Name
Abstract | ||
|---|---|---|
Artificial intelligence (AI) applications can profoundly affect society. Recently, there has been extensive interest in studying how scientists design AI systems for general tasks. However, it remains an open question as to whether the AI systems developed in this way can work as expected in different regional contexts while simultaneously empowering local people. How can scientists co-create AI systems with local communities to address regional concerns? This article contributes new perspectives in this underexplored direction at the intersection of data science, AI, citizen science, and human-computer interaction. Through case studies, we discuss challenges in co-designing AI systems with local people, collecting and explaining community data using AI, and adapting AI systems to long-term social change. We also consolidate insights into bridging AI research and citizen needs, including evaluating the social impact of AI, curating community datasets for AI development, and building AI pipelines to explain data patterns to laypeople. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.patter.2022.100449 | Patterns |
Keywords | DocType | Volume |
DSML 2: Proof-of-concept: Data science output has been formulated, implemented, and tested for one domain/problem | Journal | 3 |
Issue | ISSN | Citations |
3 | 2666-3899 | 0 |
PageRank | References | Authors |
0.34 | 1 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yen-Chia Hsu | 1 | 0 | 0.68 |
| Ting-Hao Huang | 2 | 146 | 19.23 |
| himanshu verma | 3 | 14 | 4.33 |
| Andrea Mauri | 4 | 109 | 16.75 |
| Illah Nourbakhsh | 5 | 2464 | 294.80 |
| Alessandro Bozzon | 6 | 641 | 71.27 |