back to old commit and removed cohort vacancy

jfparie · jfparie · commit 1734b80daa35 · 2024-04-03T21:45:43.000+02:00
diff --git a/content/english/about/vacancies.md b/content/english/about/vacancies.md
@@ -63,109 +63,3 @@ form1:
       type: checkbox
 ---
 
-{{< accordions_area_open >}}
-
-{{< accordion_item_open image="/images/logo/logo.svg" title="Responsible AI expert – AI Act standardization cohort" id="standardization" tag1="rolling applications" tag2="2-4 hours per week" tag3="voluntary" background_color="#ffffff" >}}
-
-{{< button button_text="Apply for this function" button_link="#form" >}}
-
-#### Summary
-
-Would you like to contribute to shaping AI standards
-for the common good? Become part of Algorithm Audit’s part-time voluntary cohort,
-consisting of 5 international qualitative and quantitative responsible AI
-experts. By joining, you will be registered on behalf of Algorithm Audit as a CEN-CENELEC
-JTC21 expert, granting you direct involvement in working groups devising AI
-standards at the European level. Participating in this cohort positions you to
-become an AI Act expert towards the implementation of the Act in 2026. Besides,
-it enables you to work together with cutting-edge not-for-profit international AI
-auditing experts.
-
-#### What is Algorithm Audit?
-
-Algorithm Audit is a European knowledge platform for
-AI bias testing and normative AI standards. We are a young, tech-savvy NGO working
-on ethical issues that arise in real-world algorithms. We bring together
-experts from various professional backgrounds to build bottom-up public
-knowledge how to use AI in a responsible manner (see our case repository: https://algorithmaudit.eu/algoprudence/).
-Besides, we develop, maintain and test open-source AI auditing tools. Check for
-instance our synthetic data generation and bias detection tool cohorts (https://algorithmaudit.eu/about/teams/).
-
-#### &#xA;Project activities
-
-You will follow standardization activities in one of
-the following working groups (WGs): WG2 Operational aspects (e.g., risk
-management), WG3 Engineering aspects (e.g., data and bias) or WG4
-Trustworthiness (e.g., fundamental rights). Within your chosen WG, your role
-involves staying informed about ongoing standardization activities by reviewing
-online materials and attending WG meetings. Depending on the distribution of
-cohort members over the WGs, tasks can be divided. During the first 4 weeks of
-the cohort, you will undergo together with fellow cohort members a concise online
-standardization training to familiarize yourselves with using CEN-CENELEC’s
-information system. After this, you will collaborate with Algorithm Audit’s AI
-auditing experts to formulate written contributions for ongoing standardization
-activities. Insights gained from Algorithm Audit’s bottom-up auditing work will
-serve as input for top-down AI standards currently under development. Every 4-6
-weeks, you will provide a brief summary of the WG’s recent progress to your
-fellow cohort members.
-
-#### &#xA;&#xA;What will you do as cohort team member?   
-
-* Dedicate 2-4 hours per week from Apr-15 up to Dec-31st
-  2024 on JTC21 standardization activities;
-* As an AI expert, serve as a representative for Algorithm
-  Audit within the international AI standardization community, showcasing
-  Algorithm Audit as a European knowledge platform for AI bias testing and
-  normative AI standards;
-* Translate bottom-up AI auditing experiences into meaningful contributions to procedural and technical standards for AI, for instance hypothesis testing standards (t-tests, Z-tests, chi-square-tests etc.)
-  for risk profiling algorithms, inclusion of stakeholder panels for qualitative
-  interpretation of confusion matrix-based performance/fairness metrics (FPRs, FNRs
-  etc.) and your own ideas. See also Algorithm Audit’s algoprudence case repository
-  https://algorithmaudit.eu/algoprudence/;
-* Coordinate your own work activities. Reading and writing activities can be scheduled at your convenience. Attendance at working group meetings may necessitate some planning, attendance can be coordinated with fellow cohort members;
-* Share (bi)monthly updates with the standardization cohort;
-* Become an expert in standards that will underpin the AI Act from 2026 onwards.
