Technology and regulatory solutions

1.5.1 Protecting privacy

1.5.2 Protection of personal data across borders

1.5.3 Ethical standards in autonomous systems

1.6 Conclusion

Note

References

Part I Challenges of digitization and datafication

2 Algorithms in society

Arbitrage, bias, and culture

2.1 Introduction

2.2 Broader issues with technology deployment

2.3 Algorithms—A quick overview

2.3.1 Historical foundations

2.3.2 Theoretical foundations and limitations

2.3.3 Computers and minds

2.3.4 The pragmatic basis of algorithms

2.3.5 Models and reality

2.4 Algorithms and computing systems

2.5 Ethics and bias in algorithms

2.6 Algorithmic arbitration of culture

2.7 Other issues in the age of algorithms

2.7.1 Undue influence and restrictions

2.7.2 A historical precedent

2.8 Conclusion

References

3 Artificial intelligence and its effect on employment and skilling

3.1 Introduction

3.2 AI and the changing nature of work

3.2.1 Technical capabilities of AI systems

3.2.2 Suitability of tasks for AI

3.2.3 Emerging use cases of AI

3.3 Effects on employment

3.3.1 Economic incentives for firms to adopt AI

3.3.2 AI and job losses

3.3.3 Institutional role in socially acceptable AI

3.3.3.1 Role of AI in employment generation

3.3.3.2 Development of skills that complement changing nature of jobs

3.3.3.3 Social adjustment of displaced workers

3.4 A task-based framework to evaluate suitability of occupations for AI

3.5 Summary and conclusion

References

4 Continuing cybernetic musing

Behaviour shaping through data-driven feedback

4.1 Introduction

4.2 Elements of feedback control

4.2.1 Closing the loop

4.2.2 Aiding feedback: Buffering and feedforward

4.2.3 Feedforward to maintain allostasis

4.2.4 Stability and controllability

4.3 Control in social networking sites

4.3.1 Feedback in SNS design

4.3.2 Feedback data

4.3.3 Data variety

4.4 Conclusions

Notes

References

5 Data-driven identities

5.1 Introduction

5.2 Data-driven identities: Implications for socio-economic development

5.3 The effects of data-driven identities: A framework

5.4 Data-driven identities: Tales from the field

5.4.1 Access: From inclusion to digitally induced exclusions

5.4.2 Monitoring: Rebuilding the back-end of services

5.4.3 Policy: From access to rebuilding programme architectures

5.5 Conclusion

References

6 Inclusive digital governance

Reflecting on public value in a food security programme

6.1 Introduction

6.1.1 National food security act (NFSA) 2013 and the targeted public distribution system (TPDS) in India

6.1.2 ICTD and creating public value

6.2 Field site and methodology

6.3 Findings: The practice of TPDS in Bangalore

6.3.1 Ration card issue

6.3.2 Food grains issue

6.3.2.1 Information dissemination before issue of food grains

6.3.2.2 Disbursement of food grains at FPS

6.3.2.3 Notifications after issue of food grains

6.4 Discussion: Local-level adjustments for a TPDS that ‘works’

6.4.1 Ration card application and updating process, including Aadhaar seeding

6.4.2 Biometric authentication failures and workarounds

6.4.3 Information dissemination mechanisms and awareness

6.5 Conclusions

Notes

References

7 The social meaning of mobile money

Navigating digital payments, savings and credit in the global South

7.1 Introduction

7.2 The social meaning and life of money in a Digital Age

7.3 Understanding the social meaning of mobile money

7.4 Giving money: Remittances, payments and repayments using mobile money

7.4.1 Remittances

7.4.2 Payments and repayments

7.5 Receiving money: Income and loans

7.5.1 Income

7.5.2 Loans

7.6 Savings

7.7 Conclusion: Inclusion with choices?

Notes

References

8 Sharing and use of non-personal health information

Case of the COVID-19 pandemic

8.1 Information technology in healthcare

8.2 Privacy and security in open health information

8.2.1 Security of health information

8.3 Technologies that preserve information privacy

8.3.1 k-Anonymity

8.3.2 l-Diversity

8.3.3 t-Closeness

8.3.4 Differential privacy

8.4 Regulations on health information privacy

8.5 Non-personal data (NPD) as open public data

8.6 Use of open health information in COVID-19 pandemic

8.6.1 Taxonomy of COVID-19 data

8.6.1.1 Personal information

8.6.1.2 Location information

8.6.1.3 Contact tracing

8.6.1.4 Clinical information

8.6.1.5 Other related information

8.6.2 Processing and use of COVID-19 data across countries

8.6.2.1 Administration notification

8.6.2.2 User notification

8.6.2.3 Epidemiology research

8.7 Analysis of COVID-19 apps

8.7.1 Personal information

8.7.2 Contact tracing

8.7.3 Location tracking

8.7.4 Liability clauses

8.7.5 Concerns on COVID-19 apps

8.8 Sample analysis of COVID-19 public data sets

8.9 Conclusions

Note

References

Part II Technology and regulatory solutions

9 Evaluation of privacy policies of digital firms

