Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Stephen C Slota"'
Publikováno v:
Big Data & Society, Vol 7 (2020)
Data science is characterized by engaging heterogeneous data to tackle real world questions and problems. But data science has no data of its own and must seek it within real world domains. We call this search for data “prospecting” and argue tha
Externí odkaz:
https://doaj.org/article/00363889f8e24e3cb990b2bb4bfd03d5
Publikováno v:
Proceedings of the Association for Information Science and Technology. 59:287-298
Autor:
Stephen C. Slota, Kenneth R. Fleischmann, Sherri Greenberg, Nitin Verma, Brenna Cummings, Lan Li, Chris Shenefiel
Publikováno v:
Journal of the Association for Information Science and Technology. 74:311-322
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031280313
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::beaf28db51f5aaa82cdaf94388e8cc0a
https://doi.org/10.1007/978-3-031-28032-0_38
https://doi.org/10.1007/978-3-031-28032-0_38
Autor:
Tara Zimmerman, Stephen C. Slota, James Snow, Michelle Surka, Keyanna S. Evans, Sherri R. Greenberg, Sarah Rodriguez, Kenneth R. Fleischmann
Publikováno v:
Proceedings of the Association for Information Science and Technology. 58:327-336
Autor:
Stephen C. Slota, Kenneth R. Fleischmann, Min Kyung Lee, Sherri R. Greenberg, Ishan Nigam, Tara Zimmerman, Sarah Rodriguez, James Snow
Publikováno v:
Journal of the Association for Information Science and Technology.
Autor:
Stephen C. Slota
Publikováno v:
Science, Technology, & Human Values. 47:750-773
Knowledge produced by environmental scientists is often inaccessible, intractable, or otherwise in need of reconfiguration for use in environmental regulation. Similarly, policy knowledge undergoes decontextualization in its address to the community
Publikováno v:
TMS Proceedings 2021.
Publikováno v:
Information for a Better World: Shaping the Global Future ISBN: 9783030969561
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f4987f9f5205363dc685ff90b5c5a58d
https://doi.org/10.1007/978-3-030-96957-8_19
https://doi.org/10.1007/978-3-030-96957-8_19
Autor:
Brenna Cummings, Stephen C. Slota, Lan Li, Chris Shenefiel, Nitin Verma, Kenneth R. Fleischmann, Sherri R. Greenberg
Publikováno v:
AI & SOCIETY.
Given the complexity of teams involved in creating AI-based systems, how can we understand who should be held accountable when they fail? This paper reports findings about accountable AI from 26 interviews conducted with stakeholders in AI drawn from