The public perceptions of algorithmic decision-making systems: Results from a large-scale survey

Aysolmaz, Banu; Müller, Rudolf; Meacham, Darian

doi:10.1016/j.tele.2023.101954

“…The perceived transparency of systems impacts trust, with higher transparency entailing more trust (Aysolmaz et al 2023). As has been shown in TA studies, trust-building communication cannot only consist of conveying technical aspects such as reliability (Weydner-Volkmann 2021).…”

Section: Implications Of Low Trustmentioning

confidence: 98%

AI for decision support: What are possible futures, social impacts, regulatory options, ethical conundrums and agency constellations?

Schneider,

Weber

2024

TATuP

0

View full text Add to dashboard Cite

Although artificial intelligence (AI) and automated decision-making systems have been around for some time, they have only recently gained in importance as they are now actually being used and are no longer just the subject of research. AI to support decision-making is thus affecting ever larger parts of society, creating technical, but above all ethical, legal, and societal challenges, as decisions can now be made by machines that were previously the responsibility of humans. This introduction provides an overview of attempts to regulate AI and addresses key challenges that arise when integrating AI systems into human decision-making. The Special topic brings together research articles that present societal challenges, ethical issues, stakeholders, and possible futures of AI use for decision support in healthcare, the legal system, and border control.

show abstract

“…Several surveys have been conduced with transparency in mind. Although the causal presumptions in these survey studies are often ambiguous with little uniformity across studies, transparency has been observed to improve people's perceptions on the privacy and fairness of algorithmic decision-making in general (Aysolmaza, et al, 2023). Transparency of recommender systems also affects user satisfaction (Gedikli, , et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Mysterious and manipulative black boxes: A qualitative analysis of perceptions on recommender systems

Ruohonen

2024

FM

0

View full text Add to dashboard Cite

Recommender systems are used to provide relevant suggestions on various matters. Although these systems are a classical research topic, knowledge is still limited regarding the public opinion about these systems. Public opinion is also important because the systems are known to cause various problems. To this end, this paper presents a qualitative analysis of the perceptions of ordinary citizens, civil society groups, businesses, and others on recommender systems in Europe. The dataset examined is based on the answers submitted to a consultation about the Digital Services Act (DSA) recently enacted in the European Union (EU). Therefore, not only does the paper contribute to the pressing question about regulating new technologies and online platforms, but it also reveals insights about the policy-making of the DSA. According to the qualitative results, Europeans have generally negative opinions about recommender systems and the quality of their recommendations. The systems are widely seen to violate privacy and other fundamental rights. According to many Europeans, these also cause various societal problems, including even threats to democracy. Furthermore, existing regulations in the EU are commonly seen to have failed due to a lack of proper enforcement. Numerous suggestions were made by the respondents to the consultation for improving the situation, but only a few of these ended up to the DSA.

show abstract

“…Several surveys have been conduced with transparency in mind. Although the causal presumptions in these survey studies are often ambiguous with little uniformity across studies, transparency has been observed to improve people's perceptions on the privacy and fairness of algorithmic decision-making in general (Aysolmaza, Müller, & Meacham, 2023). Transparency of recommender systems also impacts user satisfaction (Gedikli, Jannach, & Ge, 2014).…”

Section: Introductionmentioning

confidence: 99%

Mysterious and Manipulative Black Boxes: A Qualitative Analysis of Perceptions on Recommender Systems

Ruohonen¹

2023

Preprint

0

View full text Add to dashboard Cite

Recommender systems are used to provide relevant suggestions on various matters. Although these systems are a classical research topic, knowledge is still limited regarding the public opinion about these systems. Public opinion is also important because the systems are known to cause various problems. To this end, this paper presents a qualitative analysis of the perceptions of ordinary citizens, civil society groups, businesses, and others on recommender systems in Europe. The dataset examined is based on the answers submitted to a consultation about the Digital Services Act (DSA) recently enacted in the European Union (EU). Therefore, not only does the paper contribute to the pressing question about regulating new technologies and online platforms, but it also reveals insights about the policy-making of the DSA. According to the qualitative results, Europeans have generally negative opinions about recommender systems and the quality of their recommendations. The systems are widely seen to violate privacy and other fundamental rights. According to many Europeans, these also cause various societal problems, including even threats to democracy. Furthermore, existing regulations in the EU are commonly seen to have failed due to a lack of proper enforcement. Numerous suggestions were made by the respondents to the consultation for improving the situation, but only a few of these ended up to the DSA.

show abstract

The public perceptions of algorithmic decision-making systems: Results from a large-scale survey

Cited by 12 publications

References 92 publications

AI for decision support: What are possible futures, social impacts, regulatory options, ethical conundrums and agency constellations?

AI for decision support: What are possible futures, social impacts, regulatory options, ethical conundrums and agency constellations?

Mysterious and manipulative black boxes: A qualitative analysis of perceptions on recommender systems

Mysterious and Manipulative Black Boxes: A Qualitative Analysis of Perceptions on Recommender Systems

Contact Info

Product

Resources

About