Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Proceedings of the 4th ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization |
| Untertitel | EAAMO 2024 |
| Seitenumfang | 11 |
| ISBN (elektronisch) | 9798400712227 |
| Publikationsstatus | Veröffentlicht - 29 Okt. 2024 |
| Veranstaltung | 4th ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization, EAAMO 2024 - San Luis Potosi, Mexiko Dauer: 29 Okt. 2024 → 31 Okt. 2024 |
Abstract
While some research fields have a long history of collaborating with domain experts outside academia, many quantitative researchers do not have natural avenues to meet experts in areas where the research is later deployed. We explain how conversations - interviews without a specific research objective - can bridge research and practice. Using collaborative autoethnography, we reflect on our experience of conducting conversations with practitioners from a range of different backgrounds, including refugee rights, conservation, addiction counseling, and municipal data science. Despite these varied backgrounds, common lessons emerged, including the importance of valuing the knowledge of experts, recognizing that academic research and practice have differing objectives and timelines, understanding the limits of quantification, and avoiding data extractivism. We consider the impact of these conversations on our work, the potential roles we can serve as researchers, and the challenges we anticipate as we move forward in these collaborations.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Artificial intelligence
- Informatik (insg.)
- Theoretische Informatik und Mathematik
- Informatik (insg.)
- Computergrafik und computergestütztes Design
- Informatik (insg.)
- Angewandte Informatik
- Informatik (insg.)
- Information systems
- Mathematik (insg.)
- Computational Mathematics
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- BibTex
- RIS
Proceedings of the 4th ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization: EAAMO 2024. 2024. 7.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Bridging Research and Practice Through Conversation
T2 - 4th ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization, EAAMO 2024
AU - Russo, Mayra
AU - Jorgensen, MacKenzie
AU - Scott, Kristen M.
AU - Xu, Wendy
AU - Nguyen, Di H.
AU - Finocchiaro, Jessie
AU - Olckers, Matthew
N1 - Publisher Copyright: © 2024 Owner/Author.
PY - 2024/10/29
Y1 - 2024/10/29
N2 - While some research fields have a long history of collaborating with domain experts outside academia, many quantitative researchers do not have natural avenues to meet experts in areas where the research is later deployed. We explain how conversations - interviews without a specific research objective - can bridge research and practice. Using collaborative autoethnography, we reflect on our experience of conducting conversations with practitioners from a range of different backgrounds, including refugee rights, conservation, addiction counseling, and municipal data science. Despite these varied backgrounds, common lessons emerged, including the importance of valuing the knowledge of experts, recognizing that academic research and practice have differing objectives and timelines, understanding the limits of quantification, and avoiding data extractivism. We consider the impact of these conversations on our work, the potential roles we can serve as researchers, and the challenges we anticipate as we move forward in these collaborations.
AB - While some research fields have a long history of collaborating with domain experts outside academia, many quantitative researchers do not have natural avenues to meet experts in areas where the research is later deployed. We explain how conversations - interviews without a specific research objective - can bridge research and practice. Using collaborative autoethnography, we reflect on our experience of conducting conversations with practitioners from a range of different backgrounds, including refugee rights, conservation, addiction counseling, and municipal data science. Despite these varied backgrounds, common lessons emerged, including the importance of valuing the knowledge of experts, recognizing that academic research and practice have differing objectives and timelines, understanding the limits of quantification, and avoiding data extractivism. We consider the impact of these conversations on our work, the potential roles we can serve as researchers, and the challenges we anticipate as we move forward in these collaborations.
KW - AI4SG
KW - collaborative autoethnography
KW - participatory methods
UR - http://www.scopus.com/inward/record.url?scp=85212448747&partnerID=8YFLogxK
U2 - 10.48550/arXiv.2409.05880
DO - 10.48550/arXiv.2409.05880
M3 - Conference contribution
AN - SCOPUS:85212448747
BT - Proceedings of the 4th ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization
Y2 - 29 October 2024 through 31 October 2024
ER -