• Dr.V.N. Sudheer

  Author

The growth of cross-border web-based recruitment has reshaped the way organizations locate and assess talent, but it has also brought about the existence of subtle disparities imbued in digital recruitment. In the present paper, discuss the convergence of linguistic profiling and algorithmic discrimination in the recruitment practices worldwide and how language-related signals, like accent indicators, vocabulary, and styles of writing, can be used to affect the results of automated screening. Taking a theoretical and analytical approach, the research is a synthesis of recent literature in the field of language and identity and algorithmic decision-making and will form a conceptual definition of how linguistic characteristics are perceived by recruitment technologies. It becomes evident in the analysis that, regardless of the intent to improve the efficiency and objectivity of the hiring processes, algorithm-driven hiring systems can contribute to sustaining the current social hierarchies, favouring the normative linguistic processes. These kinds of systems are usually based on training data and assessment criteria that incorporate standardized language expectations. The results point to the idea that linguistic profiling is not solely a human process; it is becoming embedded in automated systems and, as such, forms a layer of discrimination that is hard to detect and to fight back. In this paper, it has been concluded that the solution to these issues needs a critical evaluation of the operationalization of language in recruitment technologies. It emphasizes the necessity to create more inclusive systems, transparency in the analysis of algorithms, and the policies that consider diversity of language as an asset and not a weakness. Placing linguistic profiling in the context of the wider discussion of algorithmic fairness, this paper is relevant to the current debate on equity and ethicality in digital recruitment spaces.

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