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AI anonymization of personal data in public infrastructure asset management

Reference number
Coordinator Stockholms kommun - Stockholms stad Trafikkontoret
Funding from Vinnova SEK 600 000
Project duration November 2022 - February 2024
Status Completed
Venture Learning and meeting places
Call Start your AI journey: For organizational learning and practical use of artificial intelligence in municipalities and civil society spring 2022

Important results from the project

The purpose of the project was to automatically anonymize personal data in images received by the Transport Department in order to meet regulatory eligibility requirements in current GDPR legislation. This objective has been achieved by the Transport Department having procured and installed an AI service and verified that it meets to all eligibility requirements set by the Transport Department based on automation and GDPR.

Expected long term effects

As mentioned above, the result is that the images are 100% anonymized, which was the Transport Department´s requirement level. It also means that the business can shorten the response time and work more efficiently as no manual handling will be needed to anonymize incoming images. The expected effect and outcome thus correspond to the high eligibility requirements that have been set. The project will bring about positive synergy effects for other businesses and their IT systems, within the Transport Department.

Approach and implementation

Three AI service providers were compared, who had specialized in this type of image processing. Interviews were conducted. All three were judged to be able to deliver a stable service. The choice fell on the supplier who was judged to be the most technologically innovative and which had a good reputation among its reference customers. Licenses, hardware and software were procured and then installation, commissioning, integration with operational systems and tests were carried out. The analysis is that the technology is mature but it is not specific to this particular solution.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 7 May 2024

Reference number 2022-02653