Abstract
| Language | English |
|---|---|
| Journal | Government Information Quarterly |
| Volume | 36 |
| Issue number | 2 |
| Pages | 368-383 |
| Number of pages | 16 |
| ISSN | 0740-624X |
| DOIs | |
| State | Published - 2019 |
Bibliographical note
Published online: 9. October 2018
Keywords
- Artificial intelligence
- Public sector
- Healthcare
- Challenges
- Framing
- China
Cite this
}
Mapping the Challenges of Artificial Intelligence in the Public Sector : Evidence from Public Healthcare. / Sun, Qian; Medaglia, Rony.
In: Government Information Quarterly, Vol. 36, No. 2, 2019, p. 368-383.Research output: Contribution to journal › Journal article › Research › peer-review
TY - JOUR
T1 - Mapping the Challenges of Artificial Intelligence in the Public Sector
T2 - Government Information Quarterly
AU - Sun,Qian
AU - Medaglia,Rony
N1 - Published online: 9. October 2018
PY - 2019
Y1 - 2019
N2 - The nascent adoption of Artificial Intelligence (AI) in the public sector is being assessed in contradictory ways. But while there is increasing speculation about both its dangers and its benefits, there is very little empirical research to substantiate them. This study aims at mapping the challenges in the adoption of AI in the public sector as perceived by key stakeholders. Drawing on the theoretical lens of framing, we analyse a case of adoption of the AI system IBM Watson in public healthcare in China, to map how three groups of stakeholders (government policy-makers, hospital managers/doctors, and Information Technology (IT) firm managers) perceive the challenges of AI adoption in the public sector. Findings show that different stakeholders have diverse, and sometimes contradictory, framings of the challenges. We contribute to research by providing an empirical basis to claims of AI challenges in the public sector, and to practice by providing four sets of guidelines for the governance of AI adoption in the public sector.
AB - The nascent adoption of Artificial Intelligence (AI) in the public sector is being assessed in contradictory ways. But while there is increasing speculation about both its dangers and its benefits, there is very little empirical research to substantiate them. This study aims at mapping the challenges in the adoption of AI in the public sector as perceived by key stakeholders. Drawing on the theoretical lens of framing, we analyse a case of adoption of the AI system IBM Watson in public healthcare in China, to map how three groups of stakeholders (government policy-makers, hospital managers/doctors, and Information Technology (IT) firm managers) perceive the challenges of AI adoption in the public sector. Findings show that different stakeholders have diverse, and sometimes contradictory, framings of the challenges. We contribute to research by providing an empirical basis to claims of AI challenges in the public sector, and to practice by providing four sets of guidelines for the governance of AI adoption in the public sector.
KW - Artificial intelligence
KW - Public sector
KW - Healthcare
KW - Challenges
KW - Framing
KW - China
KW - Artificial intelligence
KW - Public sector
KW - Healthcare
KW - Challenges
KW - Framing
KW - China
UR - https://sfx-45cbs.hosted.exlibrisgroup.com/45cbs?url_ver=Z39.88-2004&url_ctx_fmt=info:ofi/fmt:kev:mtx:ctx&ctx_enc=info:ofi/enc:UTF-8&ctx_ver=Z39.88-2004&rfr_id=info:sid/sfxit.com:azlist&sfx.ignore_date_threshold=1&rft.object_id=954925538153&rft.object_portfolio_id=&svc.holdings=yes&svc.fulltext=yes
U2 - 10.1016/j.giq.2018.09.008
DO - 10.1016/j.giq.2018.09.008
M3 - Journal article
VL - 36
SP - 368
EP - 383
JO - Government Information Quarterly
JF - Government Information Quarterly
SN - 0740-624X
IS - 2
ER -