AI‑powered recommender systems and the preservation of personal autonomy
Metadatos
Afficher la notice complèteEditorial
Springer Nature
Materia
Artificial intelligence Recommender systems Autonomy Identity Regulation Value sensitive design
Date
2023-07-21Referencia bibliográfica
del Valle, J.I., Lara, F. AI-powered recommender systems and the preservation of personal autonomy. AI & Soc (2023). [https://doi.org/10.1007/s00146-023-01720-2]
Patrocinador
Universidad de Granada/ CBUA; Agencia Estatal de Investigación (PID2019-104943RB-I00) FEDER/ Junta de Andalucía (B-HUM-64- UGR20)Résumé
Recommender Systems (RecSys) have been around since the early days of the Internet, helping users navigate the vast ocean
of information and the increasingly available options that have been available for us ever since. The range of tasks for which
one could use a RecSys is expanding as the technical capabilities grow, with the disruption of Machine Learning representing
a tipping point in this domain, as in many others. However, the increase of the technical capabilities of AI-powered RecSys
did not come with a thorough consideration of their ethical implications and, despite being a well-established technical
domain, the potential impacts of RecSys on their users are still under-assessed. This paper aims at filling this gap in regards
to one of the main impacts of RecSys: personal autonomy. We first describe how technology can affect human values and a
suitable methodology to identify these effects and mitigate potential harms: Value Sensitive Design (VSD). We use VSD to
carry out a conceptual investigation of personal autonomy in the context of a generic RecSys and draw on a nuanced account
of procedural autonomy to focus on two components: competence and authenticity. We provide the results of our inquiry as
a value hierarchy and apply it to the design of a speculative RecSys as an example