Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 1 |
| Since 2017 (last 10 years) | 1 |
| Since 2007 (last 20 years) | 1 |
Descriptor
| Algorithms | 1 |
| Artificial Intelligence | 1 |
| Case Studies | 1 |
| Decision Making | 1 |
| Elections | 1 |
| Generalization | 1 |
| Goal Orientation | 1 |
| Mathematics | 1 |
| Prediction | 1 |
| Probability | 1 |
| Problem Solving | 1 |
| More ▼ | |
Source
| Grantee Submission | 1 |
Publication Type
| Reports - Descriptive | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full text
Direct linkTamara Broderick; Andrew Gelman; Rachael Meager; Anna L. Smith; Tian Zheng – Grantee Submission, 2022
Probabilistic machine learning increasingly informs critical decisions in medicine, economics, politics, and beyond. To aid the development of trust in these decisions, we develop a taxonomy delineating where trust in an analysis can break down: (1) in the translation of real-world goals to goals on a particular set of training data, (2) in the…
Descriptors: Taxonomy, Trust (Psychology), Algorithms, Probability
