What are the ethical considerations related to the collection, sharing, and use of potentially biased datasets for machine learning research and applications?

Aug 12, 2020 ... What are Bias and Variance? · Bias: it's the difference between average predictions and true values. · Variance: it's the variability of our ... May 17, 2024 ... A set of ML models (random forest, XGBoost, multiplayer perceptron) are trained using citizen weather station observations and UKV variables ... Feb 10, 2021 ... The application of machine learning (ML) technologies in medicine generally but also in radiology more specifically is hoped to improve ... Aug 29, 2022 ... One of the main areas for concern is bias in AI systems. Bias can inappropriately skew the output from AI in favor of certain data sets; ... Jun 28, 2022 ... 'It's not going to work': Keeping race out of machine learning isn't enough to avoid bias ... As more machine learning tools reach patients, ... Previous research revealed the existence of large near-surface temperature biases (mostly warm) over the Arctic sea ice in the current generation of atmospheric ... As humanities scholars start to make use of the possibilities provided by AI, there is a risk that humanities scholarship can become polluted by hidden gender ... Mar 26, 2018 ... In the case of self-learning systems, the type of “garbage” is biased data. Left unchecked, feeding biased data to self-learning systems can ... Mar 19, 2010 ... A bias value allows you to shift the activation function to the left or right, which may be critical for successful learning. Mar 10, 2025 ... PhyloFrame is an equitable machine learning method that creates signatures of disease based on population genomics data and disease-relevant ...