Access to Innovation
Access to Capital
Access to Talent
Access to Market
Access to Knowledge
Date Trend snippet:
29 May 2021
Relevance date:
2020
Type of Treath or Oppertunity
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.
visible on larger screens only
Please expand your browser window.
Or enjoy this interactive application on your desktop or laptop.
The provisions of data protection law and non-discrimination law do not neatly overlap, posing challenges and questions
The list of categories of data the processing of which could give risk to discrimination does not neatly fit with the list of protected grounds under EU gender equality and non discrimination law. Issues of equality or discrimination are also absent from the EU General Data Protection Regulation (GDPR).
More source info
1.5.2 Interactions between non-discrimination law and data protection Scholarly discussions have drawn attention to the role of data protection law and legal obligations related to privacy in the prevention of algorithmic discrimination. The rationale is that certain categories of data – for instance race, gender, sexual orientation, etc. – are particularly sensitive because they can easily lead to unlawful discrimination if processed without particular precautions. This is reflected in the EU’s General Data Protection Regulation (GDPR), which identifies ‘special categories of personal data’ or ‘sensitive data’.153 The Regulation recognises that ‘[p]ersonal data which are, by their nature, particularly sensitive in relation to fundamental rights and freedoms merit specific protection as the context of their processing could create significant risks to the fundamental rights and freedoms’.154 In particular, Recital 71 of the GDPR indicates that ‘[i]n order to ensure fair and transparent processing in respect of the data subject […] the [data] controller should [...] prevent, inter alia, discriminatory effects on natural persons on the basis of racial or ethnic origin, political opinion, religion or beliefs, trade union membership, genetic or health status or sexual orientation, or processing that results in measures having such an effect’. Here the interaction between data protection law and non-discrimination law is evident. Nevertheless, this interaction poses a number of questions as the provisions do not neatly overlap. The list of categories of data the processing of which could give risk to discrimination does not neatly fit with the list of protected grounds under EU gender equality and non-discrimination law. Importantly, the issue of gender equality or sex discrimination is altogether absent from the GDPR and neither gender nor sex are mentioned as sensitive categories of personal data. Racial or ethnic origin, religion or belief and sexual orientation are explicitly mentioned both in relation to discrimination in Recital 71 and in relation to the prohibition of processing such data, but the recital does not refer to ‘sex’ or grounds such as ‘age’ and ‘disability’. Similarly, Article 9(1) GDPR prohibits the ‘processing of personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, or trade union membership, and the processing of genetic data, biometric data for the purpose of uniquely identifying a natural person, data concerning health or data concerning a natural person’s sex life or sexual orientation’.155 While the list is much broader than Article 19 TFEU on the prohibition of discrimination, it does not explicitly mention ‘sex’, ‘disability’ and ‘age’ either. It might be inferred that ‘disability’ is understood to be included in the terms ‘health status’ or ‘data concerning health’ but ‘age’ and ‘sex’, as protected grounds, are more difficult to read in these two provisions of the GDPR. The absence of an outright prohibition on processing such data categories could be justified by a variety of reasons pertaining to the possibilities for legitimate and nondiscriminatory use of this data (although Article 9(2), 9(3) and 9(4) provides an explicit list of derogations concerning the legitimate use of such data), yet the absence of any mention of ‘gender equality’, ‘age discrimination’ and ‘disability discrimination’ in Recital 71 concerning discriminatory risks is more difficult to understand.
