Algorithmic Prestige: Signaling, Performance, and Professional Legitimacy Among Knowledge Workers

Lauren Danny

No mdz83_v1, SocArXiv from Center for Open Science

Abstract: Generative artificial intelligence has penetrated professional and academic environments to alter standards of intellectual output and productivity. Relying on semi-structured interviews with 45 participants across technology, legal, and academic sectors, this study examines how individuals utilize AI tools to construct professional identity. We propose the notion of algorithmic prestige: the strategic appropriation of machine-generated outputs to signal superior cognitive bandwidth and technical sophistication within competitive institutional hierarchies. We argue that while AI is ostensibly adopted for efficiency, it functions primarily as a mechanism for reinforcing existing power structures and performative competence. Our findings indicate that participants navigate AI use through a complex tension between productivity and authenticity. Transparency in tool usage often triggers professional penalties. Reliance on automated systems creates new dependencies. The pursuit of efficiency frequently devolves into intensive digital labor. Algorithmic prestige serves as a sociotechnical veneer that masks underlying anxieties regarding the obsolescence of human-centric expertise, suggesting that future policy must address the ethical imperatives of algorithmic transparency in high-stakes environments.

Date: 2026-07-21
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:mdz83_v1

DOI: 10.31219/osf.io/mdz83_v1

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