Trust, Automation Bias and Aversion: Algorithmic Decision-Making in the Context of Credit Scoring

Algorithmic decision-making (ADM) systems increasingly take on crucial roles in our technology-driven society, making decisions, for instance, concerning employment, education, finances, and public services. This article aims to identify peoples’ attitudes towards ADM systems and ensuing behaviours when dealing with ADM systems as identified in the literature and in relation to credit scoring. After briefly discussing main characteristics and types of ADM systems, we first consider trust, automation bias, automation complacency and algorithmic aversion as attitudes towards ADM systems. These factors result in various behaviours by users, operators, and managers. Second, we consider how these factors could affect attitudes towards and use of ADM systems within the context of credit scoring. Third, we describe some possible strategies to reduce aversion, bias, and complacency, and consider several ways in which trust could be increased in the context of credit scoring. Importantly, although many advantages in applying ADM systems to complex choice problems can be identified, using ADM systems should be approached with care – e.g., the models ADM systems are based on are sometimes flawed, the data they gather to support or make decisions are easily biased, and the motives for their use unreflected upon or unethical

End-user Empowerment: An Interdisciplinary Perspective

In virtue of fast spreading emerging technologies, considering end-user empowerment (or human empowerment) while developing or adapting technologies gains importance. Even though many different approaches to end-user empowerment have been proposed, it is hardly clear what end-user (human) empowerment is and how it is possible to develop end-user empowering systems . This paper offers an interdisciplinary perspective on how it can be possible to arrive at a synthesized concept of end-user empowerment, in particular regarding the development of Information and Communication Technologies (ICTs). The provided interdisciplinary perspective includes concepts from Computer Science, Information Systems, Cognitive Science, Psychology, Sociology, Science-Technology-Society, Design, System Science and Philosophy. Based on an interdisciplinary literature review, and from an enactivist, pluralist, and constructivist perspective, we argue that the individual end-users and their needs and values, as well as the environment (including socioeconomical contexts, other actors, etc.) and technologies they interact with, continuously co-create the conception of end-user empowerment. Moreover, we propose that perceiving technological development as co-creation, and considering technologies as value-bearers could provide the first steps in the development of conceptual frameworks required for the development of end-user empowering systems

Wer ist schuld, wenn Algorithmen irren? Entscheidungsautomatisierung, Organisationen und Verantwortung

Algorithmic decision support (ADS) is increasingly used in a whole array of different contexts and structures in various areas of society, influencing many people's lives. Its use raises questions, among others, about accountability, transparency and responsibility. Our article aims to give a brief overview of the central issues connected to ADS, responsibility and decision-making in organisational contexts and identify open questions and research gaps. Furthermore, we describe a set of guidelines and a complementary digital tool to assist practitioners in mapping responsibility when introducing ADS within their organisational context. -- Algorithmenunterst\"utzte Entscheidungsfindung (algorithmic decision support, ADS) kommt in verschiedenen Kontexten und Strukturen vermehrt zum Einsatz und beeinflusst in diversen gesellschaftlichen Bereichen das Leben vieler Menschen. Ihr Einsatz wirft einige Fragen auf, unter anderem zu den Themen Rechenschaft, Transparenz und Verantwortung. Im Folgenden m\"ochten wir einen \"Uberblick \"uber die wichtigsten Fragestellungen rund um ADS, Verantwortung und Entscheidungsfindung in organisationalen Kontexten geben und einige offene Fragen und Forschungsl\"ucken aufzeigen. Weiters beschreiben wir als konkrete Hilfestellung f\"ur die Praxis einen von uns entwickelten Leitfaden samt erg\"anzendem digitalem Tool, welches Anwender:innen insbesondere bei der Verortung und Zuordnung von Verantwortung bei der Nutzung von ADS in organisationalen Kontexten helfen soll.Comment: 18 pages, 2 figures, in Germa

The 2021 German Federal Election on Social Media: Analysing Electoral Risks Created by Twitter and Facebook

Safeguarding democratic elections is hard. Social media plays a vital role in the discourse around elections and during electoral campaigns. The following article provides an analysis of the ‘systemic electoral risks’ created by Twitter and Facebook and the mitigation strategies employed by the platforms. It is based on the 2020 proposal by the European Commission for the new Digital Services Act (DSA) in the context of the 2021 German federal elections. This article focuses on Twitter and Facebook and their roles during the German federal elections that took place on 26 September 2021. We analysed three systemic electoral risk categories: 1) the dissemination of illegal content, 2) negative effects on electoral rights, and 3) the influence of disinformation and developed systematic categories for this purpose. In conclusion, we discuss how to respond to these challenges as well as avenues for future research

Content governance on social networking sites: Battling disinformation and upholding values

Social media platforms such as Facebook, YouTube, and Twitter have millions of users logging in every day, using these platforms for commu­ nication, entertainment, and news consumption. These platforms adopt rules that determine how users communicate and thereby limit and shape public discourse.2 Platforms need to deal with large amounts of data generated every day. For example, as of October 2021, 4.55 billion social media users were ac­ tive on an average number of 6.7 platforms used each month per internet user.3 As a result, platforms were compelled to develop governance models and content moderation systems to deal with harmful and undesirable content, including disinformation. In this study: • ‘Content governance’ is defined as a set of processes, procedures, and systems that determine how a given platform plans, publishes, moder­ ates, and curates content. • ‘Content moderation’ is the organised practice of a social media plat­ form of pre-screening, removing, or labelling undesirable content to reduce the damage that inappropriate content can cause

Emotion and experience while listening to music

Tess Roder is inviting you to a scheduled Zoom meeting. Topic: BCEM poster session Time: May 20, 2020 03:45 PM Amsterdam, Berlin, Rome, Stockholm, Vienna Join Zoom Meeting https://us04web.zoom.us/j/76135444100?pwd=c2hHbWxyamtMaXB0OFltbS94enlQUT09 Meeting ID: 761 3544 4100 Password: Tess1

Content moderation on social networking sites: Battling disinformation and upholding values

Organisation and Governanc

The 2021 German Federal Election on Social Media: Analysing Electoral Risks Created by Twitter and Facebook

Safeguarding democratic elections is hard. Social media plays a vital role in the discourse around elections and during electoral campaigns. The following article provides an analysis of the ‘systemic electoral risks’ created by Twitter and Facebook and the mitigation strategies employed by the platforms. It is based on the 2020 proposal by the European Commission for the new Digital Services Act (DSA) in the context of the 2021 German federal elections. This article focuses on Twitter and Facebook and their roles during the German federal elections that took place on 26 September 2021. We analysed three systemic electoral risk categories: 1) the dissemination of illegal content, 2) negative effects on electoral rights, and 3) the influence of disinformation and developed systematic categories for this purpose. In conclusion, we discuss how to respond to these challenges as well as avenues for future research

The 2021 German Federal Election on Social Media: Analysing Electoral Risks Created by Twitter and Facebook

Safeguarding democratic elections is hard. Social media plays a vital role in the discourse around elections and during electoral campaigns. The following article provides an analysis of the ‘systemic electoral risks’ created by Twitter and Facebook and the mitigation strategies employed by the platforms. It is based on the 2020 proposal by the European Commission for the new Digital Services Act (DSA) in the context of the 2021 German federal elections. This article focuses on Twitter and Facebook and their roles during the German federal elections that took place on 26 September 2021. We analysed three systemic electoral risk categories: 1) the dissemination of illegal content, 2) negative effects on electoral rights, and 3) the influence of disinformation and developed systematic categories for this purpose. In conclusion, we discuss how to respond to these challenges as well as avenues for future research.Organisation & Governanc