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.
aIBobjection
- Publication category
- Other algorithms
- Impact assessment
- Field not filled in.
- Status
- In use
General information
Theme
Begin date
Contact information
Link to publication website
Link to source registration
Responsible use
Goal and impact
The aim is to process objection letters efficiently and accurately. Optionally by using a large language model to automatically parse and categorise the letters, allowing them to be entered quickly and correctly. Improving efficiency and accuracy in the processing of objection letters, enabling faster responses to submitted objections. This has a positive impact on customer satisfaction and operational efficiency of the relevant government agency or organisation.
Considerations
Without these algorithms, it is not possible to process objections efficiently and uniformly for citizens and businesses.
Optional use of a large language model is essential to process the large volume of objection notices cost efficiently and accurately, and to ensure consistent and accurate categorisation.
Human intervention
Municipal officials manually process the input into the system to produce a response to the objection.
Risk management
Potential inaccuracies in automatic processing and categorisation to be mitigated by human control and continuous model improvement.
Legal basis
AWR, WOZ Act, AwB, Municipalities Act, Administrative Law Litigation Decree
Links to legal bases
- AWR: https://wetten.overheid.nl/BWBR0002320/2025-01-01/0
- Wet WOZ : https://wetten.overheid.nl/BWBR0007119/2025-01-01/0
- Awb: https://wetten.overheid.nl/BWBR0005537/2025-03-08/0
- Gemeentewet: https://wetten.overheid.nl/BWBR0005416/2025-02-12/0
- Besluit proceskosten bestuursrecht: https://wetten.overheid.nl/BWBR0006358/2025-01-01/0
Operations
Data
All information contained in an objection will be processed by the algorithm, it may include personal data and special personal data. The software integrates with existing tax system and databases to automatically retrieve and enter relevant data.
Technical design
The system optionally uses a large language model to automatically parse and categorise the content of grievances. The large language model analyses the text, identifies the main grievances and enters them into the appropriate categories in the system. This process also includes automatic input of relevant data into the administration system, minimising manual input.
External provider
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