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Scoring is not a new phenomena: we can learn from experience how to deal with scoring

Scoring is not a new phenomena: we can learn from experience how to deal with scoring Super-Scoring? Data-driven societal technologies in China and Western-style democracies as a new challenge for education

von: Gert G. Wagner (Max Planck Institute for Human Development, MPIB, Berlin)

Scores are numerical ratings used to predict or steer people’s behavior. These numerical ratings are usually calculated via algorithmic processes based on a broad range of data (see, e. g., AlgorithmWatch 2019). Wagner gives a brief historical review on score systems in Western (European) societies and depicts technological progress in Western scoring mechanisms.

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The various forms of scoring have a long tradition and there is no doubt scoring existed in the analogue era. However, it is undeniable that the implementation of scoring has changed dramatically following the technological developments of the digital age. This year, for example, France started allocating its university places using a scoring algorithm called Parcoursup, which evaluates whether the admission criteria have been met and takes into account the place of residence and the preferences of the applicant (Joeres 2018). In online retail, a consumer’s creditworthiness can be calculated automatically in just a matter of seconds so that appropriate payment options can then be offered. In the motor insurance sector, telematic tariffs now hold sway – continuously evaluating driving behavior and adjusting insurance premiums based on the resulting score.

Furthermore, algorithmic scoring is increasingly being used in many new areas and now evaluates consumers and consumer groups in the most diverse ways – with highly varied results (Dixon & Gellmann 2014, AlgorithmWatch 2019). There are scores that predict a household’s purchasing power or its willingness to donate to charity (Equifax 2018; Blackbaud 2014), scores showing whether customers will migrate to other companies (Versium Analytics Inc. 2018), scores that aim to detect pregnancies (Duhig 2012), and scores that measure energy consumption behavior (Trove 2018). Dating services are also based on scores quantifying how well personal profiles match (Carr 2016).

A culture of evaluation and quantification is emerging (Mau 2017). From ‘likes’ on Facebook to the number of Twitter followers or stars on Airbnb – we are long past the point where only companies use algorithms to assess consumers and assign them numerical values. Scoring has truly become part of our daily lives.

The examples given above help to understand how scoring of people can work and under what circumstances scoring is accepted.

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  • Produktion: 11.10.2019

  • Spieldauer: 21 Min.

  • hrsg. von: Bundeszentrale für politische Bildung/bpb

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Dieser Text und Medieninhalt sind unter der Creative Commons Lizenz "CC BY-NC-ND 4.0 - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International" veröffentlicht. Autor/-in: MPIB Gert G. Wagner (Max Planck Institute for Human Development für bpb.de

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