It seems like every day there is a new gig work platform (e.g. UpWork, Uber, Airbnb, or Rover) that uses a 5-star scale to rate workers. This helps workers build reputation and develop the trust necessary for gig work interactions, but there is a big concern: lots of prior work finds that race and gender biases occur when people evaluate each other. In an upcoming paper at the 2018 ACM CSCW conference, we describe what we thought would be a straightforward study of race and gender biases in 5-star reputation systems. However, it turned into an exercise in repeated experimentation to verify surprising results and careful statistical analysis to better understand our findings. Ultimately, we ended up with a future research agenda composed of compelling new hypotheses about race, gender and five-star rating scales. (more…)
Author Archives: Jacob Thebault-Spieker
Taavi proposed work on better explaining recommender systems output, focusing on the use of analogies to describe recommendations.
There were more than 16,000 applications for the Graduate Research Fellowship nationwide from all areas of science and engineering. The National Science Foundation (NSF) only awarded them to 2,000 students (of which GroupLens members were 0.1%!). The awards financially support 36 months of research and include opportunities for international research experiences.
Congratulations again, Taavi and Hannah!
GroupLens would like to congratulate Ed Chi (a Ph.D. graduate from our lab) and Patrick Baudisch (a former visiting graduate student to our lab) on being named ACM Distinguished Scientists! We wish them all the best and are very proud of their continued accomplishments!