1. SoBigData Ethics Unpacking Privacy Designing for Responsibility
Jeroen van den Hoven
Delft University of Technology
SoBigData Ethics Unpacking Privacy Designing for Responsibility

2. Central ‘SoBigEthical’ Questions
EU has set higher standards for ethics of research: both in terms of methods, and practices, consequences, but also aims
What good is SoBigData Research bringing?
Is it producing good outcomes, without producing bad outcomes?

3. Responsible Data Science Responsible Research Infrastructure

4. Dutch Consortium (25 meuro application pending)

5. Fairness
Accuracy
Confidentiality
Transparency

6. Humanitarian

7. Two vantage points Responsible Research and Innovation (RRI)
Value Sensitive Design

8. Applied to Research infrastructure
RRI: Basic Idea
Applied to Research infrastructure

9. Responsible Research and Innovation
A research infrastructure can be said to be “responsible” only if it accomodates data users, controlers and processors involved in bringing about epistemic outcomes as responsible agents, i.e. they must have been enabled
(A) to obtain – as much was possible – the relevant information on (i) the consequences of their actions and on (ii) the range of options/alternatives (e.g. data minimization) open to them and
(B) to evaluate outcomes and options effectively in terms of relevant moral values (including, but not limited to wellbeing, justice, equality, privacy, openness, autonomy, safety, security, accountability, and efficiency).
(C) to use these considerations (under A and B) as requirements for design and development of new functionality, products and services leading to moral improvement

10. Research Infra: socio-tech systems
Actor 4
Social Network
Actor 1
Actor 2
Actor 3
Actor 6
SociotechSoc
Human 1
Human 2
Human 3
Sociotechnical Network
Box:
Fill – white
Border – Light blue, background 2, darker 75% - 3px
Text in box:
Dark purple, text 2, darker 25%
Lines:
Light blue, background 2, darker 75%
3px
Technical
Network
Component 1
Component 2
Component 3
Component 4
Component 5

11. Value Sensitive Design

12. Values Built into Systems
Interfaces
Infrastructures
Algorithms
Ontologies
Code
Protocols
Integrity constraints
Architectures
Governance arrangements
Identity Management Systems
Authorization Matrix
Procedures
Regulations
Incentive structures
Auction mechanisms
Voting mechanism
Monitoring and inspection

13. Key Problem 21st Century: Value Sensitive Design
5/29/2018
Data sets
Models
Algorithms
Procedures
Protocols
Encryption
Responsibility
Privacy
Accountability
Agency
Autonomy
Security
transparency
Express
Implement
Values
Norms
Laws
Ideals
Ethics
Principles
Artefacts
Architectures
Materials
Standards
Security
Systems
Infrastructure
Justify
Audit
Key Problem 21st Century: Value Sensitive Design 13

14. High Level supra-functional requirementsl
Values hierarchy
Values
Norms
Policies
Mechanisms
Protocols
Design requirements
High Level supra-functional requirementsl

15. Example of values hierarchy
Design requirements
Norms
Values
privacy
Risk mitigation
Coarse graining
Data clustering
Pseudonymization
Accountability
Data quality
Security

16. Values 1. Privacy = data protection for moral reasons
1.1. prevention of Harm
1.2. prevention of Exploitation, manipulation, economic disadvantage
1.3. prevention of Discrimination
1.4 Respect for persons and human dignity, moral autonomy
2. Fairness
2.1 Equal Access/openness
2.2 positionality
3. Reliability
3.1. accuracy
3.2. relevance
3.3 veracity
3.4 soundness
4. Responsibility
4.1 transparency
4.2 accountability
4.3 liability
4.4. Agency and control
4.4.1 perspicuous representation of values and choices in Research Infrastructure

17. Design for X Design for privacy Design for security
Design for inclusion
Design for sustainability
Design for democracy
Design for safety
Design for transparency
Design for accountability
Design for responsibility

18. Design for Responsibility

19. Design for Responsibility
X Holding Y Responsible for Z
X Making Y Responsible for Z
X Taking Responsibility for Y
X Feeling Responsible for Y

