Home

Research Summary

Digital technologies and artificial intelligence permeate every bit of our existence, and their uses regulate several aspects of our lives.

Knowing that the use of such technologies tends to increase and not to decrease in upcoming years, a team of researchers at Oregon State University developed a project that aims to tackle the issue of responsible development of artificial intelligence specifically in regards to fairness.

Project Goals

  1. To enable human input in the design and implementation of algorithms, more specifically in adjusting the tradeoffs between prediction accuracy, prediction fairness, case coverage and algorithm training time. As well as training with (sub-)datasets from different historical periods, and different regions/countries, or of different age sets, racial/ethnic groups.
  2. To avoid unfair decisions on a subset of data as opposed to the whole dataset.
  3. To abstain from potentially inaccurate predictions or unfair decisions and invite human collaborators to investigate uncovered subsets.

Researchers

Fuxin

Fuxin Li is currently an associate professor in the School of Electrical Engineering and Computer Science at Oregon State University. Before that, he has held research positions in University of Bonn and Georgia Institute of Technology. He had obtained a Ph.D. degree in the Institute of Automation, Chinese Academy of Sciences in 2009. He has won an NSF CAREER award, an Amazon Research Award, (co-)won the PASCAL VOC semantic segmentation challenges from 2009-2012, and led a team to the 4th place finish in the DAVIS Video Segmentation challenge 2017. He has published more than 60 papers in computer vision, machine learning and natural language processing. His main research interests are deep learning, video object segmentation, multi-target tracking, point cloud deep networks, uncertainty estimation in deep learning and human understanding of deep learning.

Shao

Shaozeng Zhang is an Assistant Professor of anthropology at Oregon State University (OSU). He received his PhD degree in anthropology from the University of California, Irvine in 2014. His research interests include the studies of Science, Technology and Society (STS), applied anthropology, and environmental anthropology. His research has been funded by the U.S. National Science Foundation (NSF) grants, the U.S. Department of Energy (DoE) Award, OSU Ecampus Research Fellowship, Chinese National Social Sciences Foundation grant, and Institute of Money, Technology and Financial Inclusion Fellowship. He has published papers in anthropology and multidisciplinary journals as well as book chapters in edited volumes.

Student Researchers

Ana

Ana is a Ph.D. student in applied anthropology at Oregon State University. She has a background in social sciences and her research interests are at the intersection of algorithms and society. STS-oriented, Ana is interested in algorithms as political devices, in ways that they order and reorder the world.

Ali

Ali Behnoudfar is a Computer Science Master’s student and a Graduate Research Assistant at Oregon State University. He is advised by Dr. Fuxin Li. His research interests include Computer Vision and Fairness in Machine Learning. He holds a BSc in Computer Engineering from Amirkabir University of Technology.

Ethan

Ethan Copple is a master’s student studying both Industrial Systems Engineering and Applied Anthropology at Oregon State University. His research includes systems science and transdisciplinary research methods development.

Xiaolu

Xiaolu Ji is graduating with her Bachelor’s degree in communication and sociology from Tsinghua University, China in June 2022 and starting her graduate study in Media Studies at the University of Amsterdam, Netherlands in September 2022. Xiaolu’s research interests include digital STS, critical data studies, algorithms and inequality.

Danielle

Danielle Chhabra is an undergraduate student in the college of Liberal Arts studying cultural anthropology. Her studies intersect at the subjects of anthropology and social justice, causing interest in the study of AI fairness and its effects on society.