Stephen C Slota
Biographic Data
| ID | 911107 |
|---|---|
| NAME | Stephen C Slota |
| GIVEN NAMES | Stephen C |
| FAMILY NAME | Slota |
| SIGNATURE | SLOTA S C |
| AFFILIATIONS | The University of Texas at Austin |
| ORCID | 0000-0001-6526-8030 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 12 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 1 |
Many hands make many fingers to point: Challenges in creating accountable AI
Bootstrapping the Boundary between Research and Environmental Management: The TMDL as a Point of Engagement between Science and Governance
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 of researchers and data curators whose findings are fundamental to its operation. This paper addresses the development of the total maximum daily load (TMDL) measurement as a means of decontextualizin…
Prospecting (in) the data sciences
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 that the dynamics of prospecting are pervasive in, even characteristic of, data science. Prospecting aims to render the data, knowledge, expertise, and practices of worldly domains available and tractable to…
Prospecting (in) the data sciences
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 that the dynamics of prospecting are pervasive in, even characteristic of, data science. Prospecting aims to render the data, knowledge, expertise, and practices of worldly domains available and tractable to…
Prospecting (in) the data sciences
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 that the dynamics of prospecting are pervasive in, even characteristic of, data science. Prospecting aims to render the data, knowledge, expertise, and practices of worldly domains available and tractable to…
Bootstrapping the Boundary between Research and Environmental Management: The TMDL as a Point of Engagement between Science and Governance
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 of researchers and data curators whose findings are fundamental to its operation. This paper addresses the development of the total maximum daily load (TMDL) measurement as a means of decontextualizin…
Many hands make many fingers to point: Challenges in creating accountable AI
Computer Science (3 works) · Political science (3 works) · Sociology (3 works) · Business (2 works) · Engineering (2 works) · Knowledge management (2 works) · Law (2 works) · Accountability (1 works) · Artificial Intelligence (1 works) · Artificial Intelligence in Healthcare and Education (1 works)