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.

DC Asbestos demolition notifications

Supporting AI tool for assessing asbestos demolition notifications

Last change on 23rd of April 2026, at 14:50 (CET) | Publication Standard 1.0
Publication category
Other algorithms
Impact assessment
Field not filled in.
Status
In use

General information

Theme

Nature and Environment

Begin date

2026-04

Contact information

info@dcmr.nl

Responsible use

Goal and impact

Supporting AI tool for assessing asbestos demolition notifications. Is the application complete and does it contain all legally required data? The tool uses an LLM and the assessment framework from the Building Works Decree on the living environment. The final judgement on whether a notification is Approved or Rejected is up to the handler.

Considerations

The tool saves time in assessing discharge notifications and makes the work for the handler more enjoyable and easier. A drawback can be overconfidence in the result. Therefore, the tool is only available to trained users with sufficient content to assess the result.

Human intervention

The final judgement on whether a report is approved or rejected is up to a human being (the handler).

Risk management

Risks are:

* Interpretability

* Legal correctness


Mitigating measures:

The tool becomes available only to trained users who are sufficiently versed in the content to be able to assess the result.

Legal basis

Environment Act, Built Environment Decree (Bbl)

Links to legal bases

  • Environment Act: https://wetten.overheid.nl/jci1.3:c:BWBR0037885&z=2024-01-01&g=2024-01-01
  • Building Works Environment Decree (Bbl),: https://wetten.overheid.nl/BWBR0041297/2026-03-27

Operations

Data

The algorithm assesses asbestos demolition notifications for the mandatory data (submission requirements) and tests this against applicable laws and regulations. The algorithm uses the assessment framework and is trained with its own datasets of previously human-assessed notifications.

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