The world according to the data #AI sees. 50% of datasets are connected to 12 institutions. Analysis of 4384 datasets and 60647 papers.
Read the report: https://arxiv.org/abs/2112.01716
By @[email protected] @[email protected] @[email protected]
Benchmark datasets play a central role in the organization of machine learning research. They coordinate researchers around shared research problems and serve as a measure of progress towards shared goals. Despite the foundational role of benchmarking practices in this field, relatively little attention has been paid to the dynamics of benchmark dataset use and reuse, within or across machine learning subcommunities. In this paper, we dig into these dynamics. We study how dataset usage patterns differ across machine learning subcommunities and across time from 2015-2020. We find increasing concentration on fewer and fewer datasets within task communities, significant adoption of datasets from other tasks, and concentration across the field on datasets that have been introduced by researchers situated within a small number of elite institutions. Our results have implications for scientific evaluation, AI ethics, and equity/access within the field.
We are very pleased to announce the public lecture by Noopur Raval tetisheri ＊The Algorithm is a Convenient Lie: Rethinking expertise and invisibility to support decolonial digital practice.＊ February 2nd, 2023, 7 pm, online.
More info here:… https://mastodon.social/@katjamat/109739289332905460
🐦🔗: https://twitter.com/katja_mat/status/1617549679956316160
Heute demonstrieren wir vom #unterbau gemeinsam mit den Studierenden für gute Bedingungen für die Bildung! 🤝 @[email protected] @[email protected]
Check out our recent contribution to the CoAct Global Perspectives series by @[email protected] ➡️ Open Citizen Social Science and Collaboration - A key element in driving STEM Education in South Sudan. ▶️https://buff.ly/3VBG4DP #citizensocialscience
