AIMC Topic: Bias

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Challenges of artificial intelligence in medicine and dermatology.

Clinics in dermatology
Artificial intelligence (AI) in medicine and dermatology brings additional challenges related to bias, transparency, ethics, security, and inequality. Bias in AI algorithms can arise from biased training data or decision-making processes, leading to ...

Measurement and Mitigation of Bias in Artificial Intelligence: A Narrative Literature Review for Regulatory Science.

Clinical pharmacology and therapeutics
Artificial intelligence (AI) is increasingly being used in decision making across various industries, including the public health arena. Bias in any decision-making process can significantly skew outcomes, and AI systems have been shown to exhibit bi...

Efficient adversarial debiasing with concept activation vector - Medical image case-studies.

Journal of biomedical informatics
BACKGROUND: A major hurdle for the real time deployment of the AI models is ensuring trustworthiness of these models for the unseen population. More often than not, these complex models are black boxes in which promising results are generated. Howeve...

Adaptive bias-variance trade-off in advantage estimator for actor-critic algorithms.

Neural networks : the official journal of the International Neural Network Society
Actor-critic methods are leading in many challenging continuous control tasks. Advantage estimators, the most common critics in the actor-critic framework, combine state values from bootstrapping value functions and sample returns. Different combinat...

Call for algorithmic fairness to mitigate amplification of racial biases in artificial intelligence models used in orthodontics and craniofacial health.

Orthodontics & craniofacial research
Machine Learning (ML), a subfield of Artificial Intelligence (AI), is being increasingly used in Orthodontics and craniofacial health for predicting clinical outcomes. Current ML/AI models are prone to accentuate racial disparities. The objective of ...

Humans inherit artificial intelligence biases.

Scientific reports
Artificial intelligence recommendations are sometimes erroneous and biased. In our research, we hypothesized that people who perform a (simulated) medical diagnostic task assisted by a biased AI system will reproduce the model's bias in their own dec...

Algorithmic bias and research integrity; the role of nonhuman authors in shaping scientific knowledge with respect to artificial intelligence: a perspective.

International journal of surgery (London, England)
Artificial intelligence technologies were developed to assist authors in bettering the organization and caliber of their published papers, which are both growing in quantity and sophistication. Even though the usage of artificial intelligence tools i...

AI pitfalls and what not to do: mitigating bias in AI.

The British journal of radiology
Various forms of artificial intelligence (AI) applications are being deployed and used in many healthcare systems. As the use of these applications increases, we are learning the failures of these models and how they can perpetuate bias. With these n...