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.
Summarising legal objection opinions
- Publication category
- High-Risk AI-system
- Impact assessment
- DPIA
- Status
- In development
General information
Theme
Begin date
Contact information
Responsible use
Goal and impact
Summaries of existing objection opinions are created. These summaries can be used to enrich the Case Library. This can be done by displaying the core of the case first on the homepage. The Case Library is the internal database for the lawyers of the Legal Bureau (JB). The database contains objection opinions and supports the lawyers in handling new objections.
The summary contains the essence of the objection advice. With its help, lawyers can more quickly assess whether the objection advice matches the information they are looking for. The problem this solves is the long search for the right objection advice, saving time.
Considerations
This algorithm ultimately allows lawyers to consult objection opinions faster. As a result, turnaround times are shorter and review more efficient.
Human intervention
The results can be viewed internally in the objection advice database (the Case Library). Anyone searching for objection opinions will see a summary of the full opinion. The database has a feedback function to report any errors in a summary, which are then adjusted.
Risk management
Data is only viewable in a secure environment. Lawyers only use it as a search function. There is, as indicated, a feedback function to correct any errors in the data. In addition, it will be mentioned that the summary was created with generative AI.
The results of summaries will be randomly checked to avoid any incorrect output from the language model (based on the algorithm). This is done in the process of fine-tuning and will be avoided as much as possible from prompt-engineering techniques.
There are no risks to vulnerable groups, exclusion and profiling
Elaboration on impact assessments
IAMA was not implemented, as the Municipality of Amsterdam implemented the ethics leaflet.
Impact assessment
Operations
Data
Unstructured textual data of objection opinions.
Technical design
The algorithm is yet to be developed. In outline, data of objection opinions will be retrieved from the dataset. Based on the guidelines we provided, the language model will create a summary using the algorithm.
OpenAI's generative AI model, gpt-3.5-turbo or gpt-4, will be used via Azure to summarise input texts according to yet-to-be-determined instruction-prompt techniques (e.g. few-shot learning). This model can process textual input and create new texts in natural language according to the instruction provided by the user.
External provider
Link to code base
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