Administrative law 2

Question 1

What is Syri?

Answer 1

• System Risk Indication
• Linking and analyzing personal data to detect fraud with social security benefits
  o Legal basis in governmental decree based on Work and Income Implementation Structure Act (Wet SUWI)

Question 2

What are the perspective on Administrative law and information / data:

Answer 2

• Citizen’s perspective:
  o Access to files (in administrative proceedings)
  o Freedom of information / transparency
• Administration’s perspective:
  o Evidence-based lawmaking
  o Informed decision-making (including investigations)
• Inter-administration perspective: collaboration between public bodies
  o National level: e.g. Suwinet / Syri
  o Interstate level (between states): ‘deterritorialisation’

Question 3

Explain the data triangle:

Answer 3

• Wisdom
• Knowledge
• Information
• Data

Question 4

Explain big data, open government and open data

Answer 4

Big Data:
1. Non-public data for marketing business analysis, national security

Open Government:
2. Citizen engagement programs not based on data (e.g. petition websites)

Big Data & Open Data:
3. Large datasets from scientific research, social media, or other non-government sources.

Open government & Open data:
4. Public data from state, local federal government (e.g. budget data)

Open Data:
5. Business reporting (e.g. ESG data); other business data (e.g. consumer complaints)

Big Data & Government Data & Open Data
6. Large public government dataset (e.g. weather, GPS, Census, SEC, healthcare)

Question 5

What is big data?

Answer 5

• Huge in Volume
• High in Velocity
• Diverse in Variety

Question 6

What are the big data processes (3)?

Answer 6

• Collection
• Analysis
• Use

Question 7

What are the big data processes (5)?

Answer 7

• Data storage
• Data preparation
• Data analysis
• Interpretation
• Application

Question 8

What are the main conclusions of the WRR (Scientific Council for Government Policy) - Big Data in a Free and Secure Society (2016):

Answer 8

Main conclusions WRR (Scientific Council for Government Policy) - Big Data in a Free and Secure Society (2016):
- The present legal frameworks mainly cover the collection and sharing of data (data protection law), but offer too little protection to citizens (given the potential of Big Data).
• Purpose limitation and data minimisation vs. Big Data

• It is in the phases of data analysis and use that the biggest opportunities and risks of Big Data exist and where new rules are needed.
  • Strict enforcement of existing ban on automated decision making (ADM)
  • Sunset clause of three to five years for large Big Data projects within the government
  • Enhancement of data processing transparency

Question 9

Which laws and regulations regulate automated decision-making (ADM) (sources)?

Answer 9

• Article 22 GDPR: The data subject shall have the right not to be subject to a decision based solely on automated processing, including profiling, which produces legal effects concerning him or her or similarly significantly affects him or her.
• Article 14 GDPR: the controller shall provide the data subject with the following information necessary to ensure fair and transparent processing in respect of the data subject: […] the existence of automated decision-making, including profiling, […] and, at least in those cases, meaningful information about the logic involved, as well as the significance and the envisaged consequences of such processing for the data subject.

Question 10

What was the conclusion of the Dutch Council of State (highest administrative court) in AERIUS case (17 May 2017)?

Answer 10

Dutch Council of State (highest administrative court) in AERIUS case (17 May 2017):

• Automated decision-making (ADM): black box from citizens’ perspective
• Need for levelling playing field of citizens versus public bodies
• Requirement of timely and complete affirmative disclosure of ‘choices, assumptions and data’ used in algorithm
• Translation of principle of due care / duty to give reasons (general principles of good administration) into ‘data context’
• In the end: sufficient decision transparency?