-
-#### Candidate profile
-
-* PhD or MSc degree in one of the following fields
-  related to responsible AI: computer science, engineering, statistics,
-  mathematics, ethics, philosophy, law, policy or social sciences with focus on digital society;
-* Proven track record and ideally active
-  participation in public discussions regarding responsible AI;
-* Understanding of academic discussions concerning AI and its intersection
-  with fundamental rights, explainability, human oversight, and/or risk management;
-* Willing to contribute 2-4h per week, besides your day-to-day
-  professional job, to build public knowledge for responsible algorithms;
-* You can assure there is no conflict of interest
-  between contributing to AI standards from a common good-perspective and your
-  professional activities. If you are employed in industry, please provide
-  further details on your motivation for participating in standardization endeavors and
-  how you plan to address any potential conflicts;
-* Available up to 31-12-2024 to contribute to participate
-  in the cohort;
-* Advantageous: Methodological expertise in hypothesis
-  testing, unsupervised machine learning (specifically clustering) and
-  statistical inference.
-
-#### Our approach to diversity, equity and inclusion
-
-We
-encourage candidates from all backgrounds to apply and join us in our mission
-to build a European knowledge platform for AI bias testing
-and normative AI standards. Algorithm Audit is committed to inclusion across race, gender, age,
-religion, identity, and experience. We foster a multidisciplinary environment
-where everyone, from any background, can do their best work. We actively seek
-to include a diverse set of voices and perspectives in all aspects of our activities,
-how we form cohorts, structure our leadership team, the advice we give and the
-technical tools we deploy. Algorithm Audit’s commitment is reflected in its
-core mission to strengthen more fair and less discriminatory deployment of AI
-in all parts of society. We build and share public knowledge about
-discriminatory bias and fostering equitable algorithms and methods for
-data-analysis.
-
-{{< form1 >}}
-
-{{< accordion_item_close >}}
-
-{{< accordions_area_close >}}
diff --git a/content/english/knowledge-platform/knowledge-base/test.md b/content/english/knowledge-platform/knowledge-base/test.md
diff --git a/content/nederlands/about/vacancies.md b/content/nederlands/about/vacancies.md
@@ -63,109 +63,3 @@ form1:
       type: checkbox
 ---
 
-{{< accordions_area_open >}}
-
-{{< accordion_item_open image="/images/logo/logo.svg" title="Responsible AI expert – AI Act standardization cohort" id="standardization" tag1="rolling applications" tag2="2-4 hours per week" tag3="voluntary" background_color="#ffffff" >}}
-
-{{< button button_text="Apply for this function" button_link="#form" >}}
-
-#### Summary
-
-Would you like to contribute to shaping AI standards
-for the common good? Become part of Algorithm Audit’s part-time voluntary cohort,
-consisting of 5 international qualitative and quantitative responsible AI
-experts. By joining, you will be registered on behalf of Algorithm Audit as a CEN-CENELEC
-JTC21 expert, granting you direct involvement in working groups devising AI
-standards at the European level. Participating in this cohort positions you to
-become an AI Act expert towards the implementation of the Act in 2026. Besides,
-it enables you to work together with cutting-edge not-for-profit international AI
-auditing experts.
-
-#### What is Algorithm Audit?
-
-Algorithm Audit is a European knowledge platform for
-AI bias testing and normative AI standards. We are a young, tech-savvy NGO working
-on ethical issues that arise in real-world algorithms. We bring together
-experts from various professional backgrounds to build bottom-up public
-knowledge how to use AI in a responsible manner (see our case repository: https://algorithmaudit.eu/algoprudence/).
-Besides, we develop, maintain and test open-source AI auditing tools. Check for
-instance our synthetic data generation and bias detection tool cohorts (https://algorithmaudit.eu/about/teams/).
