ai

Cloud Computing
May 30, 2026

Rethinc Labs – Fairness in Justice: Use of Machine Learning in Pre-trial Detention

A large body of social science evidence indicates that objective, reliable and valid risk assessment instruments are more accurate in evaluating risk than professional human judgements alone. In the world of pretrial detention, where more than 10 million people are jailed each year in the United States after arrest, pretrial risk assessment tools may provide a more efficient, transparent and fairer basis for making assessments than having a judge quickly scan documents detailing the defendant’s prior record and current charges and make a decision in mere minutes. However, these assessments will retain any bias present in the data used by criminal justice agencies.

The Risk of Digital Discrimination Exploring AI Bias

The Risk of Digital Discrimination: Exploring AI Bias

AI applications are ubiquitous – and so is their potential to exhibit unintended bias. Algorithmic and automation biases and algorithm aversion all plague the human-AI partnership, eroding trust between people and machines that learn. But can bias be eradicated from AI? Dr, Fay Cobb Payton, Professor of Information Systems & Technology at NC State’s Poole College of Management and a Program Director at the National Science Foundation in the Division of Computer and Network Systems moderates a discussion between Timnit Gebru, research scientist and the co-lead of the Ethical AI Team at Google and the co-founder of Black in AI; Brenda Leong, senior counsel and director of artificial intelligence and ethics at the Future of Privacy Forum; Professor Mohammad Jarrahi, associate professor at UNC’s School of Information and Library Science; and Chris Wicher, Rethinc. Labs AI Research Fellow, former director of AI Research at KPMG’s AI Center of Excellence and Vice President of Watson Engineering at IBM.