🔬 Research Summary by Ding Wang, a senior researcher from the Responsible AI Group in Google Research, specializing in responsible data practices with a specific focus on accounting for the human experience and … [Read more...] about A hunt for the Snark: Annotator Diversity in Data Practices
Fine-Grained Human Feedback Gives Better Rewards for Language Model Training
🔬 Research Summary by Zeqiu Wu and Yushi Hu Zeqiu Wu is a final-year PhD student at University of Washington, where she works on language models that converse with and learn from information-seeking … [Read more...] about Fine-Grained Human Feedback Gives Better Rewards for Language Model Training
Whose AI Dream? In search of the aspiration in data annotation.
🔬 Research Summary by Ding Wang, a senior researcher from the Responsible AI Group in Google Research, specializing in responsible data practices with a specific focus on accounting for the human experience and … [Read more...] about Whose AI Dream? In search of the aspiration in data annotation.
Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation.
🔬 Research Summary by 1) Natalia Díaz Rodríguez, 2) Javier Del Ser, 3) Mark Coeckelbergh, 4) Marcos López de Prado, 5) Enrique Herrera-Viedma, and 6) Francisco Herrera 1) Assistant Professor, University of … [Read more...] about Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation.
Promoting Bright Patterns
🔬 Research Summary by Hauke Sandhaus, a Ph.D. student in Information Science at Cornell Tech researching wicked design problems in Human-AI-Interaction to create an ethical future of automation. [Original paper … [Read more...] about Promoting Bright Patterns