“Don’t let me be misunderstood”

Research and development as well as societal debates on the risks of artificial intelligence (AI) often focus on crucial but impractical ethical issues or on technocratic approaches to managing societal and ethical risks with technology. To overcome this, more practical, problem-oriented analytical...

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Main Author: Stefan Strauß
Format: Article
Language:deu
Published: oekom verlag GmbH 2021-12-01
Series:TATuP – Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis
Subjects:
Online Access:https://tatup.de/index.php/tatup/article/view/6930
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author Stefan Strauß
author_facet Stefan Strauß
author_sort Stefan Strauß
collection DOAJ
description Research and development as well as societal debates on the risks of artificial intelligence (AI) often focus on crucial but impractical ethical issues or on technocratic approaches to managing societal and ethical risks with technology. To overcome this, more practical, problem-oriented analytical perspectives on the risks of AI are needed. This article proposes an approach that focuses on a meta-risk inherent in AI systems: deep automation bias. It is assumed that the mismatch between system behavior and user practice in specific application contexts due to AI‑based automation is a key trigger for bias and other societal risks. The article presents the main factors of (deep) automation bias and outlines a framework providing indicators for the detection of deep automation bias ultimately triggered by such a mismatch. This approach intends to strengthen problem awareness and critical AI literacy and thereby create some practial use.
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language deu
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spelling doaj.art-4c75842da56a4b0bb1fc18a7bfdd0f6b2022-12-22T03:24:23Zdeuoekom verlag GmbHTATuP – Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis2568-020X2567-88332021-12-0130310.14512/tatup.30.3.44“Don’t let me be misunderstood”Stefan Strauß0Institute of Technology Assessment, Austrian Academy of SciencesResearch and development as well as societal debates on the risks of artificial intelligence (AI) often focus on crucial but impractical ethical issues or on technocratic approaches to managing societal and ethical risks with technology. To overcome this, more practical, problem-oriented analytical perspectives on the risks of AI are needed. This article proposes an approach that focuses on a meta-risk inherent in AI systems: deep automation bias. It is assumed that the mismatch between system behavior and user practice in specific application contexts due to AI‑based automation is a key trigger for bias and other societal risks. The article presents the main factors of (deep) automation bias and outlines a framework providing indicators for the detection of deep automation bias ultimately triggered by such a mismatch. This approach intends to strengthen problem awareness and critical AI literacy and thereby create some practial use.https://tatup.de/index.php/tatup/article/view/6930deep automation biasAI assessmentmachine learninguncertaintyawareness
spellingShingle Stefan Strauß
“Don’t let me be misunderstood”
TATuP – Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis
deep automation bias
AI assessment
machine learning
uncertainty
awareness
title “Don’t let me be misunderstood”
title_full “Don’t let me be misunderstood”
title_fullStr “Don’t let me be misunderstood”
title_full_unstemmed “Don’t let me be misunderstood”
title_short “Don’t let me be misunderstood”
title_sort don t let me be misunderstood
topic deep automation bias
AI assessment
machine learning
uncertainty
awareness
url https://tatup.de/index.php/tatup/article/view/6930
work_keys_str_mv AT stefanstrauß dontletmebemisunderstood