Towards a Critical Race Methodology in Algorithmic Fairness | AISC

Channel:
Canada LLMs Explained - Aggregate Intellect - AI.SCIENCE
Subscribers:
22,300
Published on ● Video Link: https://www.youtube.com/watch?v=DGUsmxta9Jg


Category:
Vlog
Duration: 1:01:40
206 views
4

For slides and more information on the paper, visit https://ai.science/e/towards-a-critical-race-methodology-in-algorithmic-fairness--MShyVLeq5fN2fxnh8SAK

Speaker: Alex Hanna; Host: Willie Costello

Motivation:
While there has been much discussion of the racial disparities and biases in debates about algorithmic fairness, there has been much less discussion of how race and racial categories are themselves conceptualized in these debates. This paper fills this gap in the literature, explaining what it means to think of race as a structural, institutional, and relational phenomenon, and why this can help us recognize the structural aspects of algorithmic unfairness.

------
#AISC hosts 3-5 live sessions like this on various AI research, engineering, and product topics every week! Visit https://ai.science for more details



Other Videos By LLMs Explained - Aggregate Intellect - AI.SCIENCE


2020-10-23Detecting and Correcting Unfairness in Machine Learning | AISC
2020-10-23Highly Recommended: A Fireside Chat with AISC's Resident Experts on Recommender Systems
2020-10-23A Fireside Chat with AISC NLP experts
2020-10-22Machine Learning in Environmental Science and Prediction: An Overview | AISC
2020-10-22Battery Modelling using Data-Driven Machine Learning | AISC
2020-10-21BERTology Meets Biology: Interpreting Attention in Protein Language Models | AISC
2020-10-20Design for Augmentation (not Automation) | AISC
2020-10-16Genomics with Deep Learning: A Concise Overview | AISC
2020-10-15Designing quantum computers with generative models | AISC
2020-10-15Explainable AI for Time Series - Literature Review | AISC
2020-10-15Towards a Critical Race Methodology in Algorithmic Fairness | AISC
2020-10-14An eye on AI in Healthcare | AISC
2020-10-13Some Salient Issues with Saliency Models | AISC
2020-10-13The Messy Side of AI Products | AISC
2020-10-09Human Aware AI: Reducing Transportation Energy of a City by Influencing Individual Behaviour
2020-10-08Policy Priority Inference: Simulations for Government Strategy | AISC
2020-10-07Inferring the 3D Standing Spine Posture from 2D Radiographs | AISC
2020-10-06Knowledge Extraction from Multimodal & Multilingual sources | AISC
2020-10-01Camera Depth of Field Manipulation for Pre- and Post-Image Capture | AISC
2020-09-30[MOREL] Unsupervised Video Object Segmentation for Deep Reinforcement Learning
2020-09-29Dealing with Bias and Fairness in Data Science Systems: A Practical Hands-on Tutorial | AISC