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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.

Woo chatbot

Municipality of Coevorden

Users can ask questions in a chatbot, about published Woo requests from Coevorden municipality. The chatbot bases answers and summaries only on documents published by the municipality.

Last change on 20th of November 2024, at 10:50 (CET) | Publication Standard 1.0
Publication category
Other algorithms
Impact assessment
Field not filled in.
Status
In use

General information

Theme

Organisation and business operations

Begin date

11-2023

Contact information

privacy@coevorden.nl

Link to publication website

https://www.coevorden.nl

Link to source registration

https://www.coevorden.nl/publicaties-wet-open-overheid

Responsible use

Goal and impact

The aim is to gain experience in using AI and ChatGPT in a low-threshold and responsible way. This is initially launched as a pilot within the municipality. By May 2024, the pilot will be completed and the chatbot will be used indefinitely on the municipal website.

Considerations

The published documents are anonymised documents intended for public disclosure. By using these documents to use CustomGPT, the risk is very low.

Human intervention

The answers given in the chatbot are checked weekly by an employee of the municipality.

Risk management

CustomGPT is used. CustomGPT indexes the data made available by the municipality of Coevorden. The published documents are anonymised documents intended for public access. By using these documents to use CustomGPT, the risk is very low

Legal basis

Woo

Operations

Data

Field not filled in.

Technical design

The user asks questions to the Chatbot (CustomGPT). These queries are presented to OpenAI via CustomGPT, via the OpenAI Public ChatGPT Instance. This means that questions from users reach OpenAI and CustomGPT. OpenAI has committed not to use data passed as context for training its models, which has improved the privacy of the queries asked.

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