arrow
Return

Toward Responsible Recommender Systems

delete2024-05-01
delete0
PRE
AI
P
Przemysław Kazienko *
E
Erik Cambria
DOI:10.1109/MIS.2024.3398190delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Recommender systems have transformed our digital experiences in many regards. We enumerate six of their positive effects on the economy and humans, such as greater user satisfaction, time savings, broadening user horizons, and positive behavioral nudging. However, it is crucial to acknowledge the potential downsides inherent in their design. One significant concern is that these algorithms often prioritize the interests of the company deploying them, aiming to maximize profits and user engagement rather than solely focusing on enhancing user experience. Therefore, we also list and consider two use cases and six negative long-term impacts on humans, including addiction, reduced ability to think critically, less autonomy, and weakened human relationships caused by more and more human-like virtual assistants. Despite the undeniable utility of recommender systems, it is imperative to approach them critically, advocating for transparency, ethical considerations, and user empowerment to ensure that they serve as tools for enrichment rather than exploitation. To accomplish this, the idea and challenges of responsible recommender systems (RRSs) are presented. RRSs extend common recommender systems with components related to individual human values and goals as well as widely accepted well-being and lifestyle guidelines.
Keywords:
Ethics
Virtual assistants
User experience
Intelligent systems
Recommender systems
Digital systems
User centered design
Human factors

Journal

IEEE Intelligent Systems cover
IEEE Intelligent Systems
IF:
6.1
Papers:
1.6K
Citations:
4.5K

Organization

N
Nanyang Technological University
Scholars:
4.9W
Papers: 4.8W
Citations: 8.1W
Cited Papers

Cited Papers

Socialisation to High Mobility?
err2015-01-01
err0
PREAI
errStéphanie Vincent-Geslin; Emmanuel Ravalet
errShare
errSave
Filter bubbles in recommender systems: Fact or fallacy-A systematic review
err2023-08-03
err18
errOAAI
errAreeb, Qazi Mohammad; Nadeem, Mohammad; Sohail, Shahab Saquib; Imam, Raza; Doctor, Faiyaz; Himeur, Yassine; Hussain, Amir; Amira, Abbes
errShare
errSave
A survey on personality-aware recommendation systems
err2021-09-19
err62
PREAI
errDhelim, Sahraoui; Aung, Nyothiri; Bouras, Mohammed Amine; Ning, Huansheng; Cambria, Erik
errShare
errSave
Economic recommender systems - a systematic review
err2024-01-01
err5
errOAAI
errDe Biasio, Alvise; Navarin, Nicolo; Jannach, Dietmar
errShare
errSave
errShare
errSave
researcher View more