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Evidence record 1037 · automatically gathered

Beyond the Algorithm: Professional Experiences and Perceptions of AI Bias

The purpose of this qualitative multi-case study was to examine how social bias emerges, is perceived, and can be mitigated within artificial intelligence and machine learning systems by practitioners directly involved in their design, development, and governance. Although examples from healthcare, criminal justice, employment, and education were used to illustrate domains where automated systems shape everyday life, the study focused on the lived experiences and professional insights of AI prac

Record details

Published: 13 June 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Regulation · Jobs & economy · Healthcare
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Bias & fairness · Shared topic: Regulation

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Shared topic: Regulation · Shared topic: Jobs & economy

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How to cite this record

ethics.ai (13 June 2026), “Beyond the Algorithm: Professional Experiences and Perceptions of AI Bias,” evidence record 1037, https://ethics.ai/record/1037 (originally published by arXiv).

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