Franklin, M;
Ashton, H;
Gorman, R;
Armstrong, S;
(2022)
Missing Mechanisms of Manipulation in the EU AI Act.
In:
Proceedings of the International Florida Artificial Intelligence Research Society Conference, FLAIRS.
University of Florida George A Smathers Libraries
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Abstract
The European Union Artificial Intelligence (AI) Act proposes to ban AI systems that ”manipulate persons through subliminal techniques or exploit the fragility of vulnerable individuals, and could potentially harm the manipulated individual or third person”. This article takes the perspective of cognitive psychology to analyze and understand what algorithmic manipulation consists of, who vulnerable individuals may be, and what is considered as harm. Subliminal techniques are expanded with concepts from behavioral science and the study of preference change. Individual psychometric differences which can be exploited are used to expand the concept of vulnerable individuals. The concept of harm is explored beyond physical and psychological harm to consider harm to one’s time and right to an un-manipulated opinion. The paper offers policy recommendations that extend from the paper’s analyses.
Type: | Proceedings paper |
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Title: | Missing Mechanisms of Manipulation in the EU AI Act |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.32473/flairs.v35i.130723 |
Publisher version: | https://doi.org/10.32473/flairs.v35i.130723 |
Language: | English |
Additional information: | Copyright (c) 2022 Matija Franklin, Hal Ashton, Rebecca Gorman, Stuart Armstrong. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
Keywords: | EU AI Act, Manipulation, Influence, Preference Change, Behavior Change, AI Policy |
UCL classification: | UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science UCL > Provost and Vice Provost Offices > UCL BEAMS UCL |
URI: | https://discovery.ucl.ac.uk/id/eprint/10150670 |
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