9.1 Introduction to privacy taxonomy

9.2 Essentials of privacy regulations

9.2.1 Types of data

9.2.2 Data collection and informed consent

9.2.3 Data storage and processing

9.2.4 Obligations of data fiduciaries

9.3 Dimensions of privacy policy

9.3.1 What information is collected, why and how?

9.3.1.1 Cookie policy

9.3.2 What information is shared, to whom and why?

9.3.3 How and where is information stored?

9.3.3.1 Security of information

9.3.3.2 Location of information

9.3.4 How long is personal information retained?

9.3.5 Accessibility

9.3.6 Personal information about minors

9.3.7 Complaints and grievance redressal

9.4 Analysis of privacy policies of digital platforms

9.4.1 Information collected, purpose and consent

9.4.2 Information sharing

9.4.3 Information security and location

9.4.4 Information retention

9.4.5 Grievance redressal

9.4.6 Accessibility

9.5 Conclusions

9.5.1 Multi-party privacy

9.5.2 Economics of privacy policies

Notes

References

10 Incorporating privacy regulatory requirements in building software

10.1 Introduction

10.2 Privacy and data protection fundamentals

10.2.1 Legislature and regulatory bodies

10.2.2 Types of data protection regulation

10.2.3 Privacy principles

10.3 Standards, frameworks and principles

10.3.1 ISO/IEC 29100 standards

10.3.2 National Institute of Standards and Technology standards privacy framework

10.3.3 IEEE P7002 data privacy process

10.3.4 DSCI – Data security council of India standards

10.4 Software development process

10.5 Privacy by design principles

10.5.1 Example use case on privacy by design

10.6 Methodology for incorporating regulatory requirements in requirements phase of SDLC

10.6.1 Input

10.6.2 Processing components

10.6.3 Output

10.7 Specific process for integrating privacy requirements into SRS

10.8 Illustration of the framework

10.9 Summary and conclusion

Notes

References

11 Data protection regulation

Comparing approaches in the US, EU and India

11.1 Context and introduction

11.2 Methodology and scope

11.2.1 Boundaries of this comparison

11.3 Privacy and data protection in the USA

11.3.1 The choice of US legislations for comparison

11.3.2 The Privacy Act of 1974

11.3.3 Title V of the Gramm–Leach–Bliley Act, 1999

11.4 Privacy and data protection in the European Union

11.4.1 The general data protection regulation

11.5 Privacy and data protection in India

11.5.1 The Personal Data Protection Bill, 2019

11.6 Conclusion: Comparing the dimensions of data protection in the US, EU and India

Notes

References

12 Data localization and its effects on cross border digital trade

12.1 Introduction

12.2 Data nationalism and data localization policies across countries

12.2.1 EU general data protection regulation

12.2.2 The unique case of the U.S.

12.2.3 Regulations in India

12.3 Data localization and its effects on stakeholders

12.3.1 Effect on data fiduciaries

12.3.1.1 Cost of services

12.3.1.2 Quality and features of service

12.3.2 Effect on data subjects

12.3.2.1 Consumer welfare

12.3.2.2 Surveillance by foreign and local governments

12.3.2.3 Freedom of expression and censorship

12.3.3 Effect on the state and governments

12.3.3.1 Containment of terrorism and fraud

12.3.3.2 Privacy and security protection

12.3.3.3 Content regulation

12.3.3.4 Economic spill-overs

12.3.4 Data localization and its effects on consumers and data fiduciaries

12.4 Effect of data localization on digital trade: An agent-based simulation study

12.4.1 Producer agent

12.4.2 Consumer agent

12.4.3 Simulation results

12.5 Conclusions and policy implications

References

13 Ethical standards in autonomous systems

13.1 Introduction

13.2 Global landscape

13.2.1 Normative standards

13.2.2 Technical standards

13.3 Analysis

13.3.1 Case study: #TechWontBuildIt

13.4 Limitations of the study

13.5 Conclusion

Note

References

14 The epilogue

Note

References

Glossary

Chapter 1. Data-centric living: An introduction

Chapter 2. Algorithms in society: Arbitrage, bias, and culture

Chapter 3. Artificial intelligence and its effect on employment and skilling

Chapter 4. Continuing cybernetic musing: Behaviour shaping through data-driven feedback

Chapter 5. Data-driven identities

Chapter 6. Inclusive digital governance

Chapter 7. The social meaning of mobile money: Navigating digital payments, savings and credit in the Global South

Chapter 8. Sharing and use of non-personal health information: Case of the COVID-19 pandemic

Chapter 9. Evaluation of privacy policies of digital firms

Chapter 10. Incorporating privacy regulatory requirements in building software

Chapter 11. Data protection regulation: Comparing approaches in the US, EU and India

Chapter 12. Data localization and its effects on cross border trade

Chapter 13. Ethical standards in autonomous systems

 

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