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Date Trend snippet:
04 June 2021
Relevance date:
2020
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- Trend snippet: National experts report that algorithms can cause direct and indirect discrimination
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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.
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National experts report that algorithms can cause direct and indirect discrimination
National experts report that algorithms can easily cause direct and indirect discrimination. Several examples are found in France, Germany, Italy, and the Netherlands with regards to sexism in the use of algorithms by media, targeted discounts for specific groups, stereotyped marketing, profiling through personal data, and the way in which a system led to heightened supervision in certain 'problem neighborhoods'.
More source info
3.2.2 Discriminatory effects Mostly as a result of in-built biases and stereotypes, national experts report that algorithms can easily cause direct and indirect discrimination. More specifically, algorithms can sometimes lead to sexist decisions, as was observed by the High Council on Equality of France in its report on sexism in the use of algorithms by the media and on the internet.357 In addition, it was mentioned that in France personalised price-setting for goods and services could cause discrimination by raising prices for gendered products for menstruation.358 Likewise, in Germany, the example has been given of the Berlin Public Transport Company offering targeted discounts to women on International Women’s Day, using facial recognition.359 This particular use relied on a binary distinction between men and women and was strongly based on stereotypes. It has been reported that personalised behavioural advertising in the real estate market in Italy can have the effect of discriminating according to ethnicity and social class, thus contributing to creating ‘new ghettos’ on the one hand, and luxury districts on the other.360 Another problem in Italy is that profiling through personal data can lead to the determination of credit ratings or insurance premiums according to lifestyle or driving, or the inclusion in certain ‘social clusters’ based on ethnic or geographical origin.361 Finally, the fraud detection system, SyRI, in the Netherlands might have a discriminatory and stigmatising effect to the extent that the system led to heightened supervision in certain ‘problem neighbourhoods’.362
