Ethical AI and Librarianship
A Resource Guide
Assembling Accountability: Algorithmic Impact Assessment for the Public Interest
|
Field
|
Description | |
|---|---|---|
| Title | Assembling Accountability: Algorithmic Impact Assessment for the Public Interest | |
| Type | Reports | |
| Creator | Emanuel Moss, Elizabeth Anne Watkins, Ranjit Singh, Madeleine Clare Elish, Jacob Metcalf | |
| Link | ||
| Creation Date | 06/29/2021 | |
| Last Updated Date | -- | |
| Summary | Produced by Data & Society and authored by Emanuel Moss, Elizabeth Anne Watkins, Ranjit Singh, Madeleine Clare Elish, and Jacob Metcalf, this report explores the concept and practice of Algorithmic Impact Assessments (AIAs) as a governance tool for mitigating algorithmic harms. To propose effective AIA regimes, the report draws from impact assessment practices in other domains (finance, environment, human rights, privacy) and identifies ten common components of existing impact assessment practices. The report emphasizes that there is no single AIA process that can be effective due to the variations in governing bodies, systems being evaluated, and affected communities. Finally, the report reviews existing AIA regulations and auditing mechanisms using the ten-component framework to highlight challenges and gaps in constructing effective AIA regimes. Additionally, a webpage provides an overview of the report along with access to related resources (see Link field). | |
| Topic | Ethical AI | |
| Source and Link | Data & Society. https://datasociety.net/ | |
| Access | Open | |
| Accessibility | -- | |
| Audience | General. Scholars and Students. | |
| Platform or Format | Document (.pdf) | |
| Length | 64 pages | |
| Geography | USA | |
| Language | ENG | |
| Description Date | 06/24/2025 |