Conceptualizing algorithmic inequality and future agenda. An annual review of information science and technology (ARIST) paper

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

The issue of inequality caused by algorithms, termed ‘algorithmic inequality’, has recently attracted scholarly attention in many disciplines due to its profound implications for society. While the body of literature on algorithmic inequality has grown, there remains a lack of comprehensive understanding of its nature, drivers, and impact. This paper conducts a scoping review to understand and conceptualize algorithmic inequality in empirical research and to recommend a future agenda. Specifically, this paper provides a research mapping of how algorithmic inequality is defined, what drives it, and how it impacts key concerns in Library and Information Science (LIS). Furthermore, this paper proposes a thematic, theoretical, and methodological agenda for future research from an LIS perspective, based on these findings. This study contributes to the literature by offering a multidimensional conceptual framework for understanding the nature and drivers of algorithmic inequality. The framework also serves as a foundation for future research, fostering a deeper understanding of algorithmic inequality and its implications for LIS scholarship and practice.