Ashton, H;
Franklin, M;
(2022)
The problem of behaviour and preference manipulation in AI systems.
In:
Proceedings of the Workshop on Artificial Intelligence Safety 2022 (SafeAI 2022).
CEUR Workshop Proceedings
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Abstract
Statistical AI or Machine learning can be applied to user data in order to understand user preferences in an effort to improve various services. This involves making assumptions about either stated or revealed preferences. Human preferences are susceptible to manipulation and change over time. When iterative AI/ML is applied, it becomes difficult to ascertain whether the system has learned something about its users, whether its users have changed/learned something or whether it has taught its users to behave in a certain way in order to maximise its objective function. This article discusses the relationship between behaviour and preferences in AI/ML, existing mechanisms that manipulate human preferences and behaviour and relates them to the topic of value alignment.
| Type: | Proceedings paper |
|---|---|
| Title: | The problem of behaviour and preference manipulation in AI systems |
| Event: | SafeAI 2022: Artificial Intelligence Safety 2022 |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | http://ceur-ws.org/Vol-3087/ |
| Language: | English |
| Additional information: | Copyright © 2022 for the individual papers by the papers' authors. Copyright © 2022 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0). |
| 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/10146136 |
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