🔬 Research Summary by Edward Small, a Ph.D. candidate in computer science at the Royal Melbourne Institute of Technology with his research focused on fair and explainable artificial intelligence. [Original paper … [Read more...] about Counterfactual Explanations via Locally-guided Sequential Algorithmic Recourse
Core Principles of Responsible AI
Outsourced & Automated: How AI Companies Have Taken Over Government Decision-Making
🔬 Research Summary by Grant Fergusson, an Equal Justice Works Fellow at the Electronic Privacy Information Center (EPIC), where he focuses on AI and automated decision-making systems within state and local … [Read more...] about Outsourced & Automated: How AI Companies Have Taken Over Government Decision-Making
Bias and Fairness in Large Language Models: A Survey
🔬 Research Summary by Isabel O. Gallegos, a Ph.D. student in Computer Science at Stanford University, researching algorithmic fairness to interrogate the role of artificial intelligence in equitable … [Read more...] about Bias and Fairness in Large Language Models: A Survey
On the Challenges of Deploying Privacy-Preserving Synthetic Data in the Enterprise
🔬 Research Summary by Lauren Arthur, Marketing Director at Hazy, a leading synthetic data company. [Original paper by Georgi Ganev, Jason Costello, Jonathan Hardy, Will O’Brien, James Rea, Gareth Rees, and Lauren … [Read more...] about On the Challenges of Deploying Privacy-Preserving Synthetic Data in the Enterprise
Algorithmic Harms in Child Welfare: Uncertainties in Practice, Organization, and Street-level Decision-Making
🔬 Research Summary by Devansh Saxena, a Presidential Postdoctoral Fellow at Carnegie Mellon University in the Human-Computer Interaction Institute. He studies sociotechnical practices of decision-making in the public … [Read more...] about Algorithmic Harms in Child Welfare: Uncertainties in Practice, Organization, and Street-level Decision-Making