Access to Innovation
Access to Capital
Access to Talent
Access to Market
Access to Knowledge
Date Trend snippet:
30 May 2021
Relevance date:
2020
Type of Treath or Oppertunity
Domain of application
Source of threat
Victim
Trends in Security
Trends in Security Information
The HSD Trendmonitor is designed to provide access to relevant content on various subjects in the safety and security domain, to identify relevant developments and to connect knowledge and organisations. The safety and security domain encompasses a vast number of subjects. Four relevant taxonomies (type of threat or opportunity, victim, source of threat and domain of application) have been constructed in order to visualize all of these subjects. The taxonomies and related category descriptions have been carefully composed according to other taxonomies, European and international standards and our own expertise.
In order to identify safety and security related trends, relevant reports and HSD news articles are continuously scanned, analysed and classified by hand according to the four taxonomies. This results in a wide array of observations, which we call ‘Trend Snippets’. Multiple Trend Snippets combined can provide insights into safety and security trends. The size of the circles shows the relative weight of the topic, the filters can be used to further select the most relevant content for you. If you have an addition, question or remark, drop us a line at info@securitydelta.nl.
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The exception of education as a protected grounds in EU law may lead to algorithmic discrimination
The exception of education as a protected grounds in EU law may lead to algorithmic discrimination as in the field of eduction algorithms are also increasingly used to assist in decision making. Concerns have been expressed about the potential risks of discrimination (the use of income and residency data about candidates) and the lack of transparency in the decision-making process.
More source info
In the field of education, too, algorithms are increasingly used to assist decision making, as the examples discussed in Chapter 3 may illustrate. For example, France has invested in an algorithm to support decision making in relation to the allocation of places in higher education institutions to incoming students (Parcoursup). Concerns were expressed by candidates regarding potential risks of discrimination and the lack of transparency in the decision-making process. These concerns regarding the use of the Parcoursup algorithm related to the consequences of the use of income and residency data about candidates in the allocation decisions.205 The generalisation of such algorithmically assisted recruitment processes in the field of education could lead to algorithmic discrimination if not kept in check. However, at present, only the grounds of race and ethnic origin are protected against discrimination in education in the EU. Education is indeed an exception to the material scope of EU gender equality law. This further gap could prove problematic from the perspective of redress in Member States that have implemented that exception.
