141 citations · 348 across the 38 of their papers we have counts for
3 papers · 1 filter
Leakage and the Reproducibility Crisis in ML-based Science
Sayash Kapoor, Arvind Narayanan
The use of machine learning (ML) methods for prediction and forecasting has become widespread across the quantitative sciences. However, there are many known methodological pitfall…
Weaving Privacy and Power: On the Privacy Practices of Labor Organizers in the U.S. Technology Industry
Sayash Kapoor, Matthew Sun, Mona Wang +2
We investigate the privacy practices of labor organizers in the computing technology industry and explore the changes in these practices as a response to remote work. Our study is…
The worst of both worlds: A comparative analysis of errors in learning from data in psychology and machine learning
Jessica Hullman, Sayash Kapoor, Priyanka Nanayakkara +2
Recent arguments that machine learning (ML) is facing a reproducibility and replication crisis suggest that some published claims in ML research cannot be taken at face value. Thes…