… learning. Data mining of 54,842,787 initial (random subsample n = 5000) data points from one
online learning … Following examination of a theory-led machine learning model, a data-led …

… The goal should be, rather, to develop an integrated approach that can encompass, and
harmonize, both dimensions of social justice.” Could the same be said of the allocation-…

… theory of social justice. We offer it only as a plausible component of social justice in societies
in … to relevant information, we distinguish traditional machine learning from deep learning: …

… justice as a blueprint to guide and inform future research into fairness for Machine Learning.
… We propose the use of cardinal social welfare functions to address this issue and as an effi…

… when their care involves machine learning (ML) models … , and justice-based theories, we
describe the Justice, Equity, … guided by medical ethics and social justice principles. We provide …

… fault lines of social stratification falls somewhat … in-machine learning scholars are careful
not to suggest that the data that is used to train algorithmic systems and that describes the social …

… Nowadays, we are relying on Machine Learning (ML) algorithms … to reflect on social justice
while designing ML algorithms. … social justice and ethics are adequately taken into account? …

… ethics and social justice. Using open text responses, our initial machine learning model will
… which the project adheres to ethics and social justice criteria. Alternative models using other …

… sciences through machine learning algorithms not only differ and conflict with social scientists’
… law proce dure, but also overlook the political and social dimensions of data. To do so, we …

… that while machine learning offers significant possibilities for advancing racial justice and …
The outcome p(click) is trained to predict is distributed unequally across social groups: click …