{"id":9357,"date":"2023-08-30T07:58:29","date_gmt":"2023-08-30T05:58:29","guid":{"rendered":"https:\/\/www.towfigh.net\/en\/?p=9357"},"modified":"2024-06-16T13:27:35","modified_gmt":"2024-06-16T11:27:35","slug":"expert-opinion-the-general-equal-treatment-act-and-the-protection-against-discrimination-by-algorithmic-decision-systems","status":"publish","type":"post","link":"https:\/\/www.towfigh.net\/en\/research\/expert-opinion-the-general-equal-treatment-act-and-the-protection-against-discrimination-by-algorithmic-decision-systems.html","title":{"rendered":"Expert Opinion \u00bbThe General Equal Treatment Act and the Protection against Discrimination by Algorithmic Decision Systems\u00ab"},"content":{"rendered":"

Legal Opinion on behalf of the German Federal Anti-Discrimination Agency<\/a><\/p>\n

Presented by<\/strong>
\nProf. Dr. iur. Indra Spiecker gen. D\u00f6hmann, LL.M. (Georgetown Univ.)<\/em><\/a>
\nProf. Dr. iur. Emanuel V. Towfigh<\/em><\/p>\n

Download at ADS<\/a>\u00a0\u2022 Local File (0,8 MB)<\/a><\/div>\n

Summary of the Results: <\/strong><\/p>\n

The use of ADM systems poses challenges to anti-discrimination law, above all the General Equal Treatment Act (AGG), which it is only able to meet to a limited extent in its current form.<\/p>\n

The main task of these systems is to use statistical methods to identify a large number of correlations in order to establish relationships between variables. Despite their undisputed discriminatory potential, ADM systems are associated with the notion of being able to make objective and neutral decisions that are uninfluenced by human bias, as well as more efficient and better decisions, not least because human error, bias and cognitive limitations could be eliminated or at least reduced (section 1 of the report).<\/p>\n

The use of such systems covers almost all areas of private and public life: pricing, access to and participation in public and private services, marketing, contract terms, diagnostic and therapeutic decisions, or allocation decisions when resources are scarce.<\/p>\n

The way ADM systems function enables, among other things, probability statements to be made about people. Through the attribution of group characteristics, large numbers of automated (selection) decisions are made, or contracts are optimized and made more efficient with the help of mass individualization. From the point of view of anti-discrimination law, it is precisely this group attribution that is problematic.<\/p>\n

Discrimination by statistics is the result of an attribution of characteristics obtained by statistical means, based on (actual or assumed) average values of a group. The reference to these average group characteristics is supposed to help overcome uncertainties about the individual characteristics of a single person. The social mechanism underlying such an assessment is not of interest, a causality is not claimed or proven. Thus, (historical) structural inequalities are perpetuated and new ones are created.<\/p>\n

The quality of the decision of an ADM system is essentially dependent on the quantity, quality, modeling and evaluation of the data used. As a result, the discrimination potential of ADM systems may already be inherent in the system itself. In addition, intransparency is inherent in the way ADM systems operate. Determining responsibility for discriminatory elements in ADM systems is problematic because of the diversity of those involved in their programming, further development, use, and further use, for example, in network structures and individually varied standard algorithms. In fact, those potentially responsible can often exculpate themselves. The technological progress of digital evaluation methods and technologies places virtually no technical limits on the sharing, further use and merging of large amounts of data, thus making discriminatory data sets uncontrollable in their dissemination and use. It cannot be assumed that discrimination can be identified on a case-by-case basis.<\/p>\n

The greatest challenge to legally effective protection against discrimination through ADM systems is the deficits of the AGG in enforcing the law. These fundamental deficits are well known and are not initially a problem specific to discrimination through ADM systems. However, due to the particularly pronounced power and information asymmetry, these effects are amplified: Among other things, the frequently encountered black-box character of ADM systems and the inability to infer from the decisions the use of such systems and their functionalities make it practically impossible for those affected to track down the causes of discrimination due to a lack of resources (section 2 of the report).<\/p>\n

It lacks:<\/p>\n