Basic online Attentional Bias Modification experiment in Javascript and PHP

A wiki slash playground for projects on how machines aquire biases.

Source code for Yik, W., Serafini, L., Lindsey, T., Montañez, G. (2022). Identifying Bias in Data Using Two-Distribution Hypothesis Tests. AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society. https://doi.org/10.1145/3514094.3534169

Properties of estimators using the Univariate Normal model

Group project for CS 6795 Introduction to Cognitive Science, Georgia Tech, Spring 2021

Assignment 3

Supplementary materials for the following publication: Davydenko, A., & Goodwin, P. (2021). Assessing point forecast bias across multiple time series: Measures and visual tools. International Journal of Statistics and Probability, 10(5), 46-69. https://doi.org/10.5539/ijsp.v10n5p46

Basic Statistics-01 Solution for Questions on Basic statistics

Selection and Misclassification Biases in Longitudinal Studies

Literature review demo for paper "Unsupervised Discovery of Implicit Gender Bias" at EMNLP'20

Basic concepts of Analog electronics and circuit design

Interactive web app for episensr

Analysis of Premier League data using machine learning techniques to detect bias in officials.

Can Chatbots Truly Be 'Unbiased'? Dissertation (UP847988)

This project explores the topic of bias and fairnness in Machine Learning using the UCI Adult dataset. It provides familiarity with the concept of bias in Machine Learning, explores differnt metrics used to quantify bias in machine learning, and demonstrates data and model-based approaches to audit bias and fairness in Machine Learning.

Code and files. Working paper: "Reporting of study limitations and hedging in articles with and without causal diagrams"

Data Challenge leading to "A Multidisciplinary Lens of Bias in Hate Speech" (ASONAM 2023)

The goal of this assignment is to explore the concept of bias through data on Wikipedia articles - specifically, articles on political figures from a variety of countries. Wikipedia articles and country populations datasets are combined, and ORES is used to estimate the quality of each article by country.

NoBias is Grammarly for Biased language in the internet. Improve your digital footground avoiding biased language while contributing to a better world.