20. Decide about criteria for
Responsibility Attribution
Responsibility Apportioning
Knowledge
Intention
Control
Non coercion
Capacity
- Fairness
- completeness

21. Determine type of responsibility
1. Causality 2. Blame 3. Accountability 4. Liability 5. Role/task
1. Task Responsibility
2. Negative Task responsibility
3. Supervising responsibility
4. Self Monitoring Responsibility
5. Meta- task Responsibility

22. Task responsibility 1. Task Responsibility
2. Negative Task responsibility
3. Supervising responsibility
4. Self Monitoring Responsibility
5. Meta- task Responsibilities
Obligation to check whether others (or future selves) can see to it that…
Obligation to see to it that others (or future selves) can see to it that …
Obligation to prevent moral dilemma’s from arising

23. Roles, Responsibilities
Legal roles:
Data controller
Data processor
Governance roles (Ethics Board, SoBigData Governance)
SoBigData Researchers (
Final Users, End Users
Software provider
Data set provider
Research infrastructure engineers
Executor
Secondary Users
Decentral governance bodies (ERB participating universities)

24. Teams

25. Unpacking Privacy

26. Privacy: Data protection for moral reasons
5/29/2018
Privacy: Data protection for moral reasons
Protecting X

27. Constrain generating Data Protection Acquiring accessing processing
Disseminating
Personal Data
Data Protection

28. Privacy: Data Protection for Moral Reasons
5/29/2018
Preventing harm
Prevention of manipulation and exploitation, e.g. fairness in markets for personal data
Prevention of Discrimination and
Contextual Integrity
4. Respect moral autonomy
Privacy: Data Protection for Moral Reasons 28

29. Design for Privacy EX ANTE 1. Informed consent
2. Right to be forgotten
3. Identity Management
4. Reciprocal Privacy
5. Coarse graining, anonymization
5. Sous-veillance, counter veillance EX POST
6. Violation/intrusion detection
7. Big data applications to detect Big data violations of privacy
EX ANTE

30. Responsibility, accountability, privacy, security………
Moral Overload
Responsibility, accountability, privacy, security………

31. Value Pluralism Dependability Usability Resilience Reliability
Privacy
Autonomy
Equity
Justice
Dignity
Wellbeing and Happiness
Safety
Security
Sustainability
Health
Friendship
Solidarity
Dependability
Usability
Resilience
Reliability
Efficiency
Flexibility
CONFLICT
DILEMMA

32. Moral Overload Prosperity AND sustainability Security AND Privacy
Efficiency AND Safety
Accountability AND Confidentiality

33. 5/29/2018
Security
Moral Overload 33

34. No Privacy, no Security (1.0)
5/29/2018
Security
No Privacy, no Security (1.0) 34

35. 5/29/2018
Security
Privacy or Security (2.0) 35

36. 5/29/2018
Privacy & Security (3.0) 36

37. Moral axiom
If you can change the world by innovation today so that you can satisfy more of your obligations tomorrow, you have a moral obligation to innovate today.

39. SobigData Ethics

40. Where can we improve upon older ethical frameworks?
Design Stance
Better recognition of the difficulties of informed consent;
Definition of Personal data
Specification of “use limitation” and “purpose specification”
Recognizing the potential expansion of identifiability;
Anonymization techniques and implementation;
Algorithmic ethics/ fairness/transparency/accountability and preventation of discrimination;
Perspicuoius representation of data, models, algorithms
Making sure we do not forget we are dealing with people and not numbers.

41. How do we make this concrete?
It is only one thing to say that we should safeguard all these principles. It is quite another thing to make sure that these principles are actually embedded into design of the research iunfrastructure. Ethical considerations need to be introduced into:
Work flows
A knowledge base of best practices
Overarching responsibility architecture
This cannot be done by ethicists, but will require a shared commitment on the part of everyone involved in SoBigData!

42. Ethics Board Helen Nissenbaum, NYU Nikolaus Forgó, Hannover
Jeroen van den Hoven, TU Delft
Dag Elgesem, Bergen, Norway
Jeroen Terstegge, DPA Netherlands, Phillips Privacy Officer