Jessie J. Smith

REAL-ML. The Recognizing, Exploring, and Articulating Limitations in Machine Learning research tool (REAL ML) is a set of guided activities to help ML researchers recognize, explore, and articulate the limitations that arise in their research.

personal-sentiment-analysis. Data Science project that implements sentiment analysis on your personal facebook account. By cross-examining the public timeline posts vs. the private messages, I created visualizations to discover if my private sentiment is different than my public sentiment. Then, I used a machine learning algorithm to predict what my future sentiment might be.

fairness-ml-tutorial. Open Source tutorial for introductory data scientists to implement fairness models to correct for training data redundantly encoded with bias.

FairnessFeedback. The repo that holds the code for the ongoing study assessing whether fairness metrics can help minimize unwanted feedback loops in certain multistakeholder recommender systems.

DatosProfundos. An open source repository for English and Spanish speakers who are interested in learning how to use data science to create a social impact.

TwitterTrends. A tutorial to reverse engineer Twitter's trending algorithm. In this repo you will also find a report that highlights some ethical concerns with social media engagement manipulation.

intro.python.ethics. A full curriculum to teach introductory coding in python through the use of modern ethics, HCI, & STS case studies.

AILight. Repository for 'Palette'. This project utilizes the Phillips Hue Light SDK, kmeans clustering algorithms, PyTorch's neural net modules, and the Flask framework for Swift to Python integration.

ProPublicaCritique. Replicating the famous ProPublic Machine Bias study with an emphasis on gender bias rather than racial bias