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Evidence record 9306 · automatically gathered

Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies

The significant advancements in applying artificial intelligence (AI) to healthcare decision-making, medical diagnosis, and other domains have simultaneously raised concerns about the fairness and bias of AI systems. This is particularly critical in areas like healthcare, employment, criminal justice, credit scoring, and increasingly, in generative AI models (GenAI) that produce synthetic media. Such systems can lead to unfair outcomes and perpetuate existing inequalities, including generative b

Record details

Published: 26 December 2023
Source: OpenAlex
Category: Research
Topics: Bias & fairness · Jobs & economy · Misinformation · 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.

Same publisher byline · Shared topic: Misinformation

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Shared topic: Bias & fairness · Shared topic: Jobs & economy

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Shared topic: Bias & fairness · Shared topic: Jobs & economy

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arXiv · 22 May 2026

How to cite this record

ethics.ai (26 December 2023), “Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies,” evidence record 9306, https://ethics.ai/record/9306 (originally published by OpenAlex).

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