Submit a case for review by a normative advice commission

Cases can be submitted anonymously. Read more about how we work. You can find more information below about next steps after case submission.

Case information

* required

Name algorithm
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Short description – Define the specific task of the algorithm and its the context in which it operates (max. 200 words)
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Technical dimension – Description of data collection, used statistical methodologies and used evaluation criteria

Legal framework – Applicable laws and open legal norms, e.g., GDPR, EU non-discrimination law

Ethical issues – Description of the identified ethical issue given it’s technical and legal framework
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Contact details

Terms and conditions
Submitted data will only be processed for the purpose described above, kept for the minimum necessary duration, and is securely stored in a protected environment
*

Add a case to algoprudence repository

Would you like to contribute to our algoprudence repository? Please complete the below form. Please familiarize yourself with the cases already present in the repository. You can find more information below about next steps after case submission.

Case information

* required

Name organisation
*

Normative decision taken – Define the specific task of the algorithm, its socio-technical context, statistical methodology, the relevant legal framework and what decision is taken to deal with the identified ethical issue
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Contact details
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Relevant documents

Terms and conditions
Submitted data will only be processed for the purpose described above, kept for the minimum necessary duration, and is securely stored in a protected environment
*

What are the next steps after case submission?

Your submission is reviewed by Team Algoprudence. The team assesses whether de case aligns with the mission of Algorithm Audit and the availability of resources for further investigation. Notification regarding any follow-up steps can be expected within two weeks.

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Normative advice commission provides rationales why these variables are eligible or not as a profiling selection criterion for a xgboost algorithm

Technical audit indirect discrimination

Qualitative and quantitative audit of algorithmic-driven college allowances control process. Assessment of risk distributions through Z-tests and bias test in the control process

Risk Profiling Social Welfare Re-examination

Normative advice commission provides rationales why these variables are eligible or not as a profiling selection criterion for a xgboost algorithm

Technical audit indirect discrimination

Qualitative and quantitative audit of algorithmic-driven college allowances control process. Assessment of risk distributions through Z-tests and bias test in the control process

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Building public knowledge for ethical algorithms