30 citations · 51 across the 4 of their papers we have counts for
5 papers
New Tools are Needed for Tracking Adherence to AI Model Behavioral Use Clauses
Daniel McDuff, Tim Korjakow, Kevin Klyman +1
Foundation models have had a transformative impact on AI. A combination of large investments in research and development, growing sources of digital data for training, and architec…
Responding to Generative AI Technologies with Research-through-Design: The Ryelands AI Lab as an Exploratory Study
Jesse Josua Benjamin, Joseph Lindley, Elizabeth Edwards +4
Generative AI technologies demand new practical and critical competencies, which call on design to respond to and foster these. We present an exploratory study guided by Research-t…
On the Standardization of Behavioral Use Clauses and Their Adoption for Responsible Licensing of AI
Daniel McDuff, Tim Korjakow, Scott Cambo +9
Growing concerns over negligent or malicious uses of AI have increased the appetite for tools that help manage the risks of the technology. In 2018, licenses with behaviorial-use c…
Explanation Strategies as an Empirical-Analytical Lens for Socio-Technical Contextualization of Machine Learning Interpretability
Jesse Josua Benjamin, Christoph Kinkeldey, Claudia Müller-Birn +2
During a research project in which we developed a machine learning (ML) driven visualization system for non-ML experts, we reflected on interpretability research in ML, computer-su…
FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning
Felix Sattler, Tim Korjakow, Roman Rischke +1
Federated Distillation (FD) is a popular novel algorithmic paradigm for Federated Learning, which achieves training performance competitive to prior parameter averaging based metho…