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Die voranschreitende Digitalisierung aller Lebensbereiche gewinnt zunehmend an Bedeutung, auch die Soziale Arbeit ist davon betroffen. Wichtige Grundlage für alle Bereiche der Digitalisierung stellen Algorithmen dar. Lernende Algorithmen können in großen Datenmengen Muster erkennen und auf deren Grundlage Entscheidungsregeln definieren. Dies möchte sich auch das Arbeitsmarktservice Österreich zu Nutze machen, um die Chancen zur Arbeitsaufnahme von Arbeitsuchenden durch ein algorithmisches System prognostizieren zu lassen und auf dessen Basis deren Zugang zu Ressourcen zu bestimmen. Ziel dieser Arbeit ist es zu untersuchen welche Diskriminierungen in diesem System eingebettet sind oder dadurch verursacht werden. Es zeigt sich, dass in der aktuellen Umsetzung bereits marginalisierte Personen Gefahr laufen weitere Benachteiligung zu erfahren und bestehende strukturelle Ungleichheiten verstärkt werden. The increasing digitalization of all areas of life is steadily gaining more significance, which also affects the profession of social work. An important basis for all areas of digitalization are algorithms. Learning algorithms can identify patterns in big amounts of data and derive decision making rules from them. The Austrian employment market service intends to make use of these capabilities to predict chances of job seekers for finding employment and subsequently allocate access to resources based on those predictions. This paper’s aim is to identify discriminatory aspects of this approach. Results show that in its current implementation already marginalized people are at risk of further discrimination while existing structural inequalities get reinforced.

Medical ultrasound imaging is a well-known technique to gather live views of the interior of the human body. It is totally safe, it provides high spatial and temporal resolution, and it is nowadays available at any hospital. This suggests that it could be used as a human-computer interface. In this paper, we use ultrasound images of the human forearm to predict the finger positions, including thumb adduction and thumb rotation. Our experimental results show that there is a clear linear relationship between the features we extract from the images, and finger positions, expressed as angles at the metacarpo-phalangeal joints. The method is uniformly valid for all subjects considered. The unavoidable movements of the ultrasound probe with respect to the skin and of the skin with respect to the inner musculoskeletal structure are compensated for using the optical flow. Typical applications of this system range from teleoperated fine manipulation to finger stiffness estimation to ergonomy. If successfully applied to transradial amputees, it could be also used to reconstruct the imaginary limb, paving the way to, e.g., fine control of hand prostheses, treatment of neuropathic/phantom limb pain and visualization of the imaginary limb as a tool for the neuroscientist.