-
-#### &#xA;Project activities
-
-You will follow standardization activities in one of
-the following working groups (WGs): WG2 Operational aspects (e.g., risk
-management), WG3 Engineering aspects (e.g., data and bias) or WG4
-Trustworthiness (e.g., fundamental rights). Within your chosen WG, your role
-involves staying informed about ongoing standardization activities by reviewing
-online materials and attending WG meetings. Depending on the distribution of
-cohort members over the WGs, tasks can be divided. During the first 4 weeks of
-the cohort, you will undergo together with fellow cohort members a concise online
-standardization training to familiarize yourselves with using CEN-CENELEC’s
-information system. After this, you will collaborate with Algorithm Audit’s AI
-auditing experts to formulate written contributions for ongoing standardization
-activities. Insights gained from Algorithm Audit’s bottom-up auditing work will
-serve as input for top-down AI standards currently under development. Every 4-6
-weeks, you will provide a brief summary of the WG’s recent progress to your
-fellow cohort members.
-
-#### &#xA;&#xA;What will you do as cohort team member?   
-
-* Dedicate 2-4 hours per week from Apr-15 up to Dec-31st
-  2024 on JTC21 standardization activities;
-* As an AI expert, serve as a representative for Algorithm
-  Audit within the international AI standardization community, showcasing
-  Algorithm Audit as a European knowledge platform for AI bias testing and
-  normative AI standards;
-* Translate bottom-up AI auditing experiences into meaningful contributions to procedural and technical standards for AI, for instance hypothesis testing standards (t-tests, Z-tests, chi-square-tests etc.)
-  for risk profiling algorithms, inclusion of stakeholder panels for qualitative
-  interpretation of confusion matrix-based performance/fairness metrics (FPRs, FNRs
-  etc.) and your own ideas. See also Algorithm Audit’s algoprudence case repository
-  https://algorithmaudit.eu/algoprudence/;
-* Coordinate your own work activities. Reading and writing activities can be scheduled at your convenience. Attendance at working group meetings may necessitate some planning, attendance can be coordinated with fellow cohort members;
-* Share (bi)monthly updates with the standardization cohort;
-* Become an expert in standards that will underpin the AI Act from 2026 onwards.
-
-#### Candidate profile
-
-* PhD or MSc degree in one of the following fields
-  related to responsible AI: computer science, engineering, statistics,
-  mathematics, ethics, philosophy, law, policy or social sciences with focus on digital society;
-* Proven track record and ideally active
-  participation in public discussions regarding responsible AI;
-* Understanding of academic discussions concerning AI and its intersection
-  with fundamental rights, explainability, human oversight, and/or risk management;
-* Willing to contribute 2-4h per week, besides your day-to-day
-  professional job, to build public knowledge for responsible algorithms;
-* You can assure there is no conflict of interest
-  between contributing to AI standards from a common good-perspective and your
-  professional activities. If you are employed in industry, please provide
-  further details on your motivation for participating in standardization endeavors and
-  how you plan to address any potential conflicts;
-* Available up to 31-12-2024 to contribute to participate
-  in the cohort;
-* Advantageous: Methodological expertise in hypothesis
-  testing, unsupervised machine learning (specifically clustering) and
-  statistical inference.
-
-#### Our approach to diversity, equity and inclusion
-
-We
-encourage candidates from all backgrounds to apply and join us in our mission
-to build a European knowledge platform for AI bias testing
-and normative AI standards. Algorithm Audit is committed to inclusion across race, gender, age,
-religion, identity, and experience. We foster a multidisciplinary environment
-where everyone, from any background, can do their best work. We actively seek
-to include a diverse set of voices and perspectives in all aspects of our activities,
-how we form cohorts, structure our leadership team, the advice we give and the
-technical tools we deploy. Algorithm Audit’s commitment is reflected in its
-core mission to strengthen more fair and less discriminatory deployment of AI
-in all parts of society. We build and share public knowledge about
-discriminatory bias and fostering equitable algorithms and methods for
-data-analysis.
-
-{{< form1 >}}
-
-{{< accordion_item_close >}}
-
-{{< accordions_area_close >}}
