Please note: The algorithm descriptions in English have been automatically translated. Errors may have been introduced in this process. For the original descriptions, go to the Dutch version of the Algorithm Register.
Neighbourhood approach
Better and well-informed decision-making to improve neighbourhood liveability interventions.
Last change on 15th of April 2025, at 17:38 (CET) | Publication Standard 1.0
- Publication category
- Other algorithms
- Impact assessment
- DPIA, IAMA
- Status
- In use
General information
Theme
- Space and Infrastructure
- Living
Begin date
2023-08
Contact information
info@assen.nl
Link to publication website
https://www.assen.nl/privacyverklaringavg-algemene-verordening-gegevensbescherming
Responsible use
Goal and impact
Better and informed decision-making to improve interventions of liveability in neighbourhoods.
Sub-goals
- To analyse more effectively and efficiently what data is available within a neighbourhood and which links are potentially (correlatively) going to have the most impact.
- With AI analysis, we make the assessment of data more person-independent.
- Transparency and traceability of the analysis.
- Gaining experience with the (im)possibilities of AI.
Considerations
The expected outcomes of the algorithm are expected to infringe little on related fundamental rights.
The potential risks of the algorithm are mitigated by embedding it in the neighbourhood approaches process.
This outweighs the expected large returns in time savings, explainability and turnaround time.
The potential risks of the algorithm are mitigated by embedding it in the neighbourhood approaches process.
This outweighs the expected large returns in time savings, explainability and turnaround time.
Human intervention
Outcomes are used in the analysis phase and tested with residents (participation) and partners.
Risk management
Stigmatisation is the biggest danger. This is combated by engaging with residents and paying close attention to it in communications.
Legal basis
General management order for conducting research.
To process the neighbourhood survey data, it has been anonymised in line with the AVG (DPIA conducted).
To process the neighbourhood survey data, it has been anonymised in line with the AVG (DPIA conducted).
Elaboration on impact assessments
A DPIA and an IAMA were carried out for this processing
Impact assessment
- Data Protection Impact Assessment (DPIA): niet gepubliceerd
- Human Rights and Algorithms Impact Assessment (IAMA): niet gepubliceerd
Operations
Data
District survey data of 2019 and 2022 from municipality of Assen
Open data government (CBS, police, RIVM, cadastre, dego, VNG realisation, tax authority, lisa, aedes)
Open data government (CBS, police, RIVM, cadastre, dego, VNG realisation, tax authority, lisa, aedes)
Technical design
Machine learning (gradient boosting model)
Explainable AI (t-shape model)
Explainable AI (t-shape model)
External provider
Clappform
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