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Auditing is a multi-faceted concept. In the financial industry, an audit refers to an independent examination of book keeping. According to a pre-defined criteria a financial audit attempts to ensure that books of accounts are properly maintained. For AI systems, auditing is a relatively new concept and auditing criteria have not taken full shape. Due to it's context dependency, gaining case-based experience in dealing with concrete normative dilemmas in semi-automated decision-making processes is key. Since these dilemmas involve ethical considerations and trade-offs, they cannot be solved by technical audit standards only, but must involve collective deliberation by all stakeholders. Algorithm Audit's audits are therefore inclusive and deliberative in nature, which resonates with the meaning of the Latin word *audire*, from which "audit" is derived, meaning "to hear".
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Ethics washing refers to the practice where a company or organization pays lip service to ethics or ethical review, to make it seem outwardly as though it operates in a responsible way. However, the company or organization actually does not wish to implement responsible practices in a meaningful way. We do not participate in ethical reviews as branding. As an organization, we do not confer ethics certificates or labels to our partners. We clearly communicate that our advice commissions only give normative advice and may not be used as stand-in for internal control or external accountability. This is established in explicit conditions under which we work and that we discuss with our partners beforehand. A concrete measure we will regularly adopt is making the partner anonymous in our publication of the case and reports.
*[Aileen Nielsen](https://hls.harvard.edu/faculty/aileen-nielsen/), Visiting Assistant Professor, Harvard Law School, author of the book [Practical Fairness](https://www.oreilly.com/library/view/practical-fairness/9781492075721/)	
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*[Anne Meuwese](https://www.universiteitleiden.nl/medewerkers/anne-meuwese#tab-1), Professor Public Law & Governance of AI, Leiden University
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Qualitative and quantitative audit of algorithmic-driven college
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allowances control process. Assessment of risk distributions through
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Z-tests and bias test in the control process
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team:
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title: Team Algoprudence
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icon: fas fa-user-friends
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button_text: Other teams
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button_link: /about/teams/
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team_members:
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- image: /images/people/VDjwalapersad.jpeg
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name: Vardâyani Djwalapersad
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bio: |
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Project manager Algoprudence
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- image: /images/people/JParie.jpg
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name: Jurriaan Parie
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bio: |
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Director-board member
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- image: /images/people/AVoogt.jpeg
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name: Ariën Voogt
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bio: |
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Board member
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- image: /images/people/SMohammad.jpeg
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name: Samaa Mohammad-Ulenberg
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bio: |
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Board member
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quick_navigation:
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title: Content overview
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links:
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- title: Submit a case
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url: '#case-for-review'
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- title: Next steps
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url: '#next-steps'
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- title: Recent cases
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url: '#case-repository'
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---
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{{< tab_header width="6" tab1_id="case-for-review" default_tab="case-for-review" tab1_title="Submit a case for normative review" tab2_id="case-repository" tab2_title="Add a case to algoprudence repository" >}}
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Press releases of Algorithm Audit. Get in touch with the organisation by
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submitting [this](/about/contact/) contact form.
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image: /images/svg-illustrations/about.svg
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quick_navigation:
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title: Overzicht
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links:
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- title: DUO2 Addendum Preventing prejudice
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url: '#DUO_CBS'
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- title: DUO1 Preventing prejudice
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url: '#DUO'
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- title: Onderzoek Rotterdam
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url: '#Rotterdam'
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{{< accordion_item_open title="DUO control process biased towards students with a non-European migration background" id="DUO_CBS" background_color="#ffffff" date="22-05-2024" tag1="DUO" tag2="CBS" tag3="bias analysis" image="/images/partners/DUO.png" >}}
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{{< accordion_item_close >}}
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{{< accordion_item_open title="Irregularities identified in college allowances control process by Dutch public sector organization DUO" id="DUO_CBS" background_color="#ffffff" date="01-03-2024" tag1="DUO" tag2="audit report" tag3="" image="/images/partners/DUO.png" >}}
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{{< accordion_item_open title="Irregularities identified in college allowances control process by Dutch public sector organization DUO" id="DUO" background_color="#ffffff" date="01-03-2024" tag1="DUO" tag2="audit report" tag3="" image="/images/partners/DUO.png" >}}
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**THE HAGUE – In its control process into misuse of the allowances for students living away from home, Dutch public sector organization DUO selected individuals who lived close to their parent(s) significantly more often. The risk-taxation algorithm, that was used as an assisting tool for selecting students, worked as expected. However, the combination of the algorithm and manual selection resulted in a large overrepresentation of certain groups. Selected students were visited at home to inspect whether allowances were unduly granted. This is the main conclusion of research carried out by NGO Algorithm Audit on behalf of DUO. DUO’s control process was discredited in 2023 after media attention, in which was mentioned that students with a migration background were accused of misuse more often than other students.**
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id: message
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required: true
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type: textarea
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quick_navigation:
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title: Overview
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links:
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- title: Council of Europe
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url: '#COE'
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- title: Dutch Executive Agency for Education (DUO)
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url: '#DUO'
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- title: Municipality of Amsterdam
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url: '#amsterdam'
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Over the course of 2024, Algorithm Audit paired up with the municipality of Amsterdam to build public knowledge on pragmatic risk management measures for algorithms falling within and outside the AI-system defintion under the AI Act.
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From Q3-2024 up to Q1-2025, Algorithm Audit supported the Council of Europe (CoE) with updating eLearning with materials relating to the AI Act and CoE Framework Convention on AI.
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In 2023-25, Algorithm Audit has paired up with Dutch public sector organisation DUO to build algorithm validation capacity from both a qualitative and quantitative dimensions. We have been working on:
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In 2023-25, Algorithm Audit pairs up with Dutch public sector organisation DUO to build algorithm validation capacity from both a qualitative and quantitative dimensions. We have been working on:
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* A technical audit report of the college grant check proces. The first report, with findings and recommendation, [Preventing prejudice](/algoprudence/cases/aa202401_preventing-prejudice/) has been sent to the Dutch Parliament on 01-03-2024;
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* A second [audit report](/algoprudence/cases/aa202402_preventing-prejudice_addendum/), included a <ahref="https://github.com/NGO-Algorithm-Audit/DUO-CUB"target="_blank">data analysis</a> based on aggregation statistics shared by the Dutch National Office of Statistics to conduct a large-scale study on proxy characteristics in the college grant control process;
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Over the course of 2024, Algorithm Audit paired up with the municipality of Amsterdam to build public knowledge on pragmatic risk management measures for algorithms falling within and outside the AI-system defintion under the AI Act.
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