AI and the reduction of social inequalities in a linguistic perspective
Year: 2024
Type: conference-paper
Abstract: Artificial intelligence (AI) has the potential to both exacerbate and alleviate social inequalities. In this paper, we investigate AI's impact from a linguistic perspective, focusing on economic disparities, resource allocation, and ethical considerations. Actuality: We examine the current state of AI adoption and its implications for social equity. Recent developments, trends, and challenges related to AI's influence on linguistic and social disparities are highlighted. Purpose: Our research aims to investigate how AI can contribute to reducing inequalities. Specifically, we consider linguistic aspects, such as language bias in AI algorithms, alongside broader societal implications. Research Methods:Our methodology involves a comprehensive literature review. We analyse existing studies, case examples, and empirical evidence related to AI's impact on social inequalities. Results: Preliminary findings suggest that responsible AI design can bridge gaps and dismantle biases. By prioritizing fairness, transparency, and ethical development, we can harness AI's power to create a more equitable society across linguistic boundaries.In summary, this paper advocates for vigilance and empathy in embracing transformative AI technologies to address social disparities.
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
SDG: Reduced inequalities
Open Access status: gold
OpenAlex ID: W4412500335