Work

The Impact of Data Augmentation and Oversampling on Cultural Competence in Social Robotics

Year: 2024

Type: conference-paper

Abstract: In recent years, as robots have gained popularity, concerns have emerged about their ethical and social implications, particularly the need for robots to adapt to different cultures by being culturally competent. This issue is especially pronounced in autonomous systems that use machine learning (ML), as these systems tend to mirror disparities in the data, often underrepresenting certain cultures. To address this issue, various techniques are used in ML; in this article, we apply data augmentation (DA) and oversampling (OS) to assess how these methods affect the cultural competence of ML models in two social robotics use cases.

Source: CINECA IRIS Institutial Research Information System (University of Genoa)

DOI: 10.5281/zenodo.14730978

Authors: Petrocco, Enzo Ubaldo, Sgorbissa, Antonio, Oneto, Luca

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W6930727890

FWCI:

Cites:

Cited by:

